Video coding and decoding method, device, equipment, system and storage medium

Abstract

The invention provides a video coding and decoding method, device, equipment and system and a storage medium, and the method comprises the steps: taking a first weight export mode and K first prediction modes as a combination, and indicating the first weight export mode and the K first prediction modes in a combination form, in this way, there is no need to independently transmit K grammars corresponding to the first prediction mode and the first weight export mode in the code stream, so that code words are saved, and the coding efficiency is improved. Besides, when the current component block corresponds to the plurality of first component CUs and the prediction modes of the plurality of first component CUs are not completely the same, the first weight export mode and the K first prediction modes included in the first combination can be accurately determined, so that the prediction efficiency is improved by using the first weight export mode and the K first prediction modes. And accurate prediction of the current component block is realized.

Description

Video encoding and decoding method, device, equipment, system, and storage medium Technical Field The present application relates to the field of video coding and decoding technology, and in particular to a video coding and decoding method, device, equipment, system, and storage medium. Background Art Digital video technology can be incorporated into a variety of video devices, such as digital televisions, smart phones, computers, e-readers or video players, etc. With the development of video technology, the amount of data included in video data is large. In order to facilitate the transmission of video data, video devices implement video compression technology to make video data more efficiently transmitted or stored. Since there is temporal or spatial redundancy in the video, prediction can eliminate or reduce the redundancy in the video and improve compression efficiency. Currently, in order to improve the prediction effect, multiple prediction modes can be used to predict the current block. However, when using multiple prediction modes to predict the current block, more information needs to be transmitted in the bitstream, which increases the encoding cost. Summary of the invention The embodiments of the present application provide a video encoding and decoding method, apparatus, device, system, and storage medium, which can reduce the encoding cost. In a first aspect, the present application provides a video decoding method, applied to a decoder, comprising: Decoding the bitstream, determining a first combination, wherein the first combination includes a first weight derivation mode and K first prediction modes, where K is a positive integer greater than 1; The current component block is predicted according to the first weight derivation mode and the K first prediction modes to obtain a prediction value of the current component block, where the current component block includes the second component block or the third component block. In a second aspect, an embodiment of the present application provides a video encoding method, including: Determine a first combination, wherein the first combination includes a first weight derivation mode and K first prediction modes, where K is a positive integer greater than 1; The current component block is predicted according to the first weight derivation mode and the K first prediction modes to obtain a prediction value of the current component block, where the current component block includes the second component block or the third component block. In a third aspect, the present application provides a video decoding device, which is used to execute the method in the first aspect or its respective implementations. Specifically, the device includes a functional unit for executing the method in the first aspect or its respective implementations. In a fourth aspect, the present application provides a video encoding device, which is used to execute the method in the second aspect or its respective implementations. Specifically, the device includes a functional unit for executing the method in the second aspect or its respective implementations. In a fifth aspect, a video decoder is provided, comprising a processor and a memory, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute the method in the first aspect or its implementations. In a sixth aspect, a video encoder is provided, comprising a processor and a memory, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute the method in the second aspect or its implementations. In a seventh aspect, a video coding and decoding system is provided, including a video encoder and a video decoder. The video decoder is used to execute the method in the first aspect or its respective implementations, and the video encoder is used to execute the method in the second aspect or its respective implementations. In an eighth aspect, a chip is provided for implementing the method in any one of the first to second aspects or their respective implementations. Specifically, the chip includes: a processor for calling and running a computer program from a memory, so that a device equipped with the chip executes the method in any one of the first to second aspects or their respective implementations. In a ninth aspect, a computer-readable storage medium is provided for storing a computer program, wherein the computer program enables a computer to execute the method of any one of the first to second aspects or any of their implementations. In a tenth aspect, a computer program product is provided, comprising computer program instructions, which enable a computer to execute the method in any one of the first to second aspects or their respective implementations. In an eleventh aspect, a computer program is provided, which, when executed on a computer, enables the computer to execute the method in any one of the first to second aspects or in each of their implementations. In the twelfth aspect, a code stream is provided, which is generated based on the method of the second aspect. Optionally, the code stream includes a first index, which is used to indicate a first combination consisting of a weight derivation mode and K prediction modes, where K is a positive integer greater than 1. Based on the above technical solution, the present application regards the first weight derivation mode and the K first prediction modes as a combination, and indicates the first weight derivation mode and the K first prediction modes in the form of a combination, so that there is no need to separately transmit the syntax corresponding to the K first prediction modes and the first weight derivation mode in the code stream, thereby saving code words and improving coding efficiency. In addition, in an embodiment of the present application, when the current component block corresponds to multiple first component CUs and the prediction modes of the multiple first component CUs are not exactly the same, the first weight derivation mode and the K first prediction modes included in the first combination can also be accurately determined, and then the first weight derivation mode and the K first prediction modes can be used to achieve accurate prediction of the current component block. BRIEF DESCRIPTION OF THE DRAWINGS FIG1 is a schematic block diagram of a video encoding and decoding system according to an embodiment of the present application; FIG2 is a schematic block diagram of a video encoder according to an embodiment of the present application; FIG3 is a schematic block diagram of a video decoder according to an embodiment of the present application; Figure 4 is a schematic diagram of weight allocation; Figure 5 is a schematic diagram of weight allocation; FIG6A is a schematic diagram of inter-frame prediction; FIG6B is a schematic diagram of weighted inter-frame prediction; FIG7A is a schematic diagram of intra-frame prediction; FIG7B is a schematic diagram of intra-frame prediction; 8A-8I are schematic diagrams of intra-frame prediction; FIG9 is a schematic diagram of an intra-frame prediction mode; FIG10 is a schematic diagram of an intra-frame prediction mode; FIG11 is a schematic diagram of an intra-frame prediction mode; FIG12 is a schematic diagram of a MIP; FIG13 is a schematic diagram of weighted prediction; FIG14 is a schematic diagram of first component block matching; FIG15 is a schematic diagram of the CCLM principle involved in an embodiment of the present application; FIG16 is a schematic diagram of a video decoding method flow chart provided by an embodiment of the present application; 17A to 17D are schematic diagrams of block division methods; FIG17E is a schematic diagram of a CTU partition; FIG17F is a schematic diagram of a block division method of a luminance component and a chrominance component according to an embodiment of the present application; FIG18 is a schematic diagram of a current component block and a specific position block involved in an embodiment of the present application; FIG19A is a schematic diagram of weight allocation; FIG19B is another schematic diagram of weight allocation; FIG20 is a schematic diagram of a video encoding method flow chart provided in an embodiment of the present application; FIG21 is a schematic block diagram of a video decoding device provided by an embodiment of the present application; FIG22 is a schematic block diagram of a video encoding device provided by an embodiment of the present application; FIG23 is a schematic block diagram of an electronic device provided in an embodiment of the present application; Figure 24 is a schematic block diagram of a video encoding and decoding system provided in an embodiment of the present application. DETAILED DESCRIPTION The present application can be applied to the field of image coding and decoding, the field of video coding and decoding, the field of hardware video coding and decoding, the field of dedicated circuit video coding and decoding, the field of real-time video coding and decoding, etc. For example, the scheme of the present application can be combined with an audio and video coding standard (AVS), such as the H.264 / audio video coding (AVC) standard, the H.265 / high efficiency video coding (HEVC) standard, and the H.266 / versatile video coding (VVC) standard. Alternatively, the scheme of the present application can be combined with other proprietary or industry standards and operate, and the standards include ITU-TH.261, ISO / IECMPEG-1Visual, ITU-TH.262 or ISO / IECMPEG-2Visual, ITU-TH.263, ISO / IECMPEG-4Visual, ITU-TH.264 (also known as ISO / IECMPEG-4AVC), including scalable video coding (SVC) and multi-view video coding (MVC) extensions. It should be understood that the technology of the present application is not limited to any specific coding standard or technology. For ease of understanding, the video encoding and decoding system involved in the embodiment of the present application is first introduced in conjunction with Figure 1. FIG1 is a schematic block diagram of a video encoding and decoding system involved in an embodiment of the present application. It should be noted that FIG1 is only an example, and the video encoding and decoding system of the embodiment of the present application includes but is not limited to that shown in FIG1. ​​As shown in FIG1, the video encoding and decoding system 100 includes an encoding device 110 and a decoding device 120. The encoding device is used to encode (which can be understood as compression) the video data to generate a code stream, and transmit the code stream to the decoding device. The decoding device decodes the code stream generated by the encoding device to obtain decoded video data. The encoding device 110 of the embodiment of the present application can be understood as a device with a video encoding function, and the decoding device 120 can be understood as a device with a video decoding function, that is, the embodiment of the present application includes a wider range of devices for the encoding device 110 and the decoding device 120, such as smartphones, desktop computers, mobile computing devices, notebook (e.g., laptop) computers, tablet computers, set-top boxes, televisions, cameras, display devices, digital media players, video game consoles, vehicle-mounted computers, etc. In some embodiments, the encoding device 110 may transmit the encoded video data (eg, a code stream) to the decoding device 120 via the channel 130. The channel 130 may include one or more media and / or devices capable of transmitting the encoded video data from the encoding device 110 to the decoding device 120. In one example, the channel 130 includes one or more communication media that enable the encoding device 110 to transmit the encoded video data directly to the decoding device 120 in real time. In this example, the encoding device 110 can modulate the encoded video data according to the communication standard and transmit the modulated video data to the decoding device 120. The communication medium includes a wireless communication medium, such as a radio frequency spectrum, and optionally, the communication medium may also include a wired communication medium, such as one or more physical transmission lines. In another example, the channel 130 includes a storage medium, which can store the video data encoded by the encoding device 110. The storage medium includes a variety of locally accessible data storage media, such as optical disks, DVDs, flash memories, etc. In this example, the decoding device 120 can obtain the encoded video data from the storage medium. In another example, the channel 130 may include a storage server that can store the video data encoded by the encoding device 110. In this example, the decoding device 120 can download the stored encoded video data from the storage server. Alternatively, the storage server can store the encoded video data and transmit the encoded video data to the decoding device 120, such as a web server (e.g., for a website), a file transfer protocol (FTP) server, etc. In some embodiments, the encoding device 110 includes a video encoder 112 and an output interface 113. The output interface 113 may include a modulator / demodulator (modem) and / or a transmitter. In some embodiments, the encoding device 110 may further include a video source 111 in addition to the video encoder 112 and the input interface 113 . The video source 111 may include at least one of a video acquisition device (eg, a video camera), a video archive, a video input interface, and a computer graphics system, wherein the video input interface is used to receive video data from a video content provider, and the computer graphics system is used to generate video data. The video encoder 112 encodes the video data from the video source 111 to generate a code stream. The video data may include one or more pictures or a sequence of pictures. The code stream contains the coding information of the picture or the sequence of pictures in the form of a bit stream. The coding information may include the coded picture data and associated data. The associated data may include a sequence parameter set (SPS for short), a picture parameter set (PPS for short) and other syntax structures. The SPS may contain parameters applied to one or more sequences. The PPS may contain parameters applied to one or more pictures. The syntax structure refers to a set of zero or more syntax elements arranged in a specified order in the code stream. The video encoder 112 transmits the encoded video data directly to the decoding device 120 via the output interface 113. The encoded video data may also be stored in a storage medium or a storage server for subsequent reading by the decoding device 120. In some embodiments, the decoding device 120 includes an input interface 121 and a video decoder 122 . In some embodiments, the decoding device 120 may include a display device 123 in addition to the input interface 121 and the video decoder 122 . The input interface 121 includes a receiver and / or a modem. The input interface 121 can receive the encoded video data through the channel 130 . The video decoder 122 is used to decode the encoded video data to obtain decoded video data, and transmit the decoded video data to the display device 123 . The display device 123 displays the decoded video data. The display device 123 may be integrated with the decoding device 120 or external to the decoding device 120. The display device 123 may include a variety of display devices, such as a liquid crystal display (LCD), a plasma display, an organic light emitting diode (OLED) display, or other types of display devices. In addition, FIG1 is only an example, and the technical solution of the embodiment of the present application is not limited to FIG1 . For example, the technology of the present application can also be applied to unilateral video encoding or unilateral video decoding. The following is an introduction to the video encoding framework involved in the embodiments of the present application. Fig. 2 is a schematic block diagram of a video encoder involved in an embodiment of the present application. It should be understood that the video encoder 200 can be used to perform lossy compression on an image, or can be used to perform lossless compression on an image. The lossless compression can be visually lossless compression or mathematically lossless compression. The video encoder 200 can be applied to image data in luminance and chrominance (YCbCr, YUV) format. For example, the YUV ratio can be 4:2:0, 4:2:2 or 4:4:4, Y represents brightness (Luma), Cb (U) represents blue chrominance, Cr (V) represents red chrominance, and U and V represent chrominance (Chroma) for describing color and saturation. For example, in color format, 4:2:0 means that every 4 pixels have 4 luminance components and 2 chrominance components (YYYYCbCr), 4:2:2 means that every 4 pixels have 4 luminance components and 4 chrominance components (YYYYCbCrCbCr), and 4:4:4 means full pixel display (YYYYCbCrCbCrCbCrCbCr). For example, the video encoder 200 reads video data, and for each frame of the video data, divides the frame into a number of coding tree units (CTUs). In some examples, CTB may be referred to as a "tree block", "largest coding unit" (LCU) or "coding tree block" (CTB). Each CTU may be associated with a pixel block of equal size within the image. Each pixel may correspond to a luminance (luminance or luma) sample and two chrominance (chrominance or chroma) samples. Therefore, each CTU may be associated with a luminance sample block and two chrominance sample blocks. The size of a CTU is, for example, 128×128, 64×64, 32×32, etc. A CTU may be further divided into a number of coding units (CUs) for encoding, and a CU may be a rectangular block or a square block. CU can be further divided into prediction unit (PU) and transform unit (TU), so that coding, prediction and transform are separated and more flexible in processing. In one example, CTU is divided into CU in quadtree mode, and CU is divided into TU and PU in quadtree mode. The video encoder and video decoder may support various PU sizes. Assuming that the size of a particular CU is 2N×2N, the video encoder and video decoder may support PU sizes of 2N×2N or N×N for intra-frame prediction, and support symmetric PUs of 2N×2N, 2N×N, N×2N, N×N or similar sizes for inter-frame prediction. The video encoder and video decoder may also support asymmetric PUs of 2N×nU, 2N×nD, nL×2N, and nR×2N for inter-frame prediction. In some embodiments, as shown in FIG2 , the video encoder 200 may include: a prediction unit 210, a residual unit 220, a transform / quantization unit 230, an inverse transform / quantization unit 240, a reconstruction unit 250, a loop filter unit 260, a decoded image buffer 270, and an entropy coding unit 280. It should be noted that the video encoder 200 may include more, fewer, or different functional components. Optionally, in the present application, the current block may be referred to as a current coding unit (CU) or a current prediction unit (PU), etc. A prediction block may also be referred to as a prediction image block or an image prediction block, and a reconstructed image block may also be referred to as a reconstructed block or an image reconstructed image block. In some embodiments, the prediction unit 210 includes an inter-frame prediction unit 211 and an intra-frame prediction unit 212. Since there is a strong correlation between adjacent pixels in a frame of a video, the intra-frame prediction method is used in the video coding and decoding technology to eliminate the spatial redundancy between adjacent pixels. Since there is a strong similarity between adjacent frames in a video, the inter-frame prediction method is used in the video coding and decoding technology to eliminate the temporal redundancy between adjacent frames, thereby improving the coding efficiency. The inter-frame prediction unit 211 can be used for inter-frame prediction. Inter-frame prediction can include motion estimation and motion compensation. It can refer to the image information of different frames. Inter-frame prediction uses motion information to find reference blocks from reference frames and generates prediction blocks based on the reference blocks to eliminate temporal redundancy. The frames used for inter-frame prediction can be P frames and / or B frames. P frames refer to forward prediction frames and B frames refer to bidirectional prediction frames. Inter-frame prediction uses motion information to find reference blocks from reference frames and generates prediction blocks based on the reference blocks. Motion information includes a reference frame list where the reference frame is located, a reference frame index, and a motion vector. The motion vector can be an integer pixel or a sub-pixel. If the motion vector is a sub-pixel, it is necessary to use interpolation filtering in the reference frame to make the required sub-pixel block. Here, the integer pixel or sub-pixel block in the reference frame found according to the motion vector is called a reference block. Some technologies will directly use the reference block as a prediction block, while some technologies will generate a prediction block based on the reference block. Reprocessing the prediction block based on the reference block can also be understood as using the reference block as a prediction block and then processing the prediction block to generate a new prediction block. The intra-frame prediction unit 212 only refers to the information of the same frame image to predict the pixel information in the current code image block to eliminate spatial redundancy. The frame used for intra-frame prediction can be an I frame. There are multiple prediction modes for intra-frame prediction. Taking the H series of international digital video coding standards as an example, the H.264 / AVC standard has 8 angle prediction modes and 1 non-angle prediction mode, and H.265 / HEVC is extended to 33 angle prediction modes and 2 non-angle prediction modes. The intra-frame prediction modes used by HEVC are Planar, DC, and 33 angle modes, for a total of 35 prediction modes. The intra-frame modes used by VVC are Planar, DC, and 65 angle modes, for a total of 67 prediction modes. It should be noted that with the increase of angle modes, intra-frame prediction will be more accurate and more in line with the needs of the development of high-definition and ultra-high-definition digital videos. The residual unit 220 may generate a residual block of the CU based on the pixel blocks of the CU and the prediction blocks of the PUs of the CU. For example, the residual unit 220 may generate a residual block of the CU so that each sample in the residual block has a value equal to the difference between the following two: a sample in the pixel blocks of the CU and a corresponding sample in the prediction blocks of the PUs of the CU. The transform / quantization unit 230 may quantize the transform coefficients. The transform / quantization unit 230 may quantize the transform coefficients associated with the TUs of the CU based on a quantization parameter (QP) value associated with the CU. The video encoder 200 may adjust the degree of quantization applied to the transform coefficients associated with the CU by adjusting the QP value associated with the CU. The inverse transform / quantization unit 240 may apply inverse quantization and inverse transform to the quantized transform coefficients, respectively, to reconstruct a residual block from the quantized transform coefficients. The reconstruction unit 250 may add the samples of the reconstructed residual block to the corresponding samples of one or more prediction blocks generated by the prediction unit 210 to generate a reconstructed image block associated with the TU. By reconstructing the sample blocks of each TU of the CU in this manner, the video encoder 200 may reconstruct the pixel blocks of the CU. The loop filter unit 260 is used to process the inverse transformed and inverse quantized pixels to compensate for distortion information and provide a better reference for subsequent coded pixels. For example, a deblocking filter operation may be performed to reduce the blocking effect of the pixel blocks associated with the CU. In some embodiments, the loop filter unit 260 includes a deblocking filter unit and a sample adaptive offset / adaptive loop filter (SAO / ALF) unit, wherein the deblocking filter unit is used to remove the block effect, and the SAO / ALF unit is used to remove the ringing effect. The decoded image buffer 270 may store the reconstructed pixel blocks. The inter prediction unit 211 may use the reference image containing the reconstructed pixel blocks to perform inter prediction on PUs of other images. In addition, the intra prediction unit 212 may use the reconstructed pixel blocks in the decoded image buffer 270 to perform intra prediction on other PUs in the same image as the CU. The entropy encoding unit 280 may receive the quantized transform coefficients from the transform / quantization unit 230. The entropy encoding unit 280 may perform one or more entropy encoding operations on the quantized transform coefficients to generate entropy-encoded data. FIG. 3 is a schematic block diagram of a video decoder according to an embodiment of the present application. 3 , the video decoder 300 includes an entropy decoding unit 310, a prediction unit 320, an inverse quantization / transformation unit 330, a reconstruction unit 340, a loop filter unit 350, and a decoded image buffer 360. It should be noted that the video decoder 300 may include more, fewer, or different functional components. The video decoder 300 may receive a bitstream. The entropy decoding unit 310 may parse the bitstream to extract syntax elements from the bitstream. As part of parsing the bitstream, the entropy decoding unit 310 may parse the syntax elements in the bitstream that have been entropy encoded. The prediction unit 320, the inverse quantization / transformation unit 330, the reconstruction unit 340, and the loop filter unit 350 may decode the video data according to the syntax elements extracted from the bitstream, that is, generate decoded video data. In some embodiments, the prediction unit 320 includes an intra prediction unit 322 and an inter prediction unit 321 . The intra prediction unit 322 may perform intra prediction to generate a prediction block for the PU. The intra prediction unit 322 may use an intra prediction mode to generate a prediction block for the PU based on pixel blocks of spatially neighboring PUs. The intra prediction unit 322 may also determine the intra prediction mode of the PU according to one or more syntax elements parsed from the code stream. The inter prediction unit 321 may construct a first reference image list (list 0) and a second reference image list (list 1) according to the syntax elements parsed from the code stream. In addition, if the PU is encoded using inter prediction, the entropy decoding unit 310 may parse the motion information of the PU. The inter prediction unit 321 may determine one or more reference blocks of the PU according to the motion information of the PU. The inter prediction unit 321 may generate a prediction block of the PU according to one or more reference blocks of the PU. The inverse quantization / transform unit 330 may inversely quantize (ie, dequantize) the transform coefficients associated with the TU. The inverse quantization / transform unit 330 may use the QP value associated with the CU of the TU to determine the degree of quantization. After inverse quantizing the transform coefficients, the inverse quantization / transform unit 330 may apply one or more inverse transforms to the inverse quantized transform coefficients in order to generate a residual block associated with the TU. The reconstruction unit 340 uses the residual block associated with the TU of the CU and the prediction block of the PU of the CU to reconstruct the pixel block of the CU. For example, the reconstruction unit 340 may add samples of the residual block to corresponding samples of the prediction block to reconstruct the pixel block of the CU to obtain a reconstructed image block. The loop filtering unit 350 may perform a deblocking filtering operation to reduce blocking effects of pixel blocks associated with a CU. The video decoder 300 may store the reconstructed image of the CU in the decoded image buffer 360. The video decoder 300 may use the reconstructed image in the decoded image buffer 360 as a reference image for subsequent prediction, or transmit the reconstructed image to a display device for presentation. The basic process of video encoding and decoding is as follows: at the encoding end, a frame of image is divided into blocks, and for the current block, the prediction unit 210 uses intra-frame prediction or inter-frame prediction to generate a prediction block of the current block. The residual unit 220 can calculate the residual block based on the original block of the prediction block and the current block, that is, the difference between the original block of the prediction block and the current block, and the residual block can also be called residual information. The residual block can remove information that is not sensitive to the human eye through the transformation and quantization process of the transformation / quantization unit 230 to eliminate visual redundancy. Optionally, the residual block before transformation and quantization by the transformation / quantization unit 230 can be called a time domain residual block, and the time domain residual block after transformation and quantization by the transformation / quantization unit 230 can be called a frequency residual block or a frequency domain residual block. The entropy coding unit 280 receives the quantized change coefficient output by the change quantization unit 230, and can entropy encode the quantized change coefficient and output a bit stream. For example, the entropy coding unit 280 can eliminate character redundancy according to the target context model and the probability information of the binary bit stream. At the decoding end, the entropy decoding unit 310 can parse the code stream to obtain the prediction information, quantization coefficient matrix, etc. of the current block. The prediction unit 320 uses intra-frame prediction or inter-frame prediction to generate a prediction block of the current block based on the prediction information. The inverse quantization / transformation unit 330 uses the quantization coefficient matrix obtained from the code stream to inverse quantize and inverse transform the quantization coefficient matrix to obtain a residual block. The reconstruction unit 340 adds the prediction block and the residual block to obtain a reconstructed block. The reconstructed blocks constitute a reconstructed image, and the loop filtering unit 350 performs loop filtering on the reconstructed image based on the image or on the block to obtain a decoded image. The encoding end also requires similar operations as the decoding end to obtain a decoded image. The decoded image can also be called a reconstructed image, and the reconstructed image can be used as a reference frame for inter-frame prediction for subsequent frames. It should be noted that the block division information determined by the encoder, as well as the mode information or parameter information such as prediction, transformation, quantization, entropy coding, loop filtering, etc., are carried in the bitstream when necessary. The decoder parses the bitstream and determines the same block division information, prediction, transformation, quantization, entropy coding, loop filtering, etc. mode information or parameter information as the encoder by analyzing the existing information, thereby ensuring that the decoded image obtained by the encoder is the same as the decoded image obtained by the decoder. The above is the basic process of the video codec under the block-based hybrid coding framework. With the development of technology, some modules or steps of the framework or process may be optimized. The present application is applicable to the basic process of the video codec under the block-based hybrid coding framework, but is not limited to the framework and process. In some embodiments, the current block may be a current coding unit (CU) or a current prediction unit (PU), etc. Due to the need for parallel processing, an image may be divided into slices, etc. Slices in the same image may be processed in parallel, that is, there is no data dependency between them. "Frame" is a commonly used term, and it can generally be understood that a frame is an image. In the application, the frame may also be replaced by an image or a slice, etc. The Versatile Video Coding (VVC) video codec standard currently under development has an inter-frame prediction mode called Geometric partitioning mode (GPM). The Audio Video coding Standard (AVS) video codec standard currently under development has an inter-frame prediction mode called Angular Weighted prediction (AWP). Although these two modes have different names and specific implementation forms, they have something in common in principle. It should be noted that the traditional unidirectional prediction only finds a reference block with the same size as the current block, and the traditional bidirectional prediction uses two reference blocks with the same size as the current block, and the pixel value of each point in the prediction block is the average of the corresponding positions of the two reference blocks, that is, all points in each reference block account for 50%. Bidirectional weighted prediction allows the proportions of the two reference blocks to be different, such as all points in the first reference block account for 75%, and all points in the second reference block account for 25%. But the proportions of all points in the same reference block are the same. But the proportions of all points in the same reference block are the same. Some other optimization methods, such as the use of decoder side motion vector refinement (DMVR) technology, bidirectional optical flow (BIO), etc., will cause some changes in reference pixels or predicted pixels, but have nothing to do with the principles mentioned above. BIO can also be abbreviated as BDOF. GPM or AWP also uses two reference blocks with the same size as the current block, but some pixel positions use 100% of the pixel values ​​of the corresponding positions of the first reference block, and some pixel positions use 100% of the pixel values ​​of the corresponding positions of the second reference block. In the boundary area or transition area, the pixel values ​​of the corresponding positions of the two reference blocks are used in a certain proportion. The weight of the boundary area is also gradually transitioned. How these weights are specifically distributed is determined by the mode of GPM or AWP. The weight of each pixel position is determined according to the mode of GPM or AWP. Of course, in some cases, such as when the block size is very small, it may be impossible to guarantee that some pixel positions use 100% of the pixel values ​​of the corresponding positions of the first reference block and some pixel positions use 100% of the pixel values ​​of the corresponding positions of the second reference block in some GPM or AWP modes. It can also be considered that GPM or AWP uses two reference blocks of different sizes from the current block, that is, each takes a required part as a reference block. That is, the part with a weight not equal to 0 is used as a reference block, and the part with a weight equal to 0 is eliminated. This is an implementation problem and is not the focus of the present invention. Exemplarily, FIG4 is a weight allocation diagram, as shown in FIG4, which shows a weight allocation diagram of a GPM provided in an embodiment of the present application on a 64×64 current block of multiple partition modes, wherein GPM has 64 partition modes. FIG5 is a weight allocation diagram, as shown in FIG5, which shows a weight allocation diagram of an AWP provided in an embodiment of the present application on a 64×64 current block of multiple partition modes, wherein AWP has 56 partition modes. Regardless of FIG4 or FIG5, in each partition mode, the black area indicates that the weight value of the corresponding position of the first reference block is 0%, the white area indicates that the weight value of the corresponding position of the first reference block is 100%, and the gray area indicates that the weight value of the corresponding position of the first reference block is a certain weight value greater than 0% and less than 100% according to the different shades of color, and the weight value of the corresponding position of the second reference block is 100% minus the weight value of the corresponding position of the first reference block. GPM and AWP have different weight derivation methods. GPM determines the angle and offset for each mode, and then calculates the weight matrix for each mode. AWP first makes a one-dimensional weight line, and then uses a method similar to intra-frame angle prediction to fill the one-dimensional weight line throughout the matrix. It should be understood that in the early coding and decoding technologies, there were only rectangular division methods, whether it was the division of CU, PU or transform unit (TU). However, GPM or AWP achieved the predicted non-rectangular division effect without division. GPM and AWP use a mask of the weights of two reference blocks, that is, the weight map mentioned above. This mask determines the weights of the two reference blocks when generating the prediction block, or it can be simply understood that part of the position of the prediction block comes from the first reference block and part of the position comes from the second reference block, and the transition area (blending area) is weighted by the corresponding positions of the two reference blocks, so that the transition is smoother. GPM and AWP do not divide the current block into two CUs or PUs according to the dividing line, so the transformation, quantization, inverse transformation, inverse quantization, etc. of the residual after prediction also treat the current block as a whole. GPM uses a weight matrix to simulate the division of geometric shapes, or more precisely, the division of predictions. To implement GPM, in addition to the weight matrix, two prediction values ​​are required, each of which is determined by one unidirectional motion information. These two unidirectional motion information come from a motion information candidate list, such as a merge motion information candidate list (mergeCandList). GPM uses two indexes in the bitstream to determine the two unidirectional motion information from the mergeCandList. Inter-frame prediction uses motion information to represent "motion". Basic motion information includes information about the reference frame (or reference picture) and information about the motion vector (MV). Commonly used bidirectional prediction uses two reference blocks to predict the current block. The two reference blocks can use a forward reference block and a backward reference block. Optionally, both are forward or both are backward. The so-called forward refers to the time corresponding to the reference frame before the current frame, and the backward refers to the time corresponding to the reference frame after the current frame. In other words, forward means that the position of the reference frame in the video is before the current frame, and backward means that the position of the reference frame in the video is after the current frame. In other words, forward means that the POC (picture order count) of the reference frame is less than the POC of the current frame, and backward means that the POC of the reference frame is greater than the POC of the current frame. In order to use bidirectional prediction, it is naturally necessary to find two reference blocks, so two sets of reference frame information and motion vector information are required. Each of these groups can be understood as a unidirectional motion information, and the two groups are combined to form a bidirectional motion information. In specific implementation, the unidirectional motion information and the bidirectional motion information can use the same data structure, but the two groups of reference frame information and motion vector information of the bidirectional motion information are both valid, while one group of reference frame information and motion vector information of the unidirectional motion information is invalid. In some embodiments, two reference frame lists are supported, denoted as RPL0 and RPL1, where RPL is the abbreviation of Reference Picture List. In some embodiments, P slice can only use RPL0, and B slice can use RPL0 and RPL1. For a slice, there are several reference frames in each reference frame list, and the codec finds a reference frame through the reference frame index. In some embodiments, the motion information is represented by the reference frame index and the motion vector. For example, for the above-mentioned bidirectional motion information, the reference frame index refIdxL0 corresponding to the reference frame list 0 and the motion vector mvL0 corresponding to the reference frame list 0, the reference frame index refIdxL1 corresponding to the reference frame list 1, and the motion vector mvL0 corresponding to the reference frame list 1 are used. Here, the reference frame index corresponding to the reference frame list 0 and the reference frame index corresponding to the reference frame list 1 can be understood as the above-mentioned reference frame information. In some embodiments, two flag bits are used to respectively indicate whether the motion information corresponding to the reference frame list 0 and the motion information corresponding to the reference frame list 0 are used, which are respectively denoted as predFlagL0 and predFlagL1. It can also be understood that predFlagL0 and predFlagL1 indicate whether the above-mentioned unidirectional motion information is "valid". Although the data structure of motion information is not explicitly mentioned, it uses the reference frame index corresponding to each reference frame list, the motion vector and the "valid" flag to represent the motion information. In some standard texts, motion information does not appear, but motion vectors are used. It can also be considered that the reference frame index and the flag of whether to use the corresponding motion information are attached to the motion vector. In this application, "motion information" is still used for the convenience of description, but it should be understood that "motion vector" can also be used to describe it. The motion information used by the current block can be saved. The subsequent coded blocks of the current frame can use the motion information of the previously coded blocks, such as adjacent blocks, according to the adjacent position relationship. This utilizes the correlation in the spatial domain, so this coded motion information is called motion information in the spatial domain. The motion information used by each block of the current frame can be saved. The subsequent coded frames can use the motion information of the previously coded frames according to the reference relationship. This utilizes the correlation in the temporal domain, so the motion information of the coded frames is called motion information in the temporal domain. The storage method of the motion information used by each block of the current frame usually uses a matrix of a fixed size, such as a 4x4 matrix, as a minimum unit, and each minimum unit stores a set of motion information separately. In this way, each time a block is coded and decoded, the minimum units corresponding to its position can store the motion information of this block. In this way, when using the motion information in the spatial domain or the motion information in the temporal domain, the motion information corresponding to the position can be directly found according to the position. If a 16x16 block uses traditional unidirectional prediction, then all 4x4 minimum units corresponding to this block store the motion information of this unidirectional prediction. If a block uses GPM or AWP, then all the minimum units corresponding to this block will determine the motion information stored in each minimum unit based on the GPM or AWP mode, the first motion information, the second motion information, and the position of each minimum unit. One method is that if the 4x4 pixels corresponding to a minimum unit all come from the first motion information, then this minimum unit stores the first motion information; if the 4x4 pixels corresponding to a minimum unit all come from the second motion information, then this minimum unit stores the second motion information. If the 4x4 pixels corresponding to a minimum unit come from both the first motion information and the second motion information, then AWP will select one of the motion information to store; GPM's approach is that if the two motion information point to different reference frame lists, then they are combined into bidirectional motion information for storage, otherwise only the second motion information is stored. Optionally, the above mergeCandList is constructed based on spatial motion information, temporal motion information, historical motion information, and some other motion information. Exemplarily, mergeCandList uses positions 1 to 5 in Figure 6A to derive spatial motion information, and uses positions 6 or 7 in Figure 6A to derive temporal motion information. Historical motion information is to add the motion information of this block to a first-in-first-out list every time a block is encoded or decoded. The adding process may require some checks, such as whether it is repeated with the existing motion information in the list. In this way, the motion information in this history-based list can be referred to when encoding and decoding the current block. In some embodiments, the syntax description of GPM is shown in Table 1: Table 1 As shown in Table 1, in merge mode, if regular_merge_flag is not 1, the current block may use CIIP or GPM. If the current block does not use CIIP, it uses GPM, which is the content shown in the syntax "if (!ciip_flag [x0] [y0])" in Table 1. As can be seen from Table 1 above, GPM needs to transmit three pieces of information in the bitstream, namely merge_gpm_partition_idx, merge_gpm_idx0, merge_gpm_idx1. x0, y0 are used to determine the coordinates (x0, y0) of the upper left corner brightness pixel of the current block relative to the upper left corner brightness pixel of the image. merge_gpm_partition_idx determines the division shape of GPM. As mentioned above, it is "simulated division". merge_gpm_partition_idx is what is referred to in this article as the weight matrix derivation mode or the index of the weight matrix derivation mode, or the weight derivation mode or the index of the weight derivation mode. merge_gpm_idx0 is the first merge candidate index. The first merge candidate index is used to determine the first motion information or the first merge candidate according to mergeCandList. merge_gpm_idx1 is the second merge candidate index. The second merge candidate index is used to determine the second motion information or the second merge candidate according to mergeCandList. If MaxNumGpmMergeCand>2, that is, the length of the candidate list is greater than 2, merge_gpm_idx1 needs to be decoded, otherwise it can be determined directly. In some embodiments, the decoding process of the GPM includes the following steps: The information input to the decoding process includes: the coordinates (xCb, yCb) of the luminance position of the upper left corner of the current block relative to the upper left corner of the image, the width cbWidth of the luminance component of the current block, the height cbHeight of the luminance component of the current block, the luminance motion vectors mvA and mvB with 1 / 16 pixel accuracy, the chrominance motion vectors mvCA and mvCB, the reference frame indexes refIdxA and refIdxB, and the prediction list flags predListFlagA and predListFlagB. Exemplarily, motion information can be represented by combining motion vector, reference frame index and prediction list flag. VVC supports 2 reference frame lists, each of which may have multiple reference frames. Unidirectional prediction uses only one reference block of one reference frame in one of the reference frame lists as a reference, and bidirectional prediction uses one reference block of each reference frame in each of the two reference frame lists as a reference. GPM in VVC uses 2 unidirectional predictions. A in the above mvA and mvB, mvCA and mvCB, refIdxA and refIdxB, predListFlagA and predListFlagB can be understood as the first prediction mode, and B can be understood as the second prediction mode. We use X to represent A or B, predListFlagX to indicate whether X uses the first reference frame list or the second reference frame list, refIdxX to indicate the reference frame index in the reference frame list used by X, mvX to indicate the luminance motion vector used by X, and mvCX to indicate the chrominance motion vector used by X. To reiterate, it can be considered that in VVC, motion vector, reference frame index and prediction list flag are combined to represent the motion information described in this article. The information output by the decoding process includes: the luminance prediction sample matrix predSamplesL of (cbWidth)X(cbHeight); the prediction sample matrix of the Cb chrominance component of (cbWidth / SubWidthC)X(cbHeight / SubHeightC), if necessary; and the prediction sample matrix of the Cr chrominance component of (cbWidth / SubWidthC)X(cbHeight / SubHeightC), if necessary. Exemplarily, the following takes the brightness component as an example, and the processing of the chrominance component is similar to that of the brightness component. Assume that the size of predSamplesLAL and predSamplesLBL is (cbWidth)X(cbHeight), which is the prediction sample matrix made according to the two prediction modes. predSamplesL is derived as follows: predSamplesLAL and predSamplesLBL are determined according to the luminance motion vectors mvA and mvB, the chrominance motion vectors mvCA and mvCB, the reference frame indexes refIdxA and refIdxB, and the prediction list flags predListFlagA and predListFlagB. That is, predictions are made according to the motion information of the two prediction modes respectively, and the detailed process will not be repeated. Usually GPM is merge mode, and it can be considered that the two prediction modes of GPM are merge modes. According to merge_gpm_partition_idx[xCb][yCb], use Table 2 to determine the GPM partition angle index variable angleIdx and distance index variable distanceIdx. Table 2 – Correspondence between angleIdx and distanceIdx and merge_gpm_partition_idx merge_gpm_partition_idx0123456789101112131415angleIdx0022223333444455distanceIdx1301230123012301merge_gpm_partitio n_idx16171819202122232425262728293031angleIdx5588111111111212121213131313distanceIdx2313012301230123merge_gpm_parti tion_idx32333435363738394041424344454647angleIdx14141414161618181819191920202021distanceIdx0123131231231231merge_g pm_partition_idx48495051525354555657585960616263angleIdx21212424272727282828292929303030distanceIdx2313123123123123 It should be noted that because all three components (such as Y, Cb, Cr) can use GPM, some standard texts divide the process of generating the prediction sample matrix of GPM from one component into a sub-process, namely the weighted prediction process of GPM (Weighted sample prediction process for geometric partitioning mode). All three components will call this process, but the parameters of the call are different. Here, only the brightness component is used as an example. The prediction matrix predSamplesL[xL][yL] of the current brightness block (where xL = 0..cbWidth–1, yL = 0..cbHeight-1) is derived from the weighted prediction process of GPM. Among them, nCbW is set to cbWidth, nCbH is set to cbHeight, and the prediction sample matrices predSamplesLAL and predSamplesLBL made by the two prediction modes, as well as angleIdx and distanceIdx are used as input. In some embodiments, the weighted prediction derivation process of the GPM includes the following steps: The inputs of this process are: the width of the current block nCbW, the height of the current block nCbH; 2 (nCbW)X(nCbH) prediction sample matrices predSamplesLA and predSamplesLB; GPM division angle index variable angleIdx; GPM distance index variable distanceIdx; component index variable cIdx. This example takes brightness as an example, so the above cIdx is 0, indicating the brightness component. The output of this process is: (nCbW)X(nCbH) GPM prediction sample matrix pbSamples. For example, the variables nW, nH, shift1, offset1, displacementX, displacementY, partFlip and shiftHor are derived as follows: nW=(cIdx==0)? nCbW:nCbW*SubWidthC; nH=(cIdx==0)? nCbH:nCbH*SubHeightC; shift1 = Max(5,17-BitDepth), where BitDepth is the bit depth of the codec; offset1=1<<(shift1-1), where “<<” means left shift; displacementX = angleIdx; displacementY=(angleIdx+8)%32; partFlip=(angleIdx>=13&&angleIdx<=27)? 0:1; shiftHor=(angleIdx%16==8||(angleIdx%16!=0&&nH>=nW))? 0:1. The variables offsetX and offsetY are derived as follows: When the value of shiftHor is 0: offsetX=(-nW)>>1, offsetY=((-nH)>>1)+(angleIdx<16?(distanceIdx*nH)>>3:-((distanceIdx*nH)>>3)). When the value of shiftHor is 1: offsetX=((-nW)>>1)+(angleIdx<16?(distanceIdx*nW)>>3:-((distanceIdx*nW)>>3), offsetY=(-nH)>>1. The variables xL and yL are derived as follows: xL=(cIdx==0)? x:x*SubWidthC, yL=(cIdx==0)? y:y*SubHeightC, The variable wValue representing the weight of the predicted sample at the current position is derived as follows: wValue is the weight of the predicted value predSamplesLA[x][y] of the prediction matrix of the first prediction mode at the point (x, y), and (8-wValue) is the weight of the predicted value predSamplesLB[x][y] of the prediction matrix of the first prediction mode at the point (x, y). The distance matrix disLut is determined according to Table 3: Table 3 idx02345681011121314disLut[idx]8884420-2-4-4-8-8idx161819202122242627282930disLut[idx]-8-8-8-4-4-2024488 weightIdx=(((xL+offsetX)<<1)+1)*disLut[displacementX]+(((yL+offsetY)<<1)+1)*disLut[displacementY], weightIdxL=partFlip? 32+weightIdx:32–weightIdx, wValue=Clip3(0,8,(weightIdxL+4)>>3), The predicted sample values ​​pbSamples[x][y] are derived as follows: pbSamples[x][y]=Clip3(0,(1<<BitDepth)-1,(predSamplesLA[x][y]*wValue+predSamplesLB[x][y]*(8-wValue)+offset1)> >shift1). It should be noted that a weight value is derived for each position of the current block, and then a predicted value pbSamples[x][y] of GPM is calculated. Because of this method, the weight wValue does not have to be written in the form of a matrix, but it can be understood that if the wValue of each position is saved in a matrix, it is a weight matrix. The principle is the same for calculating the weight of each point separately and weighting it to obtain the predicted value of GPM, or calculating all the weights and then uniformly weighting them to obtain the predicted sample matrix of GPM. The term weight matrix is ​​used in many descriptions of this application to make the expression easier to understand, and it is more intuitive to draw pictures with weight matrices. In fact, it can also be described according to the weight of each position. For example, the weight matrix export mode can also be referred to as the weight export mode. In some embodiments, as shown in FIG6B , the decoding process of GPM can be described as follows: parsing the bitstream, determining whether the current block uses the GPM technology; if the current block uses the GPM technology, determining the weight derivation mode (or the division mode or the weight matrix derivation mode), and the first motion information and the second motion information. Determine the first prediction block according to the first motion information, determine the second prediction block according to the second motion information, determine the weight matrix according to the weight matrix derivation mode, and determine the prediction block of the current block according to the first prediction block, the second prediction block and the weight matrix. The intra-frame prediction method uses the reconstructed pixels that have been coded and decoded around the current block as reference pixels to predict the current block. Figure 7A is a schematic diagram of intra-frame prediction. As shown in Figure 7A, the size of the current block is 4x4, and the pixels in one row to the left and one column above the current block are the reference pixels of the current block. Intra-frame prediction uses these reference pixels to predict the current block. These reference pixels may all be available, that is, all have been coded and decoded. Some may also be unavailable, for example, the current block is the leftmost of the entire frame, then the reference pixels on the left of the current block are unavailable. Or when encoding and decoding the current block, the lower left part of the current block has not been coded and decoded, then the reference pixels on the lower left are also unavailable. For the case where reference pixels are unavailable, available reference pixels or certain values ​​or certain methods can be used for filling, or no filling can be performed. FIG7B is a schematic diagram of intra prediction. As shown in FIG7B , the multiple reference line intra prediction method (MRL) can use more reference pixels to improve encoding and decoding efficiency, for example, using 4 reference rows / columns as reference pixels of the current block. Furthermore, there are multiple prediction modes for intra-frame prediction. FIG8A-5I is a schematic diagram of intra-frame prediction. As shown in FIG8A-5I, intra-frame prediction for 4x4 blocks in H.264 can mainly include 9 modes. Among them, mode 0 as shown in FIG8A copies the pixels above the current block to the current block in a vertical direction as a prediction value, mode 1 as shown in FIG8B copies the reference pixels on the left to the current block in a horizontal direction as a prediction value, mode 2 DC as shown in FIG8C uses the average value of the eight points A to D and I to L as the prediction value of all points, and modes 3 to 8 as shown in FIG8D-5I copy the reference pixels to the corresponding positions of the current block at a certain angle, because some positions of the current block cannot correspond exactly to the reference pixels, and may need to use the weighted average value of the reference pixels, or the sub-pixels of the interpolated reference pixels. In addition, there are Plane, Planar and other modes, and with the development of technology and the expansion of blocks, there are more and more angle prediction modes. Figure 9 is a schematic diagram of the intra-frame prediction mode. As shown in Figure 9, the intra-frame prediction modes used by HEVC include Planar, DC and 33 angle modes, a total of 35 prediction modes. Figure 10 is a schematic diagram of the intra-frame prediction mode. As shown in Figure 10, the intra-frame modes used by VVC include Planar, DC and 65 angle modes, a total of 67 prediction modes. Figure 11 is a schematic diagram of the intra-frame prediction mode. As shown in Figure 11, VS3 uses DC, Plane, Bilinear, PCM and 62 angle modes, a total of 66 prediction modes. There are also some technologies to improve the prediction, such as improving the pixel-by-pixel interpolation of reference pixels and filtering the predicted pixels. For example, the multiple intra prediction filter (MIPF) in AVS3 uses different filters to generate prediction values ​​for different block sizes. For pixels at different positions in the same block, one filter is used to generate prediction values ​​for pixels closer to the reference pixel, and another filter is used to generate prediction values ​​for pixels farther from the reference pixel. Technologies for filtering predicted pixels, such as the intra prediction filter (IPF) in AVS3, can use reference pixels to filter the predicted values. In intra-frame prediction, the intra-frame mode coding technology of the Most Probable Modes List (MPM) can be used to improve the coding efficiency. A mode list is formed by using the intra-frame prediction modes of the surrounding coded blocks, and the intra-frame prediction modes derived from the intra-frame prediction modes of the surrounding coded blocks, such as adjacent modes, and some commonly used or highly probable intra-frame prediction modes, such as DC, Planar, Bilinear modes, etc. The intra-frame prediction modes of the surrounding coded blocks are referenced to utilize spatial correlation. Because the texture has a certain degree of continuity in space. MPM can be used as a prediction of the intra-frame prediction mode. That is, it is considered that the probability of using MPM for the current block is higher than the probability of not using MPM. Therefore, when binarizing, fewer codewords will be used for MPM, thereby saving overhead to improve coding efficiency. In some embodiments, matrix-based intra prediction (MIP), sometimes also written as Matrix weighted intra prediction, can be used for intra prediction. As shown in FIG. 12 , in order to predict a block with a width of W and a height of H, MIP requires R reconstructed pixels in a column on the left side of the current block and W reconstructed pixels in a row on the upper side of the current block as input. MIP generates a prediction block in the following three steps: reference pixel averaging, matrix multiplication, and interpolation. Among them, matrix multiplication is the core of MIP. MIP can be considered as a process of generating a prediction block using input pixels (reference pixels) in a matrix multiplication manner. MIP provides a variety of matrices, and the difference in prediction methods is reflected in the difference in matrices. The same input pixels will get different results using different matrices. The process of reference pixel averaging and interpolation is a design that compromises performance and complexity. For blocks of larger size, an effect similar to downsampling can be achieved by averaging reference pixels, so that the input can be adapted to a relatively small matrix, while interpolation achieves an upsampling effect. In this way, there is no need to provide a MIP matrix for each block size, but only one or several matrices of specific sizes are provided. With the increasing demand for compression performance and the improvement of hardware capabilities, more complex MIPs may appear in the next generation of standards. MIP is somewhat similar to planar, but it is obviously more complex and more flexible than planar. GPM combines two inter prediction blocks using a weight matrix. In fact, it can be extended to combine two arbitrary prediction blocks, such as two inter prediction blocks, two intra prediction blocks, one inter prediction block and one intra prediction block. Even in screen content coding, you can use IBC (intra block copy) or palette prediction blocks as one or two prediction blocks. This application refers to intra-frame, inter-frame, IBC, and palette as different prediction methods. For the sake of convenience, a term called prediction mode is used here. The prediction mode can be understood as the information based on which the codec can generate a prediction block of the current block. For example, in intra-frame prediction, the prediction mode can be a certain intra-frame prediction mode, such as DC, Planar, various intra-frame angle prediction modes, etc. Of course, one or some auxiliary information can also be superimposed, such as the optimization method of intra-frame reference pixels, the optimization method after generating the preliminary prediction block (such as filtering), etc. For example, in inter-frame prediction, the prediction mode can be skip mode, merge mode or MMVD (merge with motion vector difference) mode, or AMVP (advanced motion vector predition), which can be unidirectional prediction, bidirectional prediction, or multi-hypothesis prediction. If the inter-frame prediction mode uses unidirectional prediction, a prediction mode must also be able to determine a motion information, and the prediction block can be determined based on the motion information. If the inter-frame prediction mode uses bidirectional prediction, a prediction mode must also be able to determine two pieces of motion information, and the prediction block can be determined based on the two pieces of motion information. The information that GPM needs to determine can be expressed as 1 weight derivation mode and 2 prediction modes. The weight derivation mode is used to determine the weight matrix or weight, and the 2 prediction modes respectively determine a prediction block or prediction value. The weight derivation mode is also called the partition mode in some places. But because it is a simulated partition, this application calls it the weight derivation mode. The two prediction modes may come from the same or different prediction methods, wherein the prediction methods include but are not limited to intra-frame prediction, inter-frame prediction, IBC, and palette. Optionally, the two prediction modes may come from the same or different prediction methods, where the prediction methods include but are not limited to intra-frame prediction, inter-frame prediction, IBC, and palette. A specific example is as follows: If the current block uses GPM. This example is used in inter-coded blocks, allowing the use of merge mode in intra-frame prediction and inter-frame prediction. As shown in Table 4, a syntax element intra_mode_idx is added to indicate which prediction mode is the intra-frame prediction mode. For example, intra_mode_idx is 0, indicating that both prediction modes are inter-frame prediction modes, that is, mode0IsInter is 1 and mode0IsInter is 1; intra_mode_idx is 1, indicating that the first prediction mode is the intra-frame prediction mode and the second prediction mode is the inter-frame prediction mode, that is, mode0IsInter is 0 and mode0IsInter is 1; intra_mode_idx is 2, indicating that the first prediction mode is the inter-frame prediction mode and the second prediction mode is the intra-frame prediction mode, that is, mode0IsInter is 1 and mode0IsInter is 0; intra_mode_idx is 3, indicating that both prediction modes are intra-frame prediction modes, that is, mode0IsInter is 0 and mode0IsInter is 0. Table 4 In some embodiments, as shown in FIG13 , the decoding process of GPM can be described as follows: parsing the bitstream to determine whether the current block uses the GPM technology; if the current block uses the GPM technology, determining the weight derivation mode (or the partitioning mode or the weight matrix derivation mode), and the first prediction mode and the second prediction mode. Determine the first prediction block according to the first prediction mode, determine the second prediction block according to the second prediction mode, determine the weight matrix according to the weight matrix derivation mode, and determine the prediction block of the current block according to the first prediction block, the second prediction block and the weight matrix. The template matching method was first used in inter-frame prediction. It uses the correlation between adjacent pixels and takes some areas around the current block as templates. When the current block is encoded and decoded, its left and upper sides have been encoded and decoded according to the encoding order. Of course, when the existing hardware decoder is implemented, it is not necessarily guaranteed that when the current block starts to be decoded, its left and upper sides have been decoded. Of course, this refers to inter-frame blocks. For example, in HEVC, when the inter-frame coded block generates a prediction block, the surrounding reconstructed pixels are not required, so the prediction process of the inter-frame block can be carried out in parallel. However, the intra-frame coded block must use the reconstructed pixels on the left and upper sides as reference pixels. Theoretically, the left and upper sides are available, which means that the hardware design can be adjusted accordingly. Relatively speaking, the right and lower sides are not available under the current standard such as VVC encoding order. As shown in FIG14 , the rectangular areas on the left and upper sides of the current block are set as templates. The height of the template on the left is generally the same as the height of the current block, and the width of the template on the upper side is generally the same as the width of the current block, but they can also be different. The best matching position of the template is found in the reference frame to determine the motion information or motion vector of the current block. This process can be roughly described as starting from a starting position in a certain reference frame and searching within a certain range around. The search rules can be pre-set, such as the search range and search step length. Each time a position is moved to, the matching degree between the template corresponding to the position and the template around the current block is calculated. The so-called matching degree can be measured by some distortion costs, such as SAD (sum of absolute difference), SATD (sum of absolute transformed difference). Generally, the transformation used by SATD is Hadamard transformation, MSE (mean-square error), etc. The smaller the value of SAD, SATD, MSE, etc., the higher the matching degree. The cost is calculated using the predicted block of the template corresponding to the position and the reconstructed block of the template around the current block. In addition to searching at the integer pixel position, the sub-pixel position can also be searched, and the motion information of the current block is determined based on the position with the highest degree of matching. By using the correlation between adjacent pixels, the motion information suitable for the template may also be the appropriate motion information for the current block. Of course, the template matching method may not necessarily be applicable to all blocks, so some methods can be used to determine whether the current block uses the above template matching method, such as using a control switch in the current block to indicate whether the template matching method is used. This template matching method is called DMVD (decoder side motion vector derivation). Both the encoder and the decoder can use the template to search to derive motion information or find better motion information based on the original motion information. It does not need to transmit specific motion vectors or motion vector differences, but the encoder and decoder both perform the same regular search to ensure the consistency of encoding and decoding. The template matching method can improve compression performance, but it also requires "searching" in the decoder, which brings a certain degree of decoder complexity. The above is a method for applying template matching between frames. The template matching method can also be used within a frame, for example, using a template to determine an intra-frame prediction mode. For the current block, the area within a certain range on the upper and left sides of the current block can also be used as a template, such as the rectangular area on the left and the rectangular area on the upper side as shown in the above figure. When encoding and decoding the current block, the reconstructed pixels in the template are available. This process can be roughly described as determining a set of candidate intra-frame prediction modes for the current block, and the candidate intra-frame prediction modes constitute a subset of all available intra-frame prediction modes. Of course, the candidate intra-frame prediction mode can be the full set of all available intra-frame prediction modes. This can be determined based on the trade-off between performance and complexity. The set of candidate intra-frame prediction modes can be determined based on MPM or some rules, such as equal-interval screening. Calculate the cost of each candidate intra-frame prediction mode on the template, such as SAD, SATD, MSE, etc. Use the mode to predict on the template to make a prediction block, and calculate the cost using the prediction block and the reconstructed block of the template. A mode with a low cost may be more compatible with the template. By using the similarity between adjacent pixels, an intra-frame prediction mode that performs well on the template may also be an intra-frame prediction mode that performs well on the current block. Select one or several modes with a low cost. Of course, the above two steps can be repeated. For example, after selecting one or several modes with a low cost, the set of candidate intra-frame prediction modes is determined again, and the cost of the newly determined candidate intra-frame prediction mode set is calculated again, and one or several modes with a low cost are selected. This can also be understood as rough selection and fine selection. The final selected intra-frame prediction mode is determined as the intra-frame prediction mode of the current block, or the final selected intra-frame prediction modes are used as candidates for the intra-frame prediction mode of the current block. Of course, the candidate intra-frame prediction mode set can also be sorted by the template matching method alone, such as sorting the MPM list, that is, the modes in the MPM list are predicted on the template and the cost is determined, and sorted from small to large cost. Generally, the mode at the front of the MPM list has a smaller overhead in the bitstream, which can also achieve the purpose of improving compression efficiency. The template matching method can be used to determine the two prediction modes of GPM. If the template matching method is used for GPM, one control switch can be used to control whether the two prediction modes of the current block use template matching, or two control switches can be used to control whether the two prediction modes use template matching respectively. Another aspect is how to use template matching. For example, if GPM is used in merge mode, such as GPM in VVC, it uses merge_gpm_idxX to determine a motion information from mergeCandList, where uppercase X is 0 or 1. For the Xth motion information, one method is to optimize it based on the above motion information using the template matching method. That is, according to merge_gpm_idxX, a motion information is determined from mergeCandList. If template matching is used for the motion information, then the template matching method is used to optimize it based on the above motion information. Another method is not to use merge_gpm_idxX to determine a motion information from mergeCandList, but to directly search based on a default motion information to determine a motion information. If the Xth prediction mode is an intra prediction mode, and the Xth prediction mode of the current block uses the template matching method, then the template matching method can be used to determine an intra prediction mode, and there is no need to indicate the index of the intra prediction mode in the bitstream. Alternatively, the template matching method is used to determine a candidate set or MPM list, and the index of the intra prediction mode needs to be indicated in the bitstream. As can be seen from the above, GPM has three elements, a weight matrix and two prediction modes. The advantage of GPM is that it can achieve more autonomous combinations through the weight matrix. On the other hand, GPM needs to determine more information, so it needs to pay a greater overhead in the bitstream. Take GPM in VVC as an example. GPM in VVC is used in merge mode. In the bitstream, merge_gpm_partition_idx, merge_gpm_idx0, merge_gpm_idx1 are used to determine the weight matrix, the first prediction mode and the second prediction mode. The weight matrix and the two prediction modes each have multiple possible choices. For example, the weight matrix in VVC has 64 possible choices. And merge_gpm_idx0 and merge_gpm_idx1 each allow a maximum of 6 possible choices in VVC. Of course, VVC stipulates that merge_gpm_idx0 and merge_gpm_idx1 are not repeated. Then such a GPM has 65X6X5 possible choices. If MMVD is used to optimize two motion information (prediction modes), multiple possible choices can be provided for each prediction mode, which is a very large number. If GPM uses two intra prediction modes, each of which can use 67 common intra prediction modes in VVC, and the two intra prediction modes are different, there are also 64X67X66 possible choices. Of course, in order to save costs, each prediction mode can be limited to only a subset of all common intra prediction modes, but this still has many possible choices. At present, GPM's 1 weight derivation mode and 2 prediction modes need to transmit necessary information in the bitstream according to their respective rules. For example, 1 weight derivation mode has its own one or more syntax elements, the first prediction mode has its own one or more syntax elements, and the second prediction mode has its own one or more syntax elements. Of course, the standard can restrict that the second prediction mode cannot be the same as the first prediction mode in some cases, or some optimization methods can be used in two prediction modes at the same time (this can also be understood as being used in the current block), but the three are relatively independent in the writing and parsing of syntax elements, that is, more codewords are required to indicate the weight derivation mode and prediction mode, and the encoding overhead is large. In addition, since different components of the same space have a strong correlation, video coding technology can use this correlation to improve compression efficiency. In some cases, the first component of the same space will be encoded and decoded first, and then the second and third components will be encoded and decoded, so that the second and third components can use some information of the first component. A typical example is cross-component linear model prediction (CCLM). In the same CU, the pixels of the chrominance component can be predicted using the reconstructed pixels of the luminance component. Specifically, as shown in the following equation: pred C (i,j)=α·rec L ′(i,j)+β Among them, pred C (i, j) represents the predicted value of the chrominance pixel at position (i, j), rec L ′(i,j) represents the reconstructed value of the downsampled chroma pixel at position (i,j). The parameters (α and β) of CCLM are derived based on the neighboring downsampled luma and chroma pixels of the current CU. In one example, as shown in FIG15 , the basic principle is to derive a linear model using adjacent luminance and chrominance pixels of the current CU, and then apply the linear model to the current CU to determine the predicted value of chrominance based on the reconstructed value of luminance and the linear model. However, in some cases, since one chroma CU may correspond to multiple luma CUs and the prediction modes of different luma CUs may be different, CCLM cannot accurately predict chroma blocks with complex textures. In order to solve the above technical problems, the embodiment of the present application regards the first weight derivation mode and K first prediction modes corresponding to the current component block as a combination, and indicates the first weight derivation mode and K first prediction modes in the form of a combination, so that there is no need to separately transmit the syntax corresponding to the K first prediction modes and the first weight derivation mode in the code stream, thereby saving code words and improving coding efficiency. In addition, in the embodiment of the present application, when the current component block corresponds to multiple first component CUs and the prediction modes of the multiple first component CUs are not exactly the same, the first weight derivation mode and K first prediction modes included in the first combination can also be accurately determined, and then the first weight derivation mode and K first prediction modes are used to achieve accurate prediction of the current component block. In conjunction with Figure 16, the video decoding method provided in the embodiment of the present application is introduced by taking the decoding end as an example. FIG16 is a schematic diagram of a video decoding method flow chart provided by an embodiment of the present application, and the embodiment of the present application is applied to the video decoders shown in FIG1 and FIG3. As shown in FIG16, the method of the embodiment of the present application includes: S101. Decode a bit stream and determine a first combination. The first combination includes a first weight derivation mode and K first prediction modes, where K is a positive integer greater than 1. Image formats include YUV, YCrCb, RGB, etc. In the YUV format, Y represents the brightness component, UV represents the chrominance component, wherein Y is also called the first component, U is called the second component, and V is called the third component. In the YCrCb format, Y represents the brightness component, CrCb represents the chrominance component, wherein Y is also called the first component, Cr is called the second component, and Cb is called the third component. In some embodiments, in the RGB format, G is called the first component, B is called the second component, and R is called the third component. In some embodiments, during encoding and decoding, the first component of the CTU may be divided into at least one first component block, the second component may be divided into at least one second component block, and the third component may be divided into at least one third component block. In the embodiment of the present application, K different prediction modes are used to predict the current component block, where the current component block includes the second component block or the third component block. From the above, it can be seen that a weight derivation mode and K prediction modes jointly generate a prediction block, and this prediction block acts on the current component block, that is, the weight is determined according to the first weight derivation mode, and the current component block is predicted according to the K first prediction modes to obtain K prediction values, and the K prediction values ​​are weighted according to the weight to obtain the prediction value of the current component block. It can be seen that the first weight derivation mode and the K first prediction modes included in the first combination act together on the current component block, and they are related. In the present application, the first weight derivation mode is used to determine the weight used for the current component block. Specifically, the first weight derivation mode can be a mode for deriving weights. For a block of a given length and width, each weight derivation mode can derive a weight matrix; for blocks of the same size, different weight derivation modes derive different weight matrices. Exemplarily, in the present application, AWP has 56 weight derivation modes and GPM has 64 weight derivation modes. The K different first prediction modes included in the first combination include the following examples: Example 1: the above K different first prediction modes are all intra-frame prediction modes, for example, the current component block is an intra-frame coded block and is not applicable to screen content coding. Example 2: The K different first prediction modes are all inter-frame prediction modes, for example, the current component block is an inter-frame coded block. Example 3: Among the above K different first prediction modes, at least one is an intra-frame prediction mode, and at least one is an inter-frame prediction mode. Example 4: Among the above K different first prediction modes, at least one is an intra-frame prediction mode, and at least one is a non-inter-frame and non-intra-frame prediction mode, such as an intra-block copy IBC prediction mode or a palette prediction mode. Example 5: Among the above K different first prediction modes, at least one is an inter-frame prediction mode, and at least one is a non-inter-frame and non-intra-frame prediction mode, such as an IBC prediction mode or a palette prediction mode. Example 6: The K different first prediction modes are neither intra-frame prediction mode nor inter-frame prediction mode. For example, one is an IBC prediction mode, and the other is a palette prediction mode. It should be noted that the embodiment of the present application does not limit the specific types of the K different first prediction modes included in the first combination. In some embodiments, before determining the first combination, it is first necessary to determine whether the current component block uses K different prediction modes for weighted prediction processing. If the decoding end determines that the current component block uses K different prediction modes for weighted prediction processing, the above S101 decoding bitstream is executed to determine the first combination. If the decoding end determines that the current component block does not use K different prediction modes for weighted prediction processing, the above S101 step is skipped. In a possible implementation manner, the decoding end may determine whether the current component block uses K different prediction modes for weighted prediction processing by determining the prediction mode parameters of the current component block. Optionally, in the implementation of the present application, the prediction mode parameter may indicate whether the current component block can use the GPM mode or the AWP mode, that is, whether the current component block can use K different prediction modes for prediction processing. It is understandable that, in the embodiment of the present application, the prediction mode parameter can be understood as a flag indicating whether the GPM mode or the AWP mode is used. Specifically, the encoder can use a variable as the prediction mode parameter, so that the setting of the prediction mode parameter can be realized by setting the value of the variable. Exemplarily, in the present application, if the current component block uses the GPM mode or the AWP mode, then the encoder can set the value of the prediction mode parameter to indicate that the current component block uses the GPM mode or the AWP mode, and specifically, the encoder can set the value of the variable to 1. Exemplarily, in the present application, if the current component block does not use the GPM mode or the AWP mode, then the encoder can set the value of the prediction mode parameter to indicate that the current component block does not use the GPM mode or the AWP mode, and specifically, the encoder can set the variable value to 0. Further, in the embodiment of the present application, after completing the setting of the prediction mode parameter, the encoder can write the prediction mode parameter into the bitstream and transmit it to the decoder, so that the decoder can obtain the prediction mode parameter after parsing the bitstream. Based on this, the decoding end decodes the bit stream to obtain the prediction mode parameters, and then determines whether the current component block uses the GPM mode or the AWP mode according to the prediction mode parameters. If the current component block uses the GPM mode or the AWP mode, that is, when K different prediction modes are used for prediction processing, the weight derivation mode of the current component block is determined. In some embodiments, as shown in Table 5, the embodiments of the present application can also conditionally limit the use of the GPM mode or the AWP mode for the current component block, that is, when it is determined that the current component block meets the preset conditions, it is determined that the current component block uses K prediction modes for weighted prediction, and then the decoding end decodes the code stream to determine the first combination. Exemplarily, when the GPM mode or the AWP mode is applied, the size of the current component block may be limited. It is understandable that, since the prediction method proposed in the embodiment of the present application needs to use K different prediction modes to generate K prediction values, and then weight them according to the weights to obtain the prediction value of the current component block, in order to reduce the complexity and consider the trade-off between compression performance and complexity, in the embodiment of the present application, it is possible to limit the use of the GPM mode or AWP mode for blocks of certain sizes. Therefore, in the present application, the decoder can first determine the size parameter of the current component block, and then determine whether the current component block uses the GPM mode or the AWP mode according to the size parameter. In an embodiment of the present application, the size parameter of the current component block may include the height and width of the current component block. Therefore, the decoder may determine whether the current component block uses the GPM mode or the AWP mode according to the height and width of the current component block. Exemplarily, in the present application, if the width is greater than the first threshold and the height is greater than the second threshold, it is determined that the current component block can use the GPM mode or the AWP mode. It can be seen that a possible limitation is to use the GPM mode or the AWP mode only when the width of the block is greater than (or greater than or equal to) the first threshold and the height of the block is greater than (or greater than or equal to) the second threshold. The values ​​of the first threshold and the second threshold can be 4, 8, 16, 32, 128, 256, etc., and the first threshold can be equal to the second threshold. Exemplarily, in the present application, if the width is less than the third threshold and the height is greater than the fourth threshold, it is determined that the current component block can use the GPM mode or the AWP mode. It can be seen that a possible limitation is to use the GPM mode or the AWP mode only when the width of the block is less than (or less than or equal to) the third threshold and the height of the block is greater than (or greater than or equal to) the fourth threshold. The values ​​of the third threshold and the fourth threshold can be 4, 8, 16, 32, 128, 256, etc., and the third threshold can be equal to the fourth threshold. Furthermore, in the embodiments of the present application, the size of the block that can use the GPM mode or the AWP mode can be limited by limiting the pixel parameters. Exemplarily, in the present application, the decoder may first determine the pixel parameters of the current component block, and then further determine whether the current component block can use the GPM mode or the AWP mode based on the pixel parameters and the fifth threshold. It can be seen that a possible limitation is to use the GPM mode or the AWP mode only when the number of pixels of the block is greater than (or greater than or equal to) the fifth threshold. The value of the fifth threshold may be 4, 8, 16, 32, 128, 256, 1024, etc. That is to say, in the present application, only when the size parameter of the current component block meets the size requirement, the current component block can use the GPM mode or the AWP mode. Exemplarily, in the present application, there may be a frame-level flag to determine whether the current frame to be decoded uses the present application. For example, intra-frames (such as I-frames) may be configured to use the present application, while inter-frames (such as B-frames and P-frames) may not use the present application. Alternatively, intra-frames may be configured not to use the present application, while inter-frames may use the present application. Alternatively, some inter-frames may be configured to use the present application, while some inter-frames may not use the present application. Inter-frames may also use intra-frame prediction, and thus inter-frames may also use the present application. In some embodiments, there may also be a flag below the frame level and above the CU level (such as tile, slice, patch, LCU, etc.) to determine whether this area uses the present application. The embodiment of the present application does not limit the specific method of decoding the code stream in the above S101 to determine the first combination. In some embodiments, the first combination is a preset combination, that is, when the decoding end decodes the code stream and determines that the current component block can be predicted using the first combination, the preset combination is determined as the first combination, and the first weight derivation mode and K first prediction modes included in the first combination are used to predict the current component block. In some embodiments, a first combination is determined from a plurality of preset combinations. For example, the plurality of preset combinations include any number of combinations such as 2, 3, 4, 5, 6, 7, 8, 9, etc. Assume that 8 combinations are included, each combination includes a weight derivation mode and K prediction modes, and the 8 combinations have different identifiers (or indexes). In this way, the decoding end can obtain a first index by decoding the bit stream, and the first index is used to indicate the first combination. Then, the combination corresponding to the first index is queried in the plurality of preset combinations, and the combination corresponding to the first index is determined as the first combination. In some embodiments, the decoding end and the encoding end both determine a list, which includes multiple candidate combinations, so the list is also called a candidate combination list, and the first combination corresponding to the first index is determined from the candidate combination list. In this case, the above S101 includes the following steps: S101-A, decoding a bitstream, determining a candidate combination list, the candidate combination list including at least one candidate combination, any candidate combination in the at least one candidate combination including a weight derivation mode and K prediction modes; S101-B. Determine a first combination according to the candidate combination list. The above candidate combination list includes at least one candidate combination, and any candidate combination in the at least one candidate combination includes a weight derivation mode and K prediction modes. Exemplarily, the candidate combination list is shown in Table 5: Table 5 Index candidate combination 0 candidate combination 1 (including one weight derivation mode and K prediction modes) 1 candidate combination 2 (including one weight derivation mode and K prediction modes) ………… i-1 candidate combination i (including one weight derivation mode and K prediction modes) ………… As shown in Table 5, the candidate combination list includes at least one candidate combination, and any two candidate combinations in the at least one candidate combination are not completely the same, that is, the weight derivation mode included in any two candidate combinations is different from at least one mode in the K prediction modes. For example, the weight derivation mode in candidate combination 1 is different from that in candidate combination 2, or the weight derivation mode in candidate combination 1 is the same as that in candidate combination 2, and at least one prediction mode in the K prediction modes is different, or the weight derivation mode in candidate combination 1 is different from that in candidate combination 2, and at least one prediction mode in the K prediction modes is different. Illustratively, in the above Table 5, the ranking of the candidate combinations in the candidate combination list is used as the index. Optionally, the index of the candidate combination in the candidate combination list may also be reflected in other ways, which is not limited in the embodiments of the present application. In this embodiment, the decoding end determines the first combination according to the candidate combination list in the following ways, including but not limited to: In mode 1, the candidate combination list includes one candidate combination. In this case, the candidate combination included in the candidate combination list is determined as the first combination. Mode 2: The candidate combination list includes multiple candidate combinations. At this time, the code stream is decoded to obtain a first index, and the first index is used to indicate the first combination; the candidate combination corresponding to the first index in the candidate combination list is determined as the first combination. In the method 2, the decoding end decodes the code stream to obtain the first index, and determines a candidate combination list as shown in the above Table 5, and searches the candidate combination list according to the first index to obtain the first combination indicated by the first index. For example, the first index is index 1, and in the candidate combination list shown in Table 5, the candidate combination corresponding to index 1 is candidate combination 2, that is, the first combination indicated by the first index is candidate combination 2. In this way, the decoding end determines the weight derivation mode and K prediction modes included in candidate combination 1 as the first weight derivation mode and K first prediction modes included in the first combination, and uses the first weight derivation mode and K first prediction modes to predict the current component block to obtain a prediction value of the current component block. In the embodiment of the present application, the encoding end and the decoding end can respectively determine the same candidate combination list, for example, the encoding end and the decoding end both determine a list including N candidate combinations, each candidate combination including 1 weight derivation mode and K prediction modes. If N is greater than 1, then in the bitstream, the encoding end only needs to write a candidate combination finally selected, for example, the first combination, and the decoding end parses the first combination finally selected by the encoding end, specifically, the decoding end decodes the bitstream, obtains the first index, and determines the first combination in the candidate combination list determined by the decoding end through the first index. The embodiment of the present application does not limit the specific syntax element form of the first index. In a possible implementation, if the current component block is predicted using the GPM technology, gpm_cand_idx is used to represent the first index. Since the above-mentioned first index is used to indicate the first combination, in some embodiments, the first index may also be referred to as a first combination index or an index of the first combination. In an example, the syntax after adding the first index in the code stream is as shown in Table 6: Table 6 Among them, gpm_cand_idx is the first index. In order to save codewords and reduce coding costs, the embodiment of the present application regards the first weight derivation mode and K first prediction modes corresponding to the current component block as a combination, i.e., a first combination, and uses a first index to indicate the first combination. Compared with indicating the first weight derivation mode and the K first prediction modes separately, the embodiment of the present application uses fewer codewords, thereby reducing the coding cost. The specific process of determining the candidate combination list in the above S101-A is introduced below. In some embodiments, the candidate combination list is preset. In some embodiments, the candidate combination list is sent from the encoding end to the decoding end, for example, the encoding end sends it to the decoding end before encoding the current component block. In some embodiments, the candidate combination list is uploaded to the cloud by the encoding end, and the decoding end can read the candidate combination list from the cloud. In some embodiments, the candidate combination list is constructed by the decoding end. The embodiment of the present application does not limit the way in which the decoding end constructs the candidate combination list. For example, the information related to the current component block is used to analyze the probability of occurrence of each combination composed of different weight derivation modes and different prediction modes, and the candidate combination list is constructed according to the probability of occurrence of each combination. Optionally, the information related to the current component block includes pattern information of surrounding blocks of the current component block, reconstructed pixels of a first component block corresponding to the current component block, and the like. In some embodiments, the decoding end constructs a candidate combination list through the following steps S101-A1: S101-A1, decoding a bit stream, and determining a first component block corresponding to a current component block; S101-A2: Construct a candidate combination list based on the first component block. Currently in video encoding and decoding, an image is divided into blocks for processing. For example, in VVC, the image is divided into CTUs. The size of CTU allowed by VVC is 128x128. CTU can be further divided into more flexible CUs (coding units). VVC supports binary tree, ternary tree, and quadtree division methods. For example, Figures 17A to 17D are schematic diagrams of vertical binary tree, horizontal binary tree, vertical ternary tree, and horizontal ternary tree division, respectively. FIG17E is a schematic diagram of a CTU partition, where the block with a thick border is divided by a quadtree, and the block with a thin border is divided by a binary tree or a ternary tree. It can be seen that some blocks after the division can be further divided, of course, some restrictions will be imposed for the consideration of performance and complexity, and the embodiment of the present application does not impose any restrictions on this. The most commonly supported format in video codecs is YUV4:2:0. Y represents the brightness component, and UV represents the chrominance component. The YUV4:2:0 format takes advantage of the fact that the human eye is sensitive to brightness but not to chrominance, and reduces the sampling rate of chrominance relative to brightness, that is, in both the horizontal and vertical directions, every 2 pixels of the brightness component correspond to 1 pixel of the chrominance component U or V, which can help improve compression efficiency. Since the human eye is sensitive to brightness but not to chrominance, the brightness component is more important, so the general video codec standard will encode the brightness component first, and then the chrominance component. As for block partitioning, in some embodiments, the luminance component and the chrominance component adopt the same block partitioning manner. However, because the sampling rate of chroma is low and the quality requirement for chroma is usually not as high as that for luminance, in some embodiments, the block division of chroma components may be different from that of luminance components. For example, as shown in FIG. 17F , the block division of luminance components on the left is finer, while the block division of chroma components on the right is coarser. It should be noted that the video codec not only supports YUV4:2:0 format, but also supports other formats such as YUV4:4:4, YUV4:2:1, RGB, etc. As shown in FIG17F , assuming that the current component block is the gray component block on the right, the first component block in the same space as the gray component block is the gray area on the left in FIG17F , and the gray area on the left includes 10 first component CUs. As can be seen from the above FIG. 17F, the first component block in the same space as the current component block refers to the first component block located at the same spatial position and having the same spatial size as the current component block. Taking the current component block as a chroma block and the first component block as a luminance block as an example, due to different video formats, the sizes of the chroma block and the luminance block may be different. For example, for a video in YUV4:4:4 format, the size of the chroma block is the same as the size of the luminance block. For a video in YUV4:2:0 format, the size of the luminance block is 4 times the size of the chroma block. Since the size of the chroma block may be different from that of the luminance block, the chroma block and the luminance block of the same spatial position and the same spatial size may not have the same coordinates. For example, in the video format YUV4:2:0, the chroma block is a block determined by the upper left corner coordinates (x0, y0), width width, and height height. Then the luminance block in the same space can be a block determined by the upper left corner coordinates (x0*2, y0*2), width width*2, and height height*2. For another example, in the video format YUV4:4:4, the chroma block is a block determined by the upper left corner coordinates (x0, y0), width width, and height height. Then the luminance block in the same space can be a block determined by the upper left corner coordinates (x0, y0), width width, and height height. In addition, in some embodiments, since the chrominance block and the luminance block are divided into independent blocks, the luminance block corresponding to the chrominance decoding block may not overlap with the decoding block obtained by dividing the luminance component, but is in the same luminance area as the chrominance decoding block in spatial position and spatial size. That is to say, in the embodiment of the present application, the first component block corresponding to the current component block can be understood as the first component block having the same spatial coverage as the current component block. During decoding, the luminance component is usually decoded first, and then the chrominance component is decoded. Therefore, in the embodiment of the present application, when decoding the current component block, the code stream is first decoded, and the first component block corresponding to the current component block is decoded to obtain the reconstruction value of the first component block. Then, the first component block is used as a template for the current component block to decode the current component block. Since the first component block corresponding to the current component block is correlated with the current component block, based on this, the embodiment of the present application constructs a candidate combination list of the current component block based on the first component block. For example, for each combination, the first component block is predicted using the combination to obtain the predicted value of the first component block under each combination, and a candidate combination list is constructed based on the predicted value of the first component block under each combination. For example, the weight of the first component block is derived using the weight derivation mode included in the combination, and the first component block is predicted using the K prediction modes included in the combination to obtain K predicted values ​​of the first component block, and the K predicted values ​​of the first component block are weighted according to the derived weight of the first component block to obtain the predicted value of the first component block under the combination. Finally, a candidate combination list is constructed based on the predicted value of the first component block under each combination. It should be noted that the weights derived according to the weight derivation mode can be understood as the weights corresponding to each pixel in the first component block, or as the weight matrix corresponding to the first component block. When determining the predicted value of the first component block based on the weight, it can be determined that the K predicted values ​​corresponding to each pixel in the first component block are determined, and the predicted value corresponding to each pixel is determined based on the K predicted values ​​and weights corresponding to each pixel, and the predicted value corresponding to each pixel in the first component block constitutes the predicted value of the first component block. Optionally, when determining the predicted value of the first component block based on the weight, it can also be performed on a block basis, for example, the predicted value of the first component block is determined, and the K predicted values ​​of the first component block are weighted according to the weight matrix of the first component block to obtain the predicted value of the first component block. In some embodiments, S101-A2 includes the following steps S101-A21 to S101-A23: S101-A21, determining R second combinations, any second combination of the R second combinations includes a weight derivation mode and K prediction modes, and R is a positive integer greater than 1; S101-A22, for any second combination among the R second combinations, determine a cost corresponding to the second combination when the second combination is used to predict the first component block; S101-A23. Construct a candidate combination list according to the cost corresponding to each second combination in the R second combinations. In this embodiment, when constructing a candidate combination list, the decoding end first determines R second combinations. The present application does not limit the specific values ​​of the R second combinations, such as 8, 16, 32, etc. Each of the R second combinations includes a weight derivation mode and K prediction modes. Then, for each of the R second combinations, the cost corresponding to the second combination when the first component block is predicted using the second combination is determined. Finally, a candidate combination list is constructed according to the cost corresponding to each of the R second combinations. Since the first component block corresponding to the current component block is a reconstructed area, the decoding end can obtain the reconstruction value of the first component block, so for each second combination in the R second combinations, the prediction distortion cost corresponding to the second combination can be determined according to the prediction value of the first component block under the second combination and the reconstruction value of the first component block. The method of determining the cost corresponding to the second combination includes but is not limited to SAD, SATD, SEE, etc. Then, according to the cost corresponding to each second combination in the R second combinations, a candidate combination list is constructed. In the embodiment of the present application, when it is determined in S101-A22 to use the second combination to predict the first component block, the cost corresponding to the second combination includes at least two methods: The first method is to determine the weight of the first component block according to the weight derivation mode included in the second combination; predict the first component block according to the K prediction modes in the second combination to obtain K prediction values ​​of the first component block; weight the K prediction values ​​of the first component block according to the weight of the first component block to obtain the prediction value of the first component block corresponding to the second combination; determine the cost corresponding to the second combination according to the prediction value of the first component block corresponding to the second combination and the reconstructed value of the first component block. The second method is to determine the prediction values ​​of the first component blocks respectively corresponding to the K prediction modes in the second combination according to the weight derivation mode in the second combination; determine the costs respectively corresponding to the K prediction modes in the second combination according to the prediction values ​​of the first component blocks respectively corresponding to the K prediction modes in the second combination and the reconstructed values ​​of the first component blocks; determine the cost corresponding to the second combination according to the costs respectively corresponding to the K prediction modes in the second combination. In the second method, taking K=2 as an example, the weight on the first component block can be simplified to only two possibilities, 0 and 1. Then, for each pixel position, its pixel value only comes from the prediction block of the first prediction mode or the prediction block of the second prediction mode. Therefore, for a prediction mode, its cost on the first component block when it is the first prediction mode of a certain weight derivation mode can be calculated, that is, only the cost of some pixels with a weight of 1 when the prediction mode is the first prediction mode under the weight derivation mode on the first component block is calculated. An example is to record the cost as cost[pred_mode_idx][gpm_idx][0], where pred_mode_idx represents the index of the prediction mode, gpm_idx represents the index of the weight derivation mode, and 0 represents the first prediction mode. And the cost of the prediction mode on the first component block when it is used as the second prediction mode of a certain weight derivation mode, that is, only the cost of the prediction mode on the first component block with a weight of 1 when the prediction mode is used as the second prediction mode under the weight derivation mode is calculated. An example is to record the cost as cost[pred_mode_idx][gpm_idx][1], where pred_mode_idx represents the index of the prediction mode, gpm_idx represents the index of the weight derivation mode, and 1 represents the second prediction mode. Then when calculating the cost of a combination, the corresponding two costs can be directly added. For example, the cost of the prediction modes pred_mode_idx0 and pred_mode_idx1 in the weighted derivation mode gpm_idx is required, where pred_mode_idx0 is used as the first prediction mode and pred_mode_idx1 is used as the second prediction mode. The cost is recorded as costTemp, then costTemp = cost[pred_mode_idx0][gpm_idx][0] + cost[pred_mode_idx1][gpm_idx][1]. If the cost of the prediction modes pred_mode_idx0 and pred_mode_idx1 in the weighted derivation mode gpm_idx is required, where pred_mode_idx1 is used as the first prediction mode and pred_mode_idx0 is used as the second prediction mode. The cost is recorded as costTemp, then costTemp=cost[pred_mode_idx1][gpm_idx][0]+cost[pred_mode_idx0][gpm_idx][1]. One benefit of this is that the weighted combination into a prediction block before calculating the cost is simplified to directly calculating the cost of the two parts, and then adding the costs to get the combined cost. Since a prediction mode may be combined with multiple other prediction modes, and for the same weight derivation mode, the cost of the prediction mode as part of the first prediction mode and the second prediction mode is fixed, these costs can be retained, that is, cost[pred_mode_idx][gpm_idx][0] and cost[pred_mode_idx][gpm_idx][1] in the above example, and reused, thereby reducing the amount of calculation. According to the above method, the cost corresponding to each second combination in the R second combinations can be determined, and then S101 - A23 is executed. Among them, in S101-A23, the method of constructing the candidate combination list according to the cost corresponding to each second combination in the R second combinations includes but is not limited to the following examples: Example 1: sort the R second combinations according to the cost corresponding to each second combination in the R second combinations; and determine the sorted R second combinations as a candidate combination list. The candidate combination list generated in this Example 1 includes R candidate combinations. Optionally, the R candidate combinations in the candidate combination list are sorted in ascending order according to the size of the costs, that is, the costs corresponding to the R candidate combinations in the candidate combination list increase in sequence according to the sorting. Among them, sorting the R second combinations according to the cost corresponding to each second combination in the R second combinations may be sorting the R second combinations in ascending order of cost. Example 2: According to the costs corresponding to the second combinations, N second combinations are selected from the R second combinations, and the list consisting of the N second combinations is determined as a candidate combination list. Optionally, the above-mentioned N second combinations are the first N second combinations with the smallest costs among the R second combinations. For example, according to the cost corresponding to each second combination in the R second combinations, N second combinations with the smallest costs are selected from the R second combinations to form a candidate combination list. In this case, the candidate combination list includes N candidate combinations. Optionally, the N candidate combinations in the candidate combination list are sorted from small to large according to the size of the cost, that is, the costs corresponding to the N candidate combinations in the candidate combination list increase in sequence according to the sorting. The process of determining the R second combinations in the above S101-A21 is introduced below. In some embodiments, the R second combinations are preset. In this way, each second combination in the preset R second combinations is used to predict the first component block, and the predicted value of the first component block corresponding to each second combination is obtained, and then the cost corresponding to each second combination is determined according to the predicted value of the first component block corresponding to each second combination and the reconstructed value of the first component block, and the R second combinations are sorted according to the cost corresponding to each second combination, and the sorted R second combinations are used as a candidate combination list, or N second combinations with the smallest cost are selected from the sorted R second combinations to form a candidate combination list. In some embodiments, S101-A21 includes the following steps: S101-A21-1. Determine P weight derivation modes and Q prediction modes, where P is a positive integer and Q is a positive integer greater than or equal to K; S101-A21-2. Construct R second combinations based on P weight derivation modes and Q prediction modes, wherein any second combination of the R second combinations includes a weight derivation mode among the P weight derivation modes and K prediction modes among the Q prediction modes, where P is a positive integer, and Q is a positive integer greater than or equal to K. In this embodiment, the decoding end first determines P weight derivation modes and Q prediction modes, and then constructs R second combinations based on the determined P weight derivation modes and Q prediction modes. For example, the second combination includes a weight derivation mode and 2 prediction modes. Assume that the P weight derivation modes are weight derivation mode 1 and weight derivation mode 2, and the Q prediction modes are prediction mode 1, prediction mode 2 and prediction mode 3. These 2 weight derivation modes and 3 prediction modes can be combined into 2X3X2, a total of 12 second combinations. The embodiment of the present application does not limit the specific number of the above-mentioned P weight derivation modes and Q prediction modes. In a possible implementation, assuming that the current component block is an intra-frame coding block, it is assumed that there are 64 possible weight derivation modes for GPM and 67 possible intra-frame prediction modes for GPM, which can be found in the VVC standard. However, it is not limited to only 64 possible weights for GPM, or which 64. It should be noted that the reason why VVC's GPM chooses 64 is also a trade-off between improved prediction effect and increased overhead in the code stream. However, the present application no longer uses a fixed logic to encode the weight derivation mode, so in theory, the present application can use more diverse weights and use them more flexibly. Similarly, it is not limited to only 67 intra-frame prediction modes for GPM, or which 67. In theory, all possible intra-frame prediction modes can be used in GPM. For example, the intra-frame angle prediction mode is made more detailed and generates more intra-frame angle prediction modes, so GPM can also use more intra-frame angle prediction modes. For example, the MIP (matrix-based intra prediction) mode of VVC can also be used in this application, but considering that MIP has multiple sub-modes to choose from, MIP is not added to this embodiment for ease of understanding. There are also some wide-angle modes that can also be used in this application, which will not be described in this embodiment. Assuming K=2, the above K prediction modes include the first prediction mode and the second prediction mode. Assuming that there are 67 available prediction modes (i.e., Q=67), the first prediction mode has 67 possibilities. Since the second prediction mode is different from the first prediction mode, there are 66 second prediction modes. Assuming that there are 64 weight-derived modes (i.e., P=64), the present application may use any two different prediction modes and any weight-derived mode to form a second combination, with a total of 64*67*66 possible second combinations. In this implementation, the P weight derivation modes are all possible weight derivation modes, such as the 64 weight derivation modes in GPM, and the Q prediction modes are all possible prediction modes, such as the 67 intra-frame prediction modes of GPM. An exhaustive method is used to obtain all possible second combinations, for example, 64*67*66 possible second combinations are obtained. Each second combination of the 64*67*66 possible second combinations is used to predict the first component block, and the distortion cost of each second combination is calculated. Then, according to the distortion cost of each second combination, a list of candidate combinations corresponding to the current component block is obtained. In some embodiments, in order to reduce the amount of data and increase the speed of building the candidate combination list, not every prediction mode is tried, but some of the prediction modes may be selected for trying. At this time, the implementation methods of determining the Q prediction modes in the above S101-A21-1 include but are not limited to the following methods: Method 1: Q prediction modes are preset prediction modes. Method 2: Determine a candidate prediction mode list for the current component block, a candidate prediction mode list corresponding to the K first prediction modes, a prediction mode corresponding to the weighted derivative mode, and at least one of the preset modes; and determine Q prediction modes based on the candidate prediction mode list, the alternative prediction mode list corresponding to the K first prediction modes, the prediction mode corresponding to the weighted derivative mode, and at least one of the preset modes. The candidate prediction mode list includes multiple candidate prediction modes, and the candidate prediction mode list corresponding to any prediction mode among the K prediction modes includes at least one candidate prediction mode. For example, Q prediction modes are determined according to the candidate prediction mode list of the current component block. For another example, Q prediction modes are determined according to the candidate prediction mode lists corresponding to the K first prediction modes respectively. For another example, Q prediction modes are determined based on the prediction modes corresponding to the weighted derivation modes. For another example, according to a preset mode, Q prediction modes are determined. For another example, Q prediction modes are determined according to the candidate prediction mode list of the current component block and the candidate prediction mode lists corresponding to the K first prediction modes respectively. For another example, Q prediction modes are determined according to the candidate prediction mode list of the current component block and the prediction mode corresponding to the weight derivation mode. For another example, Q prediction modes are determined according to the candidate prediction mode lists corresponding to the K first prediction modes respectively and the prediction mode corresponding to the weight derivation mode. For another example, Q prediction modes are determined according to the candidate prediction mode list, the alternative prediction mode lists corresponding to the K first prediction modes, and the prediction mode corresponding to the weighted derivation mode. For another example, Q prediction modes are determined according to the candidate prediction mode list, the alternative prediction mode lists corresponding to the K first prediction modes, the prediction mode corresponding to the weighted derivation mode, and the preset mode. Among them, determining the alternative prediction mode lists corresponding to the K first prediction modes can be understood as determining an alternative prediction mode list for each of the K first prediction modes, and when the second combination is subsequently constructed, a certain prediction mode in the second combination is selected from the alternative prediction mode list corresponding to the prediction mode. For example, K=2, the K first prediction modes include the first prediction mode and the second prediction mode, and the decoding end constructs an alternative prediction mode list 1 for the first prediction mode and an alternative prediction mode list 2 for the second prediction mode. In this way, when constructing different second combinations in the later stage, an alternative prediction mode is selected from the alternative prediction mode list 1 as the first prediction mode, and an alternative prediction mode is selected from the alternative prediction mode list 2 as the second prediction mode. In this way, a weight derivation mode, as well as the currently selected first prediction mode and the second prediction mode constitute a second combination. The embodiment of the present application does not limit the method for determining the candidate prediction mode list corresponding to each prediction mode in the K first prediction modes. In one possible implementation, for any prediction mode among the K first prediction modes, a candidate prediction mode list corresponding to the prediction mode and at least one of the prediction modes corresponding to the weight-derived mode are determined; based on the candidate prediction mode list and at least one of the prediction modes corresponding to the weight-derived mode, an alternative prediction mode list corresponding to the prediction mode is determined. In the embodiment of the present application, determining a candidate prediction mode list corresponding to a prediction mode among the K first prediction modes is substantially similar to the process of determining a candidate prediction mode list corresponding to the current component block, and details may be referred to the following description. In some embodiments, the candidate prediction mode list includes one or more inter-frame prediction modes, for example, at least one of skip, merge, normal inter-frame prediction mode, unidirectional prediction, bidirectional prediction, multi-hypothesis prediction, etc. In some embodiments, the candidate prediction mode list includes one or more intra prediction modes, for example, at least one of a direct current (DC) mode, a planar (PLANAR) mode, an angle mode, etc. Optionally, the candidate prediction mode list includes at least one intra prediction mode in the MPM list. In some embodiments, the candidate prediction mode list may also include modes such as IBC and palette. The present application does not impose any restrictions on the types of prediction modes and the number of prediction modes included in the above candidate prediction mode list. In some embodiments, the candidate prediction mode list is determined by at least one of the following methods: Mode 1: the above-mentioned candidate prediction mode list includes a preset mode. Method 2: the above-mentioned candidate prediction mode list includes the modes in the MPM list. In some embodiments, the first candidate intra prediction mode list may be an MPM list of the current component block. For example, in VVC, the current component block may obtain an MPM list of length 6. In addition, in some subsequent technical evolutions, there is a secondary MPM solution that may derive an MPM list of length 22, or the sum of the lengths of the first MPM list and the second MPM list is 22. That is, the embodiment of the present application may use MPM to screen the intra prediction mode. In some embodiments, if the first candidate prediction mode list determined above does not include the preset mode, the preset mode is added to the candidate prediction mode list. In an example, the preset mode is several preset prediction modes. Optionally, the preset mode includes at least one of DC, horizontal mode, and vertical mode. In another example, the preset mode is determined by determining the image type corresponding to the current component block and according to the image type corresponding to the current component block. Commonly used image types now include I images, B images, and P images, and commonly used slice types include I slice, B slice, and P slice. Taking slice type as an example, the same applies to image type. I slice can only have intra-frame coded blocks, while B slice and P slice can have both intra-frame coded blocks and inter-frame coded blocks. That is to say, the surroundings of the current component block in I slice are all intra-frame coded blocks, while in B slice and P slice, the surroundings of the current component block may be intra-frame coded blocks or inter-frame coded blocks. Therefore, for some intra-frame GPM methods in this application, it can obtain more relevant information in I slice, such as the intra-frame prediction mode of adjacent blocks. However, the relevant information obtained in B slice and P slice is relatively less. Therefore, different rules can be set for different image types. For example, when constructing the candidate prediction mode list, if the image type corresponding to the current component block is B type or P type, more preset modes are added, such as adding some other angle modes on the basis of DC, horizontal mode and vertical mode, such as upper right direction (mode 2 in VVC), lower left direction (mode 66 in VVC), upper left direction (mode 34 in VVC), etc. Or different candidate prediction mode list number limits are used for blocks of different image types. The above-mentioned method of determining the image type corresponding to the current component block may be to determine the image type corresponding to the current component block according to the image type of the current image to which the current component block belongs or the image type of the current slice to which the current component block belongs. For example, the image type of the current image to which the current component block belongs or the image type of the current slice to which the current component block belongs is determined as the image type corresponding to the current component block. Optionally, a preset mode may be added under certain conditions. An example is adding a preset mode when the number of prediction modes in the candidate prediction modes is less than or equal to a threshold. The threshold may be 3, 4, 5, 6, etc. Mode 3: the candidate prediction mode list includes a set of candidate prediction modes determined according to some rules, such as equal-interval screening. Mode 4: Determine a candidate prediction mode list according to a prediction mode used by at least one block adjacent to the current component block. For example, the prediction mode used by one or more blocks adjacent to the current component block is added to the candidate prediction mode list to obtain the candidate prediction mode list of the current component block, or the candidate prediction mode list corresponding to the kth prediction mode among K prediction modes is obtained, where the kth prediction mode is any prediction mode among the K prediction modes. For another example, the prediction mode corresponding to the kth prediction mode among the prediction modes used by one or more blocks adjacent to the current component block is added to the candidate prediction mode list corresponding to the kth prediction mode. For example, assuming K=2, the kth prediction mode is the first prediction mode, and the two blocks adjacent to the current component block are also assumed to use two prediction modes for weighted prediction, wherein the two prediction modes used by the first adjacent block are prediction mode 1 and prediction mode 3, respectively, and the two prediction modes used by the second adjacent block are prediction mode 4 and prediction mode 5, respectively. In this way, prediction mode 1 and prediction mode 4 can be added to the candidate prediction mode list corresponding to the first prediction mode. Method 5, determine the image type corresponding to the current component block, and determine the candidate prediction mode list according to the image type corresponding to the current component block. For example, if the image type corresponding to the current component block is B type or P type, then at least one of DC, horizontal mode, vertical mode and some angle modes can be added to the first candidate prediction mode list. For another example, if the image type corresponding to the current component block is I type, then at least one of DC, horizontal mode and vertical mode can be added to the candidate prediction mode list. Method 6, determining at least one of the second prediction mode used by the first component block at a preset position, at least one component block among the second component block and the third component block (for example, a chroma block and / or a luminance block), the third prediction mode used by the decoded first component block, the second component block and at least one component block among the third component block (for example, a luminance block and / or a chroma block) around the current component block, the fourth prediction mode used by the first component block (for example, a luminance block) corresponding to the internal preset area of ​​the current component block, and the fifth prediction mode related to the first component block corresponding to the current component block; and determining a candidate prediction mode list of the current component block according to at least one of the second prediction mode, the third prediction mode, the fourth prediction mode and the fifth prediction mode. In some embodiments, in mode 6, at least one of the first component block, the second component block, and the third component block decoded around the current component block includes at least one of the first component block, the second component block, and the third component block corresponding to the decoded area above and / or on the left of the current component block. For example, as shown in Figure 18, the prediction mode used by blocks 0 to 5 is selected as the second prediction mode, and / or the prediction mode used by at least one block represented by the ellipsis between blocks 2 and 3 is selected as the second prediction mode, and / or the prediction mode used by at least one block represented by the ellipsis between blocks 1 to 5 is selected as the second prediction mode. In an example, the first component block in this embodiment can be a luminance CU, and the second component block and / or the third component block can be a chrominance CU. At this time, the prediction mode used by the luminance CU and / or chrominance CU decoded around the current component block is determined as the second prediction mode. In some embodiments, in the above-mentioned method 6, the internal preset area of ​​the current component block can be any area inside the current component block. The first component block corresponding to the internal area of ​​the current component block can be understood as a first component block in the same space as the internal area of ​​the current component block. Optionally, the first component block can be a brightness CU. For example, according to the coordinates of the upper left corner vertex of the internal area of ​​the current component block, the brightness CU corresponding to the coordinates is mapped, and then the prediction mode used by the brightness CU is determined to be the fourth prediction mode. In some embodiments, in the above-mentioned method 6, the method of determining the fifth prediction mode related to the first component block corresponding to the current component block includes at least the following examples: Example 1: Since the first component block corresponding to the current component block has been decoded, the prediction mode used by the first component block is determined to be the fifth prediction mode. In one example, the first component block may include multiple first component CUs, and the prediction modes used by the multiple first component CUs may be the same or different. In an embodiment of the present application, the prediction mode used by at least one first component CU among the multiple first component CUs included in the first component block may be determined to be the fifth prediction mode. Example 2: Determine the fifth prediction mode according to the texture of the first component block corresponding to the current component block. Exemplarily, determine the texture direction of the first component block; and determine the fifth prediction mode according to the texture direction. The embodiment of the present application does not limit the specific method of determining the texture direction of the first component block corresponding to the current component block. In a possible implementation, the texture directions of certain points in the first component block corresponding to the current component block are determined, and the texture direction of the first component block is determined based on the texture directions of these points. In some embodiments, for ease of description, the points in the first component block for which the texture directions need to be determined are recorded as texture points. These texture points may be default, for example, the encoding end and the decoding end default to using some points in the first component block as texture points to calculate their texture directions. In some embodiments, the above-mentioned texture points are selected according to a preset method, for example, the decoding end selects multiple texture points in the first component block according to a preset texture point selection method. For each of the multiple texture points, the gradient of each texture point is determined, for example, the horizontal gradient and the vertical gradient of each texture point are determined, and then the texture direction of each texture point is determined according to the horizontal gradient and the vertical gradient of each texture point. Next, the texture direction of the first component block is determined according to the texture direction of each texture point. Exemplarily, one or more of the texture directions corresponding to the plurality of texture points are determined as the texture direction of the first component block. For example, any one or more of the texture directions corresponding to the plurality of texture points are determined as the texture direction of the first component block. For another example, one or more texture directions corresponding to a plurality of texture points that appear the most times are determined as the texture directions of the first component block. After the texture direction of the first component block corresponding to the current component block is determined according to the above, the fifth prediction mode is determined according to the texture direction. In an example, a prediction mode in which the prediction direction is parallel to the texture direction is determined as the fifth prediction mode. In an example, a prediction mode in which the prediction direction is perpendicular to the texture direction is determined as the fifth prediction mode. In an example, a prediction mode in which the prediction direction is parallel to the texture direction and a prediction mode in which the prediction direction is perpendicular to the texture direction are determined as the fifth prediction mode. It should be noted that the prediction mode in which the prediction direction is parallel to the texture direction includes a prediction mode in which the prediction direction is parallel to the texture direction and / or approximately parallel to the texture direction. The prediction mode in which the prediction direction is perpendicular to the texture direction includes a prediction mode in which the prediction direction is perpendicular to the texture direction and / or approximately perpendicular to the texture direction. It should be noted that the above-mentioned methods 1 to 6 can be used alone as methods for determining a candidate prediction mode list, or can be used in any combination. In some embodiments, the candidate prediction mode list includes at least one of a candidate intra prediction mode list and a candidate inter prediction mode list, wherein the candidate intra prediction mode list includes at least one candidate intra prediction mode, and the candidate inter prediction mode list includes at least one candidate inter prediction mode. According to the above method, after obtaining the candidate prediction mode list of the current component block, Q prediction modes are determined according to the candidate prediction mode list, for example, all or part of the candidate prediction modes included in the candidate prediction mode list are determined as all or part of the Q prediction modes. The process of determining the prediction mode corresponding to the weight derivation mode is introduced below. In the embodiments of the present application, the prediction mode corresponding to the weight derivation mode is a general term, for example, it can be a prediction mode corresponding to a preset weight derivation mode, or prediction modes corresponding to several preset weight derivation modes. In some embodiments, the prediction mode corresponding to the weight derivation mode can also be understood as a prediction mode list corresponding to the weight derivation mode, and the prediction mode list includes at least one prediction mode. In some embodiments, the prediction mode corresponding to the above-mentioned weight derivation mode includes the prediction mode corresponding to at least one weight derivation mode among the P weight derivation modes. At this time, determining the prediction mode corresponding to the weight derivation mode includes: for the p-th weight derivation mode among the P weight derivation modes, determining the prediction mode corresponding to the p-th weight derivation mode, and determining the prediction mode corresponding to the above-mentioned weight derivation mode according to the prediction mode corresponding to at least one weight derivation mode among the P weight derivation modes, where p is a positive integer. In an embodiment of the present application, the process of determining the prediction mode corresponding to each of P weight derivation modes is basically the same. For ease of description, the pth weight derivation mode among the P weight derivation modes is taken as an example for explanation below. There are two ways to determine the prediction mode corresponding to the p-th weight derivation mode: Method 1: If at least one of the prediction modes corresponding to the p-th weight derivation mode is an intra-frame prediction mode, the angle index is determined according to the p-th weight derivation mode; the intra-frame prediction mode corresponding to the angle index is determined to be at least one of the prediction modes corresponding to the p-th weight derivation mode. The angle index is used to indicate the angle index of the dividing line of the weight. In some embodiments, the angle index is represented by the field angleIdx. Table 2 above shows the correspondence between merge_gpm_partition_idx and angleIdx. Referring to Table 2 above, the angle index can be derived according to the p-th weight derivation mode. In the present application, the angle index corresponds to the intra-frame prediction mode, that is, different angle indices correspond to different intra-frame prediction modes. Exemplarily, the corresponding relationship between the angle index and the intra prediction mode is shown in Table 7: Table 7 angleIdx intra prediction mode 050242338434530…… In the first method, taking K=2 as an example, if the first prediction mode or the second prediction mode is an intra-frame prediction mode, the angle index is determined according to the pth weight derivation mode, for example, according to the above Table 2, the angle index corresponding to the pth weight derivation mode is derived. Then, in the above Table 7, the intra-frame prediction mode corresponding to the angle index is determined, for example, the angle index is 2, and its corresponding intra-frame prediction mode is 42, and then the intra-frame prediction mode 42 is determined as the first prediction mode or the second prediction mode. Method 2: If at least one of the prediction modes corresponding to the p-th weight derivation mode is an intra-frame prediction mode, determine the intra-frame prediction mode corresponding to the p-th weight derivation mode; and determine at least one of the intra-frame prediction modes corresponding to the p-th weight derivation mode as at least one of the prediction modes corresponding to the p-th weight derivation mode. Among them, the intra-frame prediction mode corresponding to the p-th weight derivation mode includes at least one of an intra-frame prediction mode in which the prediction direction is parallel to the weight boundary line, an intra-frame prediction mode in which the prediction direction is perpendicular to the boundary line, and a planar mode. It should be noted that the intra-frame prediction mode in which the prediction direction is parallel to the boundary line of the weight includes one or more intra-frame prediction modes in which the prediction direction is parallel to or approximately parallel to the boundary line of the weight. The intra-frame prediction mode in which the prediction direction is perpendicular to the boundary line of the weight includes one or more intra-frame prediction modes in which the prediction direction is perpendicular to or approximately perpendicular to the boundary line of the weight. In the second method, taking K=2 as an example, if the first prediction mode and / or the second prediction mode is an intra-frame prediction mode, the first prediction mode and / or the second prediction mode is determined from the intra-frame prediction mode corresponding to the weight derivation mode. For example, the first prediction mode and / or the second prediction mode can be an intra-frame prediction mode that is on the same straight line or approximately on the same straight line as the weight dividing line (also called the dividing line). Alternatively, the first prediction mode and / or the second prediction mode can be an intra-frame prediction mode whose prediction direction is perpendicular or approximately perpendicular to the weight dividing line. For example, the weight dividing line is horizontal, such as the modes with GPM indexes of 18, 19, 50, and 51 in Figure 4, and the first prediction mode and / or the second prediction mode is mode 18 in the horizontal direction or mode 50 in the vertical direction. According to the above steps, the decoding end determines the prediction mode corresponding to at least one of the P weight derivation modes, and then determines the prediction mode corresponding to the weight derivation mode according to the prediction mode corresponding to at least one of the P weight derivation modes. For example, all or part of the prediction mode corresponding to at least one of the P weight derivation modes is used as the prediction mode corresponding to the weight derivation mode. Furthermore, there may be repeated prediction modes among the prediction modes corresponding to the P weight derivation modes, and the repeated prediction modes are eliminated, and the remaining different prediction modes are determined as the prediction modes corresponding to the weight derivation modes. In the embodiment of the present application, in order to reduce the number of R second combinations, the prediction modes are screened, specifically, Q prediction modes are determined according to the above method. In some embodiments, in order to reduce the complexity of the decoding end, the number of the above-mentioned Q prediction modes is limited. For example, Q is less than or equal to a first preset threshold. The present application does not limit the specific value of the first preset threshold, which can be determined according to actual needs. For example, the first preset threshold is 6, that is, 6 prediction modes are selected to construct R second combinations to control the number of second combinations. In some embodiments, the size of Q is related to the size and / or shape of the current component block, wherein the shape of the current component block can be understood to be determined by the aspect ratio of the current component block. When predicting, for smaller blocks, similar prediction modes have little effect on the prediction results, while for larger blocks, similar prediction modes have more obvious effect on the prediction results. Based on this, the embodiment of the present application sets different Q values ​​for blocks of different sizes, that is, a larger Q value is set for larger blocks, and a smaller Q value is set for smaller blocks. At this time, when determining the Q value corresponding to the current component block, it is set according to the size of the current component block. For example, if the size of the current component block is greater than the first value, Q is greater than or equal to the second preset threshold. For another example, if the size of the current component block is less than or equal to the first value, Q is less than the third preset threshold. The embodiment of the present application does not limit the specific sizes of the first value, the second prediction threshold and the third preset threshold, wherein the third preset threshold is less than the second preset threshold. The following is an introduction to the process of determining P weight derivation modes in S101-A21-1. In the embodiment of the present application, the method of determining P weight derivation modes includes at least the following methods: Method 1: Select P weight derivation modes from the preset M weight derivation modes, where M is a positive integer greater than or equal to P. The embodiment of the present application does not limit the above-mentioned preset M weight derivation modes. In some embodiments, GPM includes 64 weight derivation modes, and AWP includes 56 weight derivation modes. In this embodiment, the above-mentioned preset M weight derivation modes include at least one weight derivation mode among the 64 weight derivation modes included in GPM, or include at least one weight derivation mode among the 56 weight derivation modes included in AWP. In some embodiments, the M weight derivation mode of the embodiment of the present application may support more angleIdx, or angleIdx different from VVC. For another example, the M weight derivation mode of the embodiment of the present application may support more distanceIdx, or distanceIdx different from VVC. In some embodiments, the above-mentioned preset M weight derivation modes can be derived through a preset weight derivation mode. For example, the embodiment of the present application uses the weight derivation mode corresponding to the AWP to determine M weight derivation modes. Optionally, the embodiment of the present application can also use other methods to derive M weight derivation modes. In some embodiments, if M is equal to P, the M weight derivation modes are determined as P weight derivation modes. In some embodiments, if M is greater than P, in order to further reduce the number of R second combinations, the preset M weight derivation modes are screened, and P weight derivation modes can be selected from the preset M weight derivation modes to construct R second combinations. In some embodiments, the weight derivation mode corresponding to the preset division angle and / or preset offset is eliminated from the M weight derivation modes to obtain P weight derivation modes. Since the same division angle in the weight derivation mode can correspond to multiple offsets, as shown in FIG. 19A , weight derivation modes 10, 11, 12, and 13 have the same division angle but different offsets, some weight derivation modes corresponding to the preset offsets can be removed, and / or some weight derivation modes corresponding to the preset division angles can also be removed. Doing so can reduce the total number of possible second combinations. And make the differences between each possible second combination more obvious. In some embodiments, the filtering conditions corresponding to different blocks may be different. Therefore, when determining the P weight derivation modes corresponding to the current component block, the filtering conditions corresponding to the current component block are first determined, and then P weight derivation modes are selected from the M weight derivation modes based on the filtering conditions corresponding to the current component block. In some embodiments, the screening condition corresponding to the current component block includes the screening condition corresponding to the size of the current component block and / or the screening condition corresponding to the shape of the current component block. When predicting, for smaller blocks, similar weight derivation modes have little effect on the prediction results, while for larger blocks, similar weight derivation modes have more obvious effects on the prediction results. Based on this, the embodiment of the present application sets different P values ​​for blocks of different sizes, i.e., a larger P value is set for larger blocks and a smaller P value is set for smaller blocks. In some embodiments, the above-mentioned screening conditions include an array including M elements, the M elements corresponding one-to-one to M weight derivation modes, and the element corresponding to each weight derivation mode is used to indicate whether the weight derivation mode is available, wherein whether the weight derivation mode is available can be understood as whether the weight derivation mode is used to form one of the P weight derivation modes for a subsequent second combination attempt. The above array can be a single-digit value or a two-digit value. For example, taking GPM as an example, there are 64 M weight export modes, and an array containing 64 elements is set, and the value of each element indicates whether the corresponding weight export mode is available. Taking a single-digit value as an example, a specific example is as follows, setting an array of g_sgpm_splitDir: g_sgpm_splitDir

[0064] ={ 1,1,1,0,1,0,1,0, 1,0,1,0,1,0,1,0, 1,0,1,1,1,0,1,0, 1,0,1,0,1,0,1,0, 0,0,0,0,1,1,0,1, 0,0,1,0,0,1,0,0, 1,0,1,1,0,1,0,0, 1,0,0,1,0,0,1,0 }; Among them, the value of g_sgpm_splitDir[x] is 1, which means that the weight export mode with index x is available, and 0, which means that the weight export mode with index x is not available. In some embodiments, if the filtering conditions corresponding to the current component block include the filtering conditions corresponding to the size of the current component block and the filtering conditions corresponding to the shape of the current component block, and for the same weight derivation mode, if the filtering conditions corresponding to the size of the current component block and the filtering conditions corresponding to the shape of the current component block indicate that the weight derivation mode is available, then the weight derivation mode is determined to be one of the P weight derivation modes; if at least one of the filtering conditions corresponding to the size of the current component block and the filtering conditions corresponding to the shape of the current component block indicates that the weight derivation mode is unavailable, then it is determined that the weight derivation mode does not constitute P weight derivation modes. In some embodiments, the filtering conditions corresponding to different block sizes and the filtering conditions corresponding to different block shapes can be implemented using multiple arrays respectively. In some embodiments, filtering conditions corresponding to different block sizes and filtering conditions corresponding to different block shapes can be implemented using a two-bit array, that is, a two-bit array includes both filtering conditions corresponding to block sizes and filtering conditions corresponding to block shapes. For example, the filtering condition corresponding to a block of size A and shape B is as follows, and the filtering condition is represented by a two-bit array: g_sgpm_splitDir

[0064] = { (1,1),(1,1),(1,1),(1,0),(1,0),(0,0),(1,0),(1,1), (1,1),(0,0),(1,1),(1,0),(1,0),(0,0),(1,0),(1,0),(1,1), (0,1),(0,0),(1,1),(0,0),(1,0),(0,0),(1,0,(0,0), (1,1),(0,0),(0,1),(1,0),(1,0),(1,0),(1,0),(0,0), (0,0),(0,0),(1,1),(0,0),(1,1),(1,1),(1,0,(0,1), (0,0),(0,0),(1,1),(0,0),(1,0),(0,0),(1,0),(0,0), (1,0),(0,0),(1,1),(1,0),(1,0),(1,0),(0,0),(0,0), (1,1),(0,0),(1,1),(0,0),(0,0),(1,0),(1,1),(0,0) }; Among them, the value of g_sgpm_splitDir[x] is 1, indicating that the weight derivation mode with index x is available, and one of the values ​​of g_sgpm_splitDir[x] is 0, indicating that the weight derivation mode with index x is not available. For example, g_sgpm_splitDir[4] = (1, 0), indicating that weight derivation mode 4 is available for blocks of size A, but not for blocks of shape B. Therefore, if the block size is A and the shape is B, the weight derivation mode is not available. It should be noted that the above example takes GPM including 64 weight derivation modes, but the weight derivation modes of the embodiments of the present application include but are not limited to the 64 weight derivation modes included in GPM and the 56 weight derivation modes included in AMP. After the decoding end determines Q prediction modes and P weight derivation modes according to the above steps, R different second combinations are formed according to the Q prediction modes and P weight derivation modes. Then, a candidate combination list is determined according to the R second combinations, and then the first weight derivation mode and K first prediction modes are determined from the candidate combination list. In some embodiments, in order to further improve the speed of constructing the candidate combination list, the decoding end screens the Q prediction modes and the P weight derivation modes determined above again. At this time, the above S101-A21-2 comprises the following steps S101-A21-21 to S101-A21-23 based on the determined P weight derivation modes and Q prediction modes: S101-A11-21. Select S weight derivation modes from P weight derivation modes, where S is a positive integer less than or equal to P. Specifically, weight derivation patterns with a low probability of occurrence are eliminated from the P weight derivation patterns determined above to obtain S screened weight derivation patterns. The methods for selecting S weight derivation modes from P weight derivation modes in S101-A11-21 above include but are not limited to the following: Method 1, for the i-th weight derivation mode among P weight derivation modes, determine the weights of K second prediction modes on the first component block according to the i-th weight derivation mode, the K second prediction modes are any K prediction modes among the Q prediction modes, and i is a positive integer from 1 to P; if the weight of any prediction mode among the K prediction modes on the first component block is less than a first preset value, then the i-th weight derivation mode is eliminated from the P weight derivation modes to obtain S weight derivation modes. In this method 1, if the weight of the first component block derived by a weight derivation mode makes a certain prediction mode have little effect on the first component block, or has no effect on the first component block, then this weight derivation mode is not used. For example, the weight derivation mode 52 in Figure 4 (square block) makes the weight of the second prediction mode on the first component block smaller. For another example, the weight derivation mode 54 makes the weight of the second prediction mode on the first component block 0, that is, it can be considered that under the weight derivation mode 54, the second prediction mode has no effect on the first component block, and the prediction value of the first component block is determined entirely by the first prediction mode. In this case, the second prediction mode has no effect on anything, and such a weight derivation mode needs to be eliminated from the P weight derivation modes. It should be noted that the same weight derivation mode for blocks of different shapes may cause different effects on the two prediction modes. Since the current component block may be a square or a rectangle, the length may be larger than the width or the width may be larger than the length, and the ratio may also be 1:2, 1:4, etc. Figures 19A and 19B show the weight derivation mode of GPM in 32x64 blocks and 64x32 blocks. It can be seen that the intersection of the dividing line and the block boundary of the same weight derivation mode in different shapes is not the same. Because the block shape has changed, but the angle of the dividing line does not change according to the change of the block shape. As shown in Figure 19A, the weight derivation mode with an index of 52, in the 32x64 block, when the interface of the weight derivation mode with an index of 52 is extended to the first component block area corresponding to the current component block, it intersects with the first component block area, so that the weight of the second prediction mode in the first component block is not less than the preset value, which means that the second prediction mode has an influence in the first component block. However, as shown in FIG19B , for the same weight derivation mode with index 52, in a 64x32 block, when the boundary surface of the weight derivation mode with index 52 is extended toward the first component block area corresponding to the current component block, it does not intersect with the first component block area, so that the weight of the second prediction mode in the first component block is 0, which means that the second prediction mode has no influence on the first component block. In the above-mentioned method 1, among the P weight derivation modes, the weight derivation mode that makes the weight of any prediction mode among the K prediction modes on the first component block less than the first preset value is eliminated to obtain S weight derivation modes. The embodiment of the present application does not limit the specific value of the first preset value, for example, it is a smaller value greater than or equal to 0. Method 2, for the i-th weight derivation mode among P weight derivation modes, determine the cost of using the i-th weight derivation mode to predict the first component block, where i is a positive integer from 1 to P; according to the cost corresponding to the i-th weight derivation mode, select S weight derivation modes from the P weight derivation modes. In this method 2, S weight derivation modes are selected from the P weight derivation modes by calculating the cost corresponding to each of the P weight derivation modes. In an embodiment of the present application, the weight derivation mode and K prediction modes are taken as a combination to calculate the cost. Thus, for the convenience of calculation, the costs of P weight derivation modes are calculated based on the given K prediction modes. That is, the P weight derivation modes are respectively combined with the set K prediction modes to obtain P combinations, and the cost corresponding to each combination in the P combinations is calculated to obtain the costs of the P weight derivation modes. For example, assuming that the given K prediction modes are prediction mode 1 and prediction mode 2, for the i-th weight derivation mode among the P weight derivation modes, the i-th weight derivation mode forms a combination with prediction mode 1 and prediction mode 2, which is recorded as combination i. Combination i is used to predict the first component block corresponding to the current component block, and the prediction value of the first component block under combination i is obtained. According to the prediction value of the first component block under combination i and the reconstructed value of the first component block, the prediction distortion cost corresponding to combination i is determined, and the prediction distortion cost corresponding to combination i is determined as the cost corresponding to the i-th weight derivation mode. In this way, the cost corresponding to any one of the P weight derivation modes can be determined. According to the above method, after determining the cost corresponding to the ith weight derivation mode among the P weight derivation modes, S weight derivation modes are selected from the P weight derivation modes according to the cost corresponding to the ith weight derivation mode. In the second mode, the decoding end selects S weight derivation modes from P weight derivation modes according to the cost corresponding to the i-th weight derivation mode, including the following modes: The first method is, if the cost corresponding to the ith weight derivation mode is less than the second preset value, then a weight derivation mode similar to the ith weight derivation mode is selected from the P weight derivation modes; and S weight derivation modes are determined according to the ith weight derivation mode and the similar weight derivation mode of the ith weight derivation mode. Among them, the similar weight derivation mode of the ith weight derivation mode can be understood as a weight derivation mode whose prediction result is similar to the prediction result of the ith weight derivation mode, for example, the similar weight derivation mode of the ith weight derivation mode includes a weight derivation mode with a division angle similar to that of the ith weight derivation mode, and / or a weight derivation mode with an offset similar to that of the ith weight derivation mode, wherein the offset of the weight derivation mode can also be understood as the intercept of the dividing line of the weight derivation mode on the edge of the current component block. Exemplarily, the above-mentioned similar division angles may include the same division angles and different offsets, such as weight derivation mode 11 and weight derivation mode 13 in Figure 4, and may also include the same division angles and similar offsets, such as weight derivation mode 11 and weight derivation mode 12 in Figure 4, and may also include similar division angles and different offsets, such as weight derivation mode 9 and weight derivation mode 11 in Figure 4, and may also include similar division angles and similar offsets, etc., such as weight derivation mode 9 and weight derivation mode 12 in Figure 4. Exemplarily, the above-mentioned similar offsets may include similar offsets and the same division angles, such as weight derivation mode 29 and weight derivation mode 30 in Figure 4, and also include the same or similar offsets and similar division angles, such as weight derivation mode 2 and weight derivation mode 38 in Figure 4. In some embodiments, a similar weight derivation pattern to the i-th weight derivation pattern may be understood as a weight derivation pattern having an index close to that of the i-th weight derivation pattern. In the first method, if the cost corresponding to the ith weight derivation mode is less than the second preset value, it means that when the ith weight derivation mode is used to predict the current component block, a better prediction effect may be achieved. At this time, the ith weight derivation mode is selected from the P weight derivation modes to construct the subsequent R second combinations. In addition, since the weight derivation mode similar to the ith weight derivation mode has similar characteristics to the ith weight derivation mode, a similar weight derivation mode of the ith weight derivation mode is selected from the P weight derivation modes to construct the subsequent R second combinations. Next, a weight derivation mode is selected from the remaining weight derivation modes of the P weight derivation modes as the new ith weight derivation mode, and the above steps are repeated to obtain S weight derivation modes. The embodiment of the present application does not limit the size of the second preset value, which is determined according to actual needs. In some embodiments, the decoding end may also select S weight derivation modes from P weight derivation modes according to the second method below. The second method is that if the cost corresponding to the ith weight derivation mode is greater than the third preset value, the ith weight derivation mode and similar weight derivation modes of the ith weight derivation mode are eliminated from the P weight derivation modes to obtain at least one weight derivation mode after elimination; and S weight derivation modes are determined based on the at least one weight derivation mode after elimination. In the second method, if the cost corresponding to the ith weight derivation mode is less than the third preset value, it means that when the ith weight derivation mode is used to predict the current component block, a better prediction effect may not be achieved. At this time, the ith weight derivation mode is eliminated from the P weight derivation modes. In addition, since the weight derivation mode similar to the ith weight derivation mode has similar characteristics to the ith weight derivation mode, the similar weight derivation mode of the ith weight derivation mode is also eliminated from the P weight derivation modes to obtain a set of eliminated weight derivation modes. Then, in the set of eliminated weight derivation modes, a weight derivation mode is selected as the new ith weight derivation mode, and the above steps are repeated to finally obtain the weight derivation modes included in the weight derivation mode set, which are determined to be S weight derivation modes. The embodiment of the present application does not limit the size of the third preset value, which is determined according to actual needs. The third preset value is greater than the second preset value. According to the above steps, after the decoding end selects S weight derivation modes from P weight derivation modes, the following steps S101-A21-22 are performed. S101-A21-22. Select T prediction modes from Q prediction modes, where T is a positive integer less than or equal to Q. The embodiment of the present application does not limit the method of selecting T prediction modes from Q prediction modes. In some embodiments, preset T prediction modes are selected from the Q prediction modes. In some embodiments, for the i-th prediction mode among Q prediction modes, the decoding end determines the cost of using the i-th prediction mode to predict the first component block, where i is a positive integer from 1 to Q; based on the cost corresponding to the i-th prediction mode, T prediction modes are selected from the Q prediction modes. In an embodiment of the present application, the weight derivation mode and K prediction modes are taken as a combination to calculate the cost. Thus, for the convenience of calculation, the costs of Q weight derivation modes are calculated based on a given weight derivation mode and other K-1 prediction modes. That is, the Q prediction modes are respectively combined with the set weight derivation mode and K-1 prediction modes to obtain Q combinations, and the cost corresponding to each of the Q combinations is calculated to obtain the costs of the Q prediction modes. For example, assuming that the given K-1 prediction modes are prediction mode 1, and the given weight derivation mode is weight derivation mode 1, for the i-th prediction mode among the Q prediction modes, weight derivation mode 1, the i-th prediction mode and prediction mode 1 form a combination, which is recorded as combination i. Combination i is used to predict the first component block, and the prediction value of the first component block under combination i is obtained. According to the prediction value of the first component block under combination i and the reconstructed value of the first component block, the prediction distortion cost corresponding to combination i is determined, and the prediction distortion cost corresponding to combination i is determined as the cost corresponding to the i-th prediction mode. In this way, the cost corresponding to any one of the Q prediction modes can be determined. According to the above method, after the cost corresponding to the i-th prediction mode among the Q prediction modes is determined, T prediction modes are selected from the Q prediction modes according to the cost corresponding to the i-th prediction mode. The decoding end selects T prediction modes from Q prediction modes according to the cost corresponding to the i-th prediction mode in the following manner: In the first way, if the cost corresponding to the ith prediction mode is less than the fourth preset value, a prediction mode similar to the ith prediction mode is selected from the Q prediction modes; and T prediction modes are determined according to the ith prediction mode and the similar prediction modes of the ith prediction mode. Among them, the prediction mode similar to the ith prediction mode can be understood as a prediction mode whose prediction result is similar (or close) to the prediction reception of the ith prediction mode, such as a prediction mode whose prediction direction (or angle) is close to the prediction direction (or angle) of the ith prediction mode, or a prediction mode whose prediction mode index is close to the index of the ith prediction mode, such as a prediction mode whose index is 1, 2, etc. larger than the index of the ith prediction mode, or a prediction mode whose index is 1, 2, etc. smaller than the index of the ith prediction mode. In the first method, if the cost corresponding to the i-th prediction mode is less than the fourth preset value, it means that when the i-th prediction mode is used to predict the current component block, a better prediction effect may be achieved. At this time, the i-th prediction mode is selected from the Q prediction modes to construct the subsequent R second combinations. In addition, since the prediction mode similar to the i-th prediction mode has similar characteristics to the i-th prediction mode, a similar prediction mode of the i-th prediction mode is selected from the Q prediction modes to construct the subsequent R second combinations. Then, a prediction mode is selected from the remaining prediction modes of the Q prediction modes as the new i-th prediction mode, and the above steps are repeated to obtain T prediction modes. The embodiment of the present application does not limit the size of the fourth preset value, which is determined according to actual needs. The second method is that if the cost corresponding to the i-th prediction mode is greater than the fifth preset value, the i-th prediction mode and similar prediction modes of the i-th prediction mode are eliminated from the Q prediction modes to obtain at least one prediction mode after elimination; and T prediction modes are determined based on the at least one prediction mode after elimination. In the second method, if the cost corresponding to the ith prediction mode is greater than the fifth preset value, it means that when the ith prediction mode is used to predict the current component block, a better prediction effect may not be achieved. At this time, the ith prediction mode is eliminated from the Q prediction modes. In addition, since the prediction mode similar to the ith prediction mode has similar characteristics to the ith prediction mode, the similar prediction mode of the ith prediction mode is also eliminated from the Q prediction modes to obtain a set of eliminated prediction modes. Then, in the set of eliminated prediction modes, a prediction mode is selected as the new ith prediction mode, and the above steps are repeated to finally obtain the prediction modes included in the prediction mode set, which are determined to be T prediction modes. The embodiment of the present application does not limit the size of the fifth preset value, which is determined according to actual needs. The fifth preset value is greater than the fourth preset value. According to the above steps, S weight derivation modes are selected from P weight derivation modes, and T prediction modes are selected from Q prediction modes. Then, the following S101-A21-23 is executed. S101-A21-23. Form R second combinations based on the S weight derivation modes and the T prediction modes. Specifically, a weight derivation mode is selected from the S weight derivation modes, and K prediction modes are selected from the T prediction modes. This weight derivation mode and the K prediction modes form a second combination. By repeating this step, R second combinations can be obtained. From the above, it can be seen that a second combination includes a weight derivation mode and K prediction modes. In this way, when screening the prediction modes, the possible selection of another element can be limited when the K elements in a combination are fixed. For example, when K=2, the possible selection of another element can be limited when it is used in combination with two of the elements. The following introduces an implementation process of the above S101-A21-2 by taking the screening process of another prediction mode when the weight derivation mode and one prediction mode are fixed as an example. In some embodiments, the above S101-A21-2 includes: for the i-th weight derivation mode among P weight derivation modes, determining the cost of using the i-th weight derivation mode and the j-th prediction mode among Q prediction modes to predict the first component block; if the cost corresponding to the combination of the i-th weight derivation mode and the j-th prediction mode is greater than a sixth preset value, then eliminating the j-th prediction mode and similar prediction modes of the j-th prediction mode from the Q prediction modes to obtain at least one prediction mode after elimination; constructing R second combinations based on the i-th weight derivation mode and the at least one prediction mode after elimination. In this embodiment, when the weight derivation mode and one prediction mode are fixed, the other prediction mode is screened. For example, if a certain intra-frame prediction mode cannot obtain a relatively small cost as the first prediction mode under a certain weight derivation mode, then the intra-frame prediction mode similar to the intra-frame prediction mode under the weight derivation mode will no longer be tried as the first prediction mode. Specifically, for the i-th weight derivation mode among the P weight derivation modes, it is assumed that K=2, that is, the combination includes the i-th weight derivation mode, the first prediction mode and the second prediction mode. Assume that the second prediction mode is set to prediction mode 1, and the prediction mode 1 can be one of the Q prediction modes, or can be another prediction mode outside the Q prediction modes. Determine the possible selection of the first prediction mode from the Q prediction modes, specifically, take the j-th prediction mode among the Q prediction modes as the first prediction mode. At this time, determine the prediction value of the first component block when the combination j composed of the i-th weight derivation mode, the j-th prediction mode and the prediction mode 1 predicts the first component block, and determine the cost corresponding to the combination j based on the prediction value, and determine the cost corresponding to the combination j as the cost corresponding to the j-th prediction mode. Next, determine whether the cost corresponding to the j-th prediction mode is greater than the sixth preset value. If the cost corresponding to the j-th prediction mode is greater than the sixth preset value, it means that the combination of the j-th prediction mode, the i-th weight derivation mode and the prediction mode 1 cannot achieve accurate prediction of the first component block. At this time, the j-th prediction mode is eliminated from the Q prediction modes. Since the prediction mode similar to the j-th prediction mode has similar characteristics to the j-th prediction mode, the similar prediction mode of the j-th prediction mode is eliminated from the Q prediction modes to obtain the eliminated prediction mode set. In the eliminated prediction mode set, a new prediction mode is selected as the new j-th prediction mode, and the above steps are repeated to obtain the final eliminated prediction mode set corresponding to the i-th weight derivation mode. According to the above steps, the final eliminated prediction mode set corresponding to each weight derivation mode in P weight derivation modes can be determined, so that R second combinations can be constructed based on the P weight derivation modes and their respective corresponding final eliminated prediction mode sets. It should be noted that the above embodiment shows a method of screening prediction modes in the form of combination. Optionally, any one of the weight derivation modes and the prediction modes can also be screened in the form of combination to finally construct R second combinations. After the decoding end determines R second combinations according to the above methods, for any second combination of the R second combinations, the weight derivation mode and K prediction modes in the second combination are used to predict the first component block to obtain the prediction value of the first component block corresponding to the second combination. The following introduces a process of using any second combination to predict the first component block and obtain a predicted value of the first component block. First, the weight of the first component block is determined using the weight derivation mode included in the second combination. The weight of the first component block can be understood as the weight of the prediction value corresponding to the first component block. That is, according to the weight derivation mode included in the second combination, the weight of the first component block is determined, according to the K prediction modes included in the second combination, the K prediction values ​​of the first component block are determined, and the K prediction values ​​of the first component block are weighted using the weight of the first component block to obtain the prediction value of the first component block. In some embodiments, determining the weight of the first component block according to the weight derivation mode comprises the following steps: Step 1: Determine the angle index and distance index according to the weight derivation mode; Step 2: Determine the weight of the first component block according to the angle index, the distance index and the size of the first component block. The present application can derive the weight of the first component block in the same manner as the weight of the derived prediction value. For example, first, according to the weight derivation mode, determine the angle index and distance index, wherein the angle index can be understood as the angle index of the dividing line of each weight derived by the weight derivation mode. Exemplarily, according to the above Table 2, the angle index and distance index corresponding to the weight derivation mode can be determined. For example, if the weight derivation mode is 27, the corresponding angle index is 12 and the distance index is 3. Then, according to the angle index, the distance index and the size of the first component block, determine the weight of the first component block. In the above step 2, the method of determining the weight of the first component block according to the angle index, the distance index and the size of the first component block includes but is not limited to the following methods: Method 1: directly determine the weight of the first component block according to the angle index, the distance index and the size of the first component block. In this case, the above step 2 includes the following steps 21 to 23: Step 21: determining a first parameter of a pixel in the first component block according to the angle index, the distance index and the size of the first component block; Step 22: Determine the weight of the pixel in the first component block according to the first parameter of the pixel in the first component block; Step 23: Determine the weight of the first component block according to the weights of the pixels in the first component block. In this implementation, the weights of the pixels in the first component block are determined according to the angle index, the distance index and the size of the first component block, and then the weight matrix composed of the weights of each point in the first component block is determined as the weight of the first component block. The first parameter of the present application is used to determine the weight. In some embodiments, the first parameter is also called a weight index. In a possible implementation, the offset and the first parameter may be determined in the following manner: The inputs to the first component block weight derivation process are: the width of the first component block nCbW, the height of the current component block nCbH; the GPM "division" angle index variable angleId; the GPM distance index variable distanceIdx; the component index variable cIdx, which determines the weight of the first component block, so cIdx is 0, indicating the brightness component. Among them, the variables nW, nH, shift1, offset1, displacementX, displacementY, partFlip and shiftHor are derived as follows: nW=(cIdx==0)? nCbW:nCbW*SubWidthC nH=(cIdx==0)? nCbH:nCbH*SubHeightC shift1 = Max(5,17-BitDepth) where BitDepth is the bit depth of the codec offset1=1<<(shift1-1) displacementX=angleIdx displacementY=(angleIdx+8)%32 partFlip=(angleIdx>=13&&angleIdx<=27)? 0:1 shiftHor=(angleIdx%16==8||(angleIdx%16!=0&&nH>=nW))? 0:1 Among them, the offsets offsetX and offsetY are derived as follows: – If the value of shiftHor is 0: offsetX=(-nW)>>1 offsetY=((-nH)>>1)+(angleIdx<16?(distanceIdx*nH)>>3:-((distanceIdx*nH)>>3)) – Otherwise (i.e. the value of shiftHor is 1): offsetX=((-nW)>>1)+(angleIdx<16?(distanceIdx*nW)>>3:-((distanceIdx*nW)>>3) offsetY=(-nH)>>1 The weight matrix wTemplateValue[x][y] of the first component block (where x = -nTmW..nCbW–1, y = -nTmH..nCbH-1, excluding the case where x and y are both greater than or equal to 0) is derived as follows in this example with the coordinates of the upper left corner of the first component block as (0, 0): – The variables xL and yL are derived as follows: xL=(cIdx==0)? x:x*SubWidthC yL=(cIdx==0)? y:y*SubHeightC Where disLut is determined according to Table 3 above Among them, the first parameter weightIdx is derived as follows: weightIdx=(((xL+offsetX)<<1)+1)*disLut[displacementX]+(((yL+offsetY)<<1)+1)*disLut[displacementY] According to the above method, after the first parameter weightIdx is determined, the weight at the midpoint (x, y) of the first component block is determined according to weightIdx. In the present application, the manner of determining the weight of the pixel in the first component block according to the first parameter of the pixel in the first component block in the above step 22 includes but is not limited to the following: Method 1, determining the second parameter of the pixel in the first component block according to the first parameter of the pixel in the first component block; determining the weight of the pixel in the first component block according to the second parameter of the pixel in the first component block. The second parameter is also used to determine the weight. In some embodiments, the second parameter is also called a weight index under the first component, and the first component may be a brightness component or the like. For example, the weights of the pixels in the first component block are determined according to the formula: weightIdxL=partFlip? 32+weightIdx:32-weightIdx wTemplateValue[x][y]=Clip3(0,8,(weightIdxL+4)>>3) Wherein, wTemplateValue[x][y] is the weight of the midpoint (x, y) of the first component block, weightIdxL is the second parameter of the midpoint (x, y) of the first component block, also known as the weight index under the first component (e.g., brightness component), wTemplateValue[x][y] is the weight of the midpoint (x, y) of the first component block, partFlip is an intermediate variable, determined according to the angle index angleIdx, such as described above: partFlip=(angleIdx>=13&&angleIdx<=27)? 0:1, that is, the value of partFlip is 1 or 0, when partFlip is 0, weightIdxL is 32-weightIdx, when partFlip is 1, weightIdxL is 32+weightIdx, it should be noted that 32 here is only an example, and the present application is not limited to this. Mode 2: determining the weight of the pixel in the first component block according to the first parameter, the first threshold and the second threshold of the pixel in the first component block. In order to reduce the computational complexity of the weight of the first component block, in method 2, the weight of the pixel points in the first component block is limited to the first threshold or the second threshold, that is, the weight of the pixel points in the first component block is either the first threshold or the second threshold, thereby reducing the computational complexity of the weight of the first component block. The present application does not limit the specific values ​​of the first threshold and the second threshold. Optionally, the first threshold is 1. Optionally, the second threshold is 0. In one example, the weight of the pixel in the first component block may be determined by the following formula: wTemplateValue[x][y]=(partFlip?weightIdx:-weightIdx)>0?1:0 Among them, wTemplateValue[x][y] is the weight of the midpoint (x, y) of the first component block, and the 1 in the above "1:0" is the first threshold and 0 is the second threshold. In the above-mentioned method 1, the weight of each point in the first component block is determined by the weight derivation mode, and the weight matrix composed of the weight of each point in the first component block is used as the weight of the first component block. According to the above method, after determining the weight of the first component block corresponding to the weight derivation mode included in the second combination, the first component block is predicted using the K prediction modes in the second combination to obtain K prediction values, and the K prediction values ​​are weighted according to the weight of the first component block to obtain the prediction value of the first component block. The predicted value of the first component block may be understood as a matrix composed of the predicted values ​​of the pixels in the first component block. In some embodiments, the above-mentioned prediction value is also referred to as a prediction sample. Next, the cost of the second combination is determined according to the predicted value and the reconstructed value of the first component block. The above-mentioned methods for determining the cost of the second combination include but are not limited to the following: Method 1, using a matrix method to determine the cost of the second combination. Specifically, a loss is determined according to the predicted value and the reconstructed value of the first component block, and the loss is recorded as the first loss. Since the predicted value and the reconstructed value of the first component block are matrices, the first loss is also a matrix. For example, the absolute value of the difference between the predicted value and the reconstructed value of the first component block is determined as the first loss, and the first loss is determined as the cost of the second combination. Method 2: Use point-by-point calculation to determine the cost of the second combination. Specifically, for the i-th pixel in the first component block, when determining the prediction of each prediction mode in the K prediction modes in the second combination at the i-th pixel, determine the weight of the first component block corresponding to the i-th pixel in the first component block weight, and obtain the prediction value of the i-th pixel according to the first component block weight of the i-th pixel and the K prediction values ​​of the i-th pixel. According to the prediction value and the reconstruction value of the i-th pixel, obtain the cost of the second combination at the i-th pixel. According to this method, the prediction distortion cost of the second combination at each pixel in the first component block can be determined, and finally, the cumulative sum of the prediction distortion costs of the second combination at each pixel in the first component block is determined as the cost of the second combination. According to the above method, the cost of each second combination in the R second combinations can be determined. Next, a candidate combination list is constructed according to the cost of each second combination in the R second combinations. For example, according to the cost of the second combination, the R second combinations are sorted in ascending order, and the sorted R second combinations are determined as the candidate combination list. For another example, according to the cost of the second combination, N second combinations with the smallest cost are selected from the R second combinations to form a candidate combination list. Optionally, N is 8 or 16 or 32, etc. According to the above method, a candidate combination list is determined, in which the candidate combinations are sorted in ascending order according to the size of the cost. Exemplarily, the candidate combination list is shown in Table 6 above. In this way, the decoding end searches for the candidate combination corresponding to the first index in the candidate combination list shown in Table 6 according to the first index, and determines the candidate combination corresponding to the first index as the first combination, that is, determines the weight derivation mode included in the candidate combination as the first weight derivation mode, and determines the K prediction modes included in the candidate combination as K first prediction modes. In the above embodiment, the method of constructing the candidate combination is introduced by taking the first combination including the first weight derivation mode and K first prediction modes as an example. In the embodiment of the present application, in case 1, the first combination includes the first weight derivation mode and K first prediction modes, and the first weight derivation mode does not include a transition parameter (blending parameter). In case 2, the first combination includes the first weight derivation mode, K first prediction modes, and a second transition parameter. In case 3, the first combination includes the first weight derivation mode and K first prediction modes, and the first weight derivation mode includes a transition parameter. The transition parameter is used together with the K first prediction modes to determine the prediction value of the current component block. For case 1, when the first combination includes the first weight derivation mode and K first prediction modes, and the first weight derivation mode does not include transition parameters, the candidate combination list corresponding to the current component block is constructed as described in the above embodiment. Case 2: The first combination includes the first weight derivation mode, K first prediction modes and the second transition parameter. As shown in Figures 4 and 5 above, there is a transition area near the weight dividing line, that is, the gray area in Figures 4 and 5, and the transition area corresponds to a transition parameter, that is, the transition parameter is used to represent the transition area in the weight map. In some cases, the weight can be affected by the transition parameter. Therefore, in an embodiment of the present application, the predicted value of the current component block is determined based on the second transition parameter, the first weight derivation mode and the K first prediction modes. At this time, the first combination of the embodiment of the present application includes the first weight derivation mode, the K first prediction modes and the second transition parameter. In this case 2, determining the first combination in S101 includes the following steps: S101-C, decoding the bitstream, determining a candidate combination list, the candidate combination list including at least one candidate combination, any candidate combination in the at least one candidate combination including a weight derivation mode, K prediction modes and a transition parameter; S101-D. Determine a first combination according to the candidate combination list. Exemplarily, the candidate combination list is shown in Table 8: Table 8 As shown in Table 8, the candidate combination list includes at least one candidate combination, any two of which are not completely the same, that is, at least one of the weight derivation mode, K prediction modes and transition parameters included in any two candidate combinations is different. Illustratively, in the above Table 8, the ranking of the candidate combinations in the candidate combination list is used as the index. Optionally, the index of the candidate combination in the candidate combination list may also be reflected in other ways, which is not limited in the embodiment of the present application. In this embodiment, the decoding end determines the first combination according to the candidate combination list in the following ways, including but not limited to: In mode 1, the candidate combination list includes one candidate combination. In this case, the candidate combination included in the candidate combination list is determined as the first combination. Mode 2: The candidate combination list includes multiple candidate combinations. At this time, the code stream is decoded to obtain a first index, and the first index is used to indicate the first combination; the candidate combination corresponding to the first index in the candidate combination list is determined as the first combination. In the method 2, the decoding end decodes the code stream to obtain the first index, and determines a candidate combination list as shown in the above Table 8, and searches the candidate combination list according to the first index to obtain the first combination indicated by the first index. For example, the first index is index 1, and in the candidate combination list shown in Table 8, the candidate combination corresponding to index 1 is candidate combination 2, that is, the first combination indicated by the first index is candidate combination 2. In this way, the decoding end determines the weight derivation mode, K prediction modes and transition parameters included in candidate combination 2 as the first weight derivation mode, K first prediction modes and second transition parameters included in the first combination, and uses the first weight derivation mode, the second transition parameters and the K first prediction modes to predict the current component block to obtain a predicted value of the current component block. In this mode 2, the encoder and the decoder can respectively determine the same candidate combination list, for example, the encoder and the decoder both determine a list including L candidate combinations, each candidate combination including 1 weight derivation mode, K prediction modes and 1 transition parameter. In the bitstream, the encoder only needs to write a candidate combination finally selected, for example, the first combination, and the decoder parses the first combination finally selected by the encoder, specifically, the decoder decodes the bitstream, obtains the first index, and determines the first combination in the candidate combination list determined by the decoder through the first index. The specific process of determining the candidate combination list in the above S101-C is introduced below. In some embodiments, the candidate combination list is already available. After obtaining the first index by decoding the code stream, the decoding end can obtain or read the candidate combination list according to the first index, and then query the candidate combination corresponding to the first index in the candidate combination list according to the first index. In some embodiments, the candidate combination list is sent from the encoding end to the decoding end, for example, the encoding end sends it to the decoding end before encoding the current component block. In some embodiments, the candidate combination list is uploaded to the cloud by the encoding end, and the decoding end reads the candidate combination list from the cloud. In some embodiments, the candidate combination list is constructed by the decoding end. The embodiment of the present application does not limit the way in which the decoding end constructs the candidate combination list. For example, the information related to the current component block is used to analyze the probability of occurrence of each combination composed of different weight derivation modes, different prediction modes and different transition parameters, and the candidate combination list is constructed according to the probability of occurrence of each combination. Optionally, the information related to the current component block includes pattern information of surrounding blocks of the current component block, reconstructed pixels of a first component block corresponding to the current component block, and the like. In some embodiments, the decoding end constructs a candidate combination list through the following steps S101-C1 and S101-C2: S101-C1, decoding a bit stream, and determining a first component block corresponding to a current component block; S101-C2. Construct a candidate combination list based on the first component block. The specific implementation process of S101-C1 refers to the description of S101-A1 above and will not be repeated here. Since the first component block corresponding to the current component block is correlated with the current component block, based on this, the embodiment of the present application constructs a candidate combination list of the current component block based on the first component block. For example, for each combination, the first component block is predicted using the combination to obtain the predicted value of the first component block under each combination, and a candidate combination list is constructed according to the predicted value of the first component block under each combination. For example, the weight of the first component block is derived using the weight derivation mode included in the combination, and the first component block is predicted using the K prediction modes included in the combination to obtain K predicted values ​​of the first component block, and the K predicted values ​​of the first component block are weighted according to the derived weight of the first component block to obtain the predicted value of the first component block under the combination. Finally, a candidate combination list is constructed according to the predicted value of the first component block under each combination. It should be noted that the weight derived according to the weight derivation mode can be understood as the weight corresponding to each pixel in the first component block, or as the weight matrix corresponding to the first component block. Using the transition parameter to adjust the weight of the first component block can be understood as adjusting the weight corresponding to each pixel in the first component block, or adjusting the weight matrix of the first component block. Wherein, when determining the predicted value of the first component block based on the adjusted weight of the first component block, it can be determined that the K predicted values ​​corresponding to each pixel in the first component block, and the predicted value corresponding to each pixel is determined according to the K predicted values ​​corresponding to each pixel and the adjusted weight, and the predicted value corresponding to each pixel in the first component block constitutes the predicted value of the first component block. Optionally, when determining the predicted value of the first component block based on the adjusted weight, it can also be performed according to the block, for example, the predicted value of the first component block is determined, and the K predicted values ​​of the first component block are weighted according to the adjusted weight matrix of the first component block to obtain the predicted value of the first component block. In some embodiments, S101-C2 includes the following steps S101-C21 to S101-C23: S101-C21, determine R second combinations, any second combination of the R second combinations includes a weight derivation mode, K prediction modes and a transition parameter, and the weight derivation mode, K prediction modes and transition parameters included in any two combinations of the R second combinations are not completely the same, and R is a positive integer greater than 1. S101-C22. For any second combination among the R second combinations, determine a cost corresponding to the second combination when predicting the first component block using the weight derivation mode, K prediction modes and transition parameters in the second combination. S101-C23. Construct a candidate combination list according to the cost corresponding to each second combination in the R second combinations. In this embodiment, when constructing a candidate combination list, the decoding end first determines R second combinations. The present application does not limit the specific values ​​of the R second combinations, such as 8, 16, 32, etc. Each of the R second combinations includes a weight derivation mode, K prediction modes and a transition parameter, and the weight derivation mode, K prediction modes and transition parameters included in any two of the R second combinations are not completely the same. Then, for each of the R second combinations, determine the cost corresponding to the second combination when the weight derivation mode, K prediction modes and transition parameters included in the second combination are used to predict the first component block. Finally, construct a candidate combination list based on the cost corresponding to each of the R second combinations. In some embodiments, when determining in S101-C22 to use the weight derivation mode, K prediction modes and transition parameters in the second combination to predict the first component block, the cost corresponding to the second combination includes at least the following methods: Mode 1, S101-C22 includes the following S101-C22-11 to S101-C22-14: S101-C22-11, determining the weight of the first component block according to the weight derivation mode and transition parameters included in the second combination; S101-C22-12, predicting the first component block according to the K prediction modes in the second combination to obtain K prediction values ​​of the first component block; S101-C22-13, weighting the K prediction values ​​of the first component block according to the weight of the first component block to obtain a prediction value of the first component block corresponding to the second combination; S101-C22-14. Determine a cost corresponding to the second combination according to the predicted value of the first component block corresponding to the second combination and the reconstructed value of the first component block. In the embodiment of the present application, the process of determining the cost corresponding to each second combination in the R second combinations is consistent. For the convenience of description, one second combination in the R second combinations is taken as an example for description. In the embodiment of the present application, the second combination includes a weight derivation mode, a transition parameter and K prediction modes. When the second combination is used to predict the first component block, the weight of the first component block is determined according to the weight derivation mode and transition parameter included in the second combination, and the first component block is predicted according to the K prediction modes included in the second combination to obtain K prediction values ​​of the first component block. Then, the K prediction values ​​of the first component block are weighted using the weight of the first component block to obtain the prediction value of the first component block corresponding to the second combination. Then, the cost corresponding to the second combination is determined according to the prediction value of the first component block corresponding to the second combination and the reconstruction value of the first component block. In the embodiment of the present application, the transition parameter is used to adjust the weight derived by the weight derivation mode. Therefore, in the embodiment of the present application, in the above S101-C22-11, according to the weight derivation mode and the transition parameter included in the second combination, the implementation method of determining the weight of the first component block includes at least the following: Example 1: When using the first weight derivation mode to derive the weight of the first component block, it is necessary to determine multiple intermediate variables, and the transition parameters can be used to adjust one or several of the multiple intermediate variables, and then the adjusted variables are used to derive the weight of the first component block. For example, the transition parameters are used to adjust one or several of the variables such as displacementX, displacementY, partFlip, shiftHoroffsetX, offsetY, xL, yL, etc. to obtain the weight of the first component block. Example 2: According to the weight derivation mode in the second combination and the first component block, determine the third weight corresponding to the first component block, use the transition parameter in the second combination to adjust the third weight to obtain the adjusted third weight; determine the weight of the first component block according to the adjusted third weight. For example, according to the weight derivation mode in the second combination and the first component block, the third weight corresponding to the first component block is determined to be weightIdx, and then, weightIdx is adjusted using the transition parameter to obtain the adjusted weightIdx, and then, according to the adjusted weightIdx, the weight wVemplateValue of the first component block is determined. In one example, weightIdx may be adjusted using a transition parameter according to the following formula to obtain an adjusted weightIdx: weightIdx=weightIdx*blendingCoeff Wherein, blendingCoeff is the transition parameter included in the second combination. For another example, according to the weight derivation mode in the second combination and the first component block, the third weight corresponding to the first component block is determined to be wVemplateValue, and then the wVemplateValue is adjusted using the transition parameter to obtain the adjusted wVemplateValue, and the adjusted wVemplateValue is used to determine the weight of the first component block. In one example, the wVemplateValue may be adjusted using the transition parameter according to the following formula to obtain the adjusted wVemplateValue: wVemplateValue=wVemplateValue*blendingCoeff According to the above method, the weight of the first component block corresponding to each of the R second combinations can be determined. Then, for each second combination, the K prediction modes included in the second combination are used to predict the first component block to obtain K prediction values ​​of the first component block, and the weight of the first component block corresponding to the second combination is used to perform weighted processing on the K prediction values ​​of the first component block corresponding to the second combination to obtain the prediction value of the first component block corresponding to the second combination, and the cost corresponding to the second combination is determined according to the prediction value of the first component block corresponding to the second combination and the reconstruction value of the first component block. Among them, the method for determining the cost corresponding to the second combination includes but is not limited to SAD, SATD, SEE, etc. Referring to this method, the cost corresponding to each of the R second combinations can be determined. Then, according to the cost corresponding to each of the R second combinations, a candidate combination list is constructed. Mode 2, S101-C22 includes the following S101-C22-11 to S101-C22-14: S101-C22-21, determining the prediction values ​​of the first component blocks respectively corresponding to the K prediction modes in the second combination according to the weight derivation mode and the transition parameter in the second combination; S101-C22-22, determining costs corresponding to the K prediction modes in the second combination according to the prediction values ​​of the first component blocks respectively corresponding to the K prediction modes in the second combination and the reconstruction values ​​of the first component blocks; S101-C22-23, determine the cost corresponding to the second combination according to the costs corresponding to the K prediction modes in the second combination. For example, determine the sum of the costs corresponding to the K prediction modes in the second combination as the cost corresponding to the second combination. For example, assuming that K=2, the two prediction modes included in the second combination are respectively recorded as prediction mode 1 and prediction mode 2. First, according to the weight derivation mode and transition parameters included in the second combination, the weight and prediction value of the first component block corresponding to prediction mode 1 are determined, and the prediction value corresponding to prediction mode 1 is processed using the weight of the first component block corresponding to prediction mode 1. For example, for each pixel in the first component block corresponding to prediction mode 1, the prediction value of the pixel in the first component block corresponding to prediction mode 1 is multiplied by the weight of the first component block corresponding to the pixel to obtain the prediction value of the pixel. In this way, the prediction value of the first component block corresponding to prediction mode 1 can be determined. Then, according to the prediction value of the first component block corresponding to prediction mode 1 and the reconstruction value of the first component block, the cost corresponding to prediction mode 1 is determined, wherein the method for determining the cost corresponding to prediction mode 1 includes but is not limited to SAD, SATD, SEE, etc. Similarly, the cost corresponding to prediction mode 2 can be determined. Then, according to the cost corresponding to prediction mode 1 and the cost corresponding to prediction mode 2, the cost corresponding to the second combination is determined. For example, the cost corresponding to prediction mode 1 and the cost corresponding to prediction mode 2 are added together to determine the cost corresponding to the second combination. The manner of constructing the candidate combination list according to the cost corresponding to each second combination in the R second combinations in the above S101-C23 can refer to the description of the above S101-A23, which will not be repeated here. The process of determining the R second combinations in the above S101-C21 is introduced below. In some embodiments, the above R second combinations are preset. In some embodiments, S101-C21 includes the following steps: S101-C21-1. Determine F weight derivation modes, J prediction modes, and W transition parameters, where F and W are both positive integers, and J is a positive integer greater than or equal to K; S101-C21-2. Construct R second combinations based on F weight derivation modes, J prediction modes and W transition parameters, wherein any second combination of the R second combinations includes a weight derivation mode among the F weight derivation modes, K prediction modes among the J prediction modes and a transition parameter among the W transition parameters. In this embodiment, the decoding end first determines F weight derivation modes, J prediction modes and W transition parameters, and then constructs R second combinations based on the determined F weight derivation modes, J prediction modes and W transition parameters. The embodiment of the present application does not limit the specific number of the above-mentioned F weight derivation modes, J prediction modes and W transition parameters. Assume that K=2, the above K prediction modes include the first prediction mode and the second prediction mode, assume that there are J types of all available prediction modes, and the first prediction mode has J possibilities. Since the second prediction mode is different from the first prediction mode, the second prediction mode has J-1 types. Assume that there are F types of weight derivation modes, and assume that there are W types of transition gradient coefficients. Then the present application may use any two different prediction modes, any weight derivation mode, and any transition gradient coefficient to form a second combination, with a total of F*J*(J-1)*W possible second combinations. In this implementation, F weight derivation modes are all possible weight derivation modes, J prediction modes are all possible prediction modes, and W transition parameters are all possible transition parameters, and an exhaustive method is used to obtain all possible second combinations. Each second combination of all possible second combinations is used to predict the first component block corresponding to the current component block, and the distortion cost of each second combination is calculated, and then according to the distortion cost of each second combination, a candidate combination list corresponding to the current component block is obtained. In some embodiments, in order to reduce the amount of data and increase the speed of building the candidate combination list, not every prediction mode is tried, but some of the prediction modes may be selected for trying. At this time, the implementation methods of determining the J prediction modes in the above S101-C21-1 include but are not limited to the following methods: Method 1: J prediction modes are preset prediction modes. Method 2: Determine a candidate prediction mode list of the current component block, a candidate prediction mode list corresponding to the K first prediction modes, a prediction mode corresponding to the weighted derivative mode, and at least one of the preset modes; and determine J prediction modes based on the candidate prediction mode list, the alternative prediction mode list corresponding to the K first prediction modes, the prediction mode corresponding to the weighted derivative mode, and at least one of the preset modes. The method of determining the candidate prediction mode list of the current component block includes at least the following examples: Example 1: Determine a candidate prediction mode list according to a prediction mode used by at least one block adjacent to the current component block. Example 2: if the candidate prediction mode list does not include the preset mode, determining the preset mode corresponding to the current component block; and adding the preset mode to the candidate prediction mode list. In an example, the above-mentioned preset modes are several preset prediction modes. In another example, the preset mode is determined by determining the image type corresponding to the current component block and according to the image type corresponding to the current component block. For example, if the image type corresponding to the current component block is B type or P type, the preset mode includes at least one of DC, a horizontal mode, a vertical mode and an angle mode. Example 3, determine the image type corresponding to the current component block, and determine the candidate prediction mode list according to the image type corresponding to the current component block. For example, if the image type corresponding to the current component block is B type or P type, then DC, at least one of the horizontal mode, vertical mode and some angle modes can be added to the second candidate prediction mode list. For another example, if the image type corresponding to the current component block is I type, then DC, at least one of the horizontal mode and vertical mode can be added to the candidate prediction mode list. Example 4, determining at least one of the second prediction mode used by the first component block at a preset position, at least one component block among the second component block and the third component block (for example, a chroma block and / or a luminance block), the third prediction mode used by the decoded first component block, the second component block and at least one component block among the third component block (for example, a luminance block and / or a chroma block) around the current component block, the fourth prediction mode used by the first component block (for example, a luminance block) corresponding to the internal preset area of ​​the current component block, and the fifth prediction mode related to the first component block corresponding to the current component block; and determining a candidate prediction mode list for the current component block based on at least one of the second prediction mode, the third prediction mode, the fourth prediction mode and the fifth prediction mode. In the embodiment of the present application, the specific implementation of the above determination of J prediction modes can refer to the specific description of determining Q prediction modes in the above S101-A21-1, which will not be repeated here. In some embodiments, the above J is equal to Q. The following is an introduction to the process of determining F weight derivation modes in S101-C21-1. In the embodiment of the present application, the method of determining F weight derivation modes includes at least the following methods: In some embodiments, the above-mentioned F weight derivation modes are preset weight derivation modes. In some embodiments, F weight derivation modes are selected from a preset Z weight derivation modes, where Z is a positive integer greater than or equal to F. The embodiment of the present application does not limit the above-mentioned preset Z weight derivation modes. In some embodiments, if Z is equal to F, the Z weight derivation modes are determined as F weight derivation modes. In some embodiments, if Z is greater than F, in order to further reduce the number of R second combinations, the preset Z weight derivation modes are screened, and then F weight derivation modes can be selected from the preset Z weight derivation modes to construct R second combinations. The process of determining F weight derivation modes in the above S101-C21-1 is basically the same as the process of determining P weight derivation modes in the above S101-A21-1. Please refer to the specific description of determining P weight derivation modes above, which will not be repeated here. The process of determining W transition gradient coefficients in S101-C21-1 is introduced below. In some embodiments, the W transition parameters are preset transition parameters, such as 1 / 4, 1 / 2, 1, 2, 4, etc. In some embodiments, W transition parameters are determined according to the size of the current component block. For example, if the size of the current component block is less than a preset value, the W transition parameters are located in a transition parameter value range 1. For another example, if the size of the current component block is less than a preset value, the W transition parameters are located in a transition parameter value range 2. The transition parameter value range 1 may intersect with the transition parameter value range 2, or may not intersect. In some embodiments, W transition parameters are determined from a plurality of preset transition parameters. In an example, W transition parameters are determined from a plurality of preset transition parameters according to the image information of the current component block. The embodiment of the present application does not limit the specific content of the image information of the current component block, such as blurriness, clarity, sharpness, etc. In some embodiments, if the image information of the current component block includes the clarity of the image edge, W transition parameters are determined from a plurality of preset transition parameters according to the image information of the current component block, including two examples: Example 1: If the clarity of the image edge of the current component block is less than a preset value, at least one first-type transition parameter among a plurality of preset transition parameters is determined as W transition parameters. The first type of transition parameter may be understood as a transition parameter that may form a wider transition region, such as 1 / 4, 1 / 2, and the like. Example 2: If the clarity of the image edge of the current component block is greater than or equal to the preset value, at least one second-type transition parameter among multiple preset transition parameters is determined as W transition parameters, and the second-type transition parameter is greater than the first-type transition parameter. The second type of transition parameters may be understood as transition parameters that may form a narrower transition region, such as 2, 4, and the like. In the embodiment of the present application, the method of determining the image information of the current component block may include at least two methods: Mode 1, the image information of the current component block is obtained by decoding the bitstream. For example, the encoding end encodes the image information of the current component block into the bitstream, so that the decoding end obtains the image information of the current component block by decoding the bitstream. Mode 2, determining the image information of the first component block; determining the image information of the current component block based on the image information of the first component block. Since the first component block has been decoded, the image information of the first component block is available, for example, the reconstructed value of the first component block is analyzed to obtain the image information of the first component block. Then, based on the image information of the first component block, the image information of the current component block is obtained. For example, the image information of the first component block is determined as the image information of the current component block, or the image information of the first component block is processed to obtain the image information of the current component block. After the decoding end determines J prediction modes, F weight derivation modes and W transition parameters according to the above steps, R different second combinations are formed according to the J prediction modes, F weight derivation modes and W transition parameters. Then, a candidate combination list is determined according to the R second combinations, and then the first weight derivation mode, K first prediction modes and second transition parameters are determined from the candidate combination list. In some embodiments, in order to further improve the speed of constructing the candidate combination list, the decoding end screens the J prediction modes, F weight derivation modes and W transition parameters determined above again. At this time, the above S101-C21-2 forms R second combinations according to the determined F weight derivation modes, J prediction modes and W transition parameters, including the following steps S101-C21-21 to S101-C21-24: S101-C21-21. Select E weight derivation modes from F weight derivation modes, where E is a positive integer less than or equal to F. Specifically, the weight derivation patterns with a low probability of occurrence are eliminated from the F weight derivation patterns determined above to obtain E screened weight derivation patterns. The methods for selecting E weight derivation modes from F weight derivation modes in S101-C21-21 above include but are not limited to the following: Method 1, for the i-th weight derivation mode among F weight derivation modes, determine the weights of K second prediction modes on the first component block according to the i-th weight derivation mode and the fourth transition parameter, the fourth transition parameter is any transition parameter in the W transition gradients, the K second prediction modes are any K prediction modes among the J prediction modes, and i is a positive integer from 1 to F; if the weight of any prediction mode among the K prediction modes on the first component block is less than a first preset value, the i-th weight derivation mode is eliminated from the F weight derivation modes to obtain E weight derivation modes. In the first mode, the weights of the K second prediction modes on the first component block are determined according to the i-th weight derivation mode and the fourth transition parameter, including at least the following examples: Example 1: When using the i-th weight derivation mode to derive the weight of the first component block, it is necessary to determine multiple intermediate variables. The fourth transition parameter can be used to adjust one or several of the multiple intermediate variables, and then the adjusted variables are used to derive the weight of the first component block. Example 2: Determine the fourth weight corresponding to the first component block based on the i-th weight derivation mode and the first component block; use the fourth transition parameter to adjust the fourth weight to obtain the adjusted fourth weight; and determine the weights of the K second prediction modes on the first component block based on the adjusted fourth weight. For example, according to the i-th weight derivation mode and the first component block, the fourth weight corresponding to the first component block is determined to be weightIdx, then, weightIdx is adjusted using the fourth transition parameter to obtain the adjusted weightIdx, and then, according to the adjusted weightIdx, the weight wVemplateValue of the first component block is determined. In an example, weightIdx may be adjusted using the fourth transition parameter according to the following formula to obtain adjusted weightIdx: weightIdx=weightIdx*blendingCoeff3 Among them, blendingCoeff3 is the fourth transition parameter. For another example, according to the i-th weight derivation mode and the first component block, the fourth weight corresponding to the first component block is determined to be wVemplateValue, and then the wVemplateValue is adjusted using the fourth transition parameter to obtain the adjusted wVemplateValue, and the adjusted wVemplateValue is determined as the weight of the first component block. In an example, the fourth transition parameter may be used to adjust wVemplateValue according to the following formula to obtain the adjusted wVemplateValue: wVemplateValue=wVemplateValue*blendingCoeff3 According to the above method, the weights of the K second prediction modes on the first component block are derived according to the i-th weight. Method 2, for the i-th weight derivation mode among F weight derivation modes, determine the cost of using the i-th weight derivation mode to predict the first component block, where i is a positive integer from 1 to F; according to the cost corresponding to the i-th weight derivation mode, select E weight derivation modes from the F weight derivation modes. In some embodiments, when determining the cost corresponding to the above-mentioned i-th weight derivation mode, the influence of the transition parameter on the weight is not considered. In some embodiments, when determining the cost corresponding to the above-mentioned i-th weight derivation mode, the influence of the transition parameter on the weight is included, that is, the weight of the first component block is determined according to the i-th weight derivation mode and the transition parameter, and then the prediction value of the first component block is determined according to the weight of the first component block and the K prediction values ​​of the first component block, and the cost corresponding to the i-th weight derivation mode is determined according to the prediction value and the reconstruction value of the first component block. The specific process of determining the weight of the first component block according to the i-th weight derivation mode and the transition parameter can refer to the description of the above-mentioned embodiment, which will not be repeated here. In some embodiments, the same method of selecting S weight derivation modes from P weight derivation modes as in the above S101-A11-21 can be used to select E weight derivation modes from F weight derivation modes. Please refer to the description of the above embodiment for details and will not repeat them here. According to the above steps, after the decoding end selects E weight derivation modes from F weight derivation modes, the following steps S101-C21-22 are performed. S101-C21-22. Select V prediction modes from J prediction modes, where V is a positive integer less than or equal to J. The embodiment of the present application does not limit the method of selecting V prediction modes from J prediction modes. In some embodiments, preset V prediction modes are selected from the J prediction modes. In some embodiments, for the i-th prediction mode among J prediction modes, the decoding end determines the cost of using the i-th prediction mode to predict the first component block, where i is a positive integer from 1 to J; based on the cost corresponding to the i-th prediction mode, V prediction modes are selected from the J prediction modes. In an embodiment of the present application, the weight derivation mode, K prediction modes and transition parameters are taken as a combination to calculate the cost. In this way, for the convenience of calculation, the costs of J weight derivation modes are calculated based on a given weight derivation mode, other K-1 prediction modes and transition parameters. That is, the J prediction modes are respectively combined with the set weight derivation mode, K-1 prediction modes and transition parameters to obtain J combinations, and the cost corresponding to each of the J combinations is calculated to obtain the costs of the J prediction modes. According to the above method, after the cost corresponding to the i-th prediction mode among the J prediction modes is determined, V prediction modes are selected from the J prediction modes according to the cost corresponding to the i-th prediction mode. The decoding end selects V prediction modes from J prediction modes according to the cost corresponding to the i-th prediction mode in the following manner: In the first way, if the cost corresponding to the ith prediction mode is less than the fourth preset value, a prediction mode similar to the ith prediction mode is selected from the J prediction modes; and V prediction modes are determined according to the ith prediction mode and the similar prediction modes of the ith prediction mode. Among them, the prediction mode similar to the ith prediction mode can be understood as a prediction mode whose prediction result is similar (or close) to the prediction reception of the ith prediction mode, such as a prediction mode whose prediction direction (or angle) is close to the prediction direction (or angle) of the ith prediction mode, or a prediction mode whose prediction mode index is close to the index of the ith prediction mode, such as a prediction mode whose index is 1, 2, etc. larger than the index of the ith prediction mode, or a prediction mode whose index is 1, 2, etc. smaller than the index of the ith prediction mode. The second method is that if the cost corresponding to the i-th prediction mode is greater than the fifth preset value, the i-th prediction mode and the similar prediction mode of the i-th prediction mode are eliminated from the J prediction modes to obtain at least one prediction mode after elimination; V prediction modes are determined based on the at least one prediction mode after elimination. According to the above steps, E weight derivation modes are selected from F weight derivation modes, and V prediction modes are selected from J prediction modes. Then, the following S101-C21-23 are executed. S101-C21-23. Select O transition parameters from W transition parameters, where O is a positive integer less than or equal to W. In some embodiments, if O is equal to W, the W transition parameters are determined as O transition parameters. In some embodiments, if W is greater than O, W transition parameters are screened to obtain O transition parameters. The method of screening the W transition parameters to obtain the O transition parameters includes at least the following: Example 1: Determine the cost of each transition parameter among W transition parameters, and select the top O transition parameters with the smallest cost among the W transition parameters. For example, for the i-th transition parameter among the W transition parameters, the i-th transition parameter is combined with the weight derivation mode 1, the prediction mode 1 and the prediction mode 2 to form a combination, and the combination is used to predict the first component block to obtain the predicted value of the first component block. Exemplarily, a weight is determined according to the weight derivation mode 1, and the weight is adjusted using the i-th transition parameter to obtain the adjusted weight. The first component block is predicted using the prediction mode 1 and the prediction mode 2 respectively to obtain two predicted values ​​of the first component block, and the two predicted values ​​are weighted using the adjusted weight to obtain the predicted value of the first component block corresponding to the i-th transition parameter. Then, the cost corresponding to the i-th transition parameter is determined according to the reconstructed value of the first component block and the predicted value of the first component block corresponding to the i-th transition parameter. Referring to the above method, the cost corresponding to the combination of the weight derivation mode 1, the prediction mode 1 and the prediction mode 2 for each transition parameter among the W transition parameters can be determined, and then according to the cost, O transition parameters are screened out from the W transition parameters. For example, O transition parameters with the smallest cost among the W transition parameters are screened out. Example 2: If the above W transition parameters are not determined by the image information of the current component block, the embodiment of the present application can also determine the image information of the current component block; and determine O transition parameters from the W transition parameters based on the image information of the current component block. The embodiment of the present application does not limit the specific content of the image information of the current component block, such as blurriness, clarity, sharpness, etc. In some embodiments, if the image information of the current component block includes the clarity of the image edge, O transition parameters are determined from W transition parameters according to the image information of the current component block, including two examples: In an example, if the clarity of the image edge of the current component block is less than a preset value, at least one first-category transition parameter among the W transition parameters is determined as O transition parameters. In another example, if the clarity of the image edge of the current component block is greater than or equal to the preset value, at least one second-category transition parameter among the W transition parameters is determined as O transition parameters. In some embodiments, the O transition parameters are selected from W transition parameters according to the size of the current component block. In a possible implementation, according to the size of the current component block, transition parameters greater than or equal to the third value among the W transition parameters are used as O transition parameters. For example, if the size of the current component block is smaller than the second set threshold, the transition parameter whose value among the W transition parameters is the third value is used as one of the O transition parameters. For another example, if the size of the current component block is greater than or equal to the second set threshold, the transition parameters less than or equal to the fourth value among the W transition parameters are used as O transition parameters, where the fourth value is less than the third value. The embodiment of the present application does not limit the specific values ​​of the second set threshold, the third value and the fourth value. Optionally, the third value is 1 and the fourth value is 1 / 2. Optionally, if the size of the current component block is represented by the number of pixels of the current component block, the second set threshold is 256, etc. In another possible implementation, the O transition parameters are determined to be at least one transition parameter within a certain value range among the W transition parameters according to the size of the current component block. For example, if the size of the current component block is smaller than the second set threshold, the O transition parameter is determined to be one or more transition parameters among the W transition parameters that are within the value range of the fourth transition parameter. For another example, if the size of the current component block is greater than or equal to the second set threshold, the O transition parameter is determined to be one or more transition parameters among the W transition parameters that are within the third transition parameter value range, where the minimum value of the third transition parameter value range is less than the minimum value of the fourth transition parameter value range. The embodiment of the present application does not limit the specific values ​​of the fourth transition parameter value range and the third transition parameter value range. Optionally, the fourth transition parameter value range and the third transition parameter value range intersect. Optionally, the fourth transition parameter value range and the third transition parameter value range do not intersect. After selecting E weight derivation modes from F weight derivation modes, selecting V prediction modes from J prediction modes, and selecting O transition parameters from W transition parameters, execute the following S101-C21-24. S101-C21-24. Form R second combinations based on E weight derivation modes, V prediction modes and O transition parameters. Specifically, a weight derivation mode is selected from E weight derivation modes, K prediction modes are selected from V prediction modes, and finally a transition parameter is selected from O transition parameters. This weight derivation mode, K prediction modes and one transition parameter constitute a second combination. By repeating this step, R second combinations can be obtained. From the above, it can be seen that a second combination includes a weight derivation mode, K prediction modes and a transition parameter, that is, a second combination includes K+2 elements. In this way, when screening an element, the other elements in a combination can be limited to be fixed, and the possible selection of another element can be limited. The following introduces an implementation process of the above S101-C21-2 by taking the screening process of another prediction mode when the weight derivation mode, transition parameters and one prediction mode are fixed as an example. In some embodiments, the above S101-C21-2 includes: for the fth weight derivation mode among F weight derivation modes, and the oth transition parameter among O transition parameters, determining the cost of using the fth weight derivation mode, the oth transition parameter and the jth prediction mode among J prediction modes to predict the first component block, wherein f is a positive integer less than or equal to F, o is a positive integer less than or equal to O, and j is a positive integer less than or equal to J; if the cost corresponding to the combination of the fth weight derivation mode, the oth transition parameter and the jth prediction mode is greater than a sixth preset value, then eliminating the jth prediction mode and similar prediction modes of the jth prediction mode from the J prediction modes to obtain at least one prediction mode after elimination; constructing R second combinations based on the fth weight derivation mode, the oth transition parameter and at least one prediction mode after elimination. In this embodiment, when the weight derivation mode, transition parameters and one prediction mode are fixed, another prediction mode is screened. For example, if a certain intra-frame prediction mode cannot obtain a relatively small cost as the first prediction mode under a certain weight derivation mode and transition parameters, then an intra-frame prediction mode similar to the intra-frame prediction mode under the weight derivation mode and transition parameters will no longer be tried as the first prediction mode. Specifically, assuming K=2, for the fth weight derivation mode among the F weight derivation modes and the oth transition gradient parameter among the O transition parameters. Assume that the second prediction mode is set to prediction mode 1, and the prediction mode 1 can be one of the J prediction modes, or can be another prediction mode outside the J prediction modes. Determine the possible selection of the first prediction mode from the J prediction modes, specifically, take the jth prediction mode among the J prediction modes as the first prediction mode. At this time, determine the prediction value of the first component block when the combination j consisting of the fth weight derivation mode, the oth transition gradient parameter, the jth prediction mode and the prediction mode 1 predicts the first component block, and determine the cost corresponding to the combination j based on the prediction value, and determine the cost corresponding to the combination j as the cost corresponding to the jth prediction mode. Next, determine whether the cost corresponding to the j-th prediction mode is greater than the sixth preset value. If the cost corresponding to the j-th prediction mode is greater than the sixth preset value, it means that the combination of the j-th prediction mode, the f-th weight derivation mode, the o-th transition gradient parameter and the prediction mode 1 cannot achieve accurate prediction of the first component block. At this time, the j-th prediction mode is eliminated from the J prediction modes. Since the prediction mode similar to the j-th prediction mode has similar characteristics to the j-th prediction mode, the similar prediction mode of the j-th prediction mode is eliminated from the J prediction modes to obtain the eliminated prediction mode set. In the eliminated prediction mode set, a new prediction mode is selected as the new j-th prediction mode, and the above steps are repeated to obtain the final eliminated prediction mode set corresponding to the f-th weight derivation mode and the o-th transition parameter. According to the above steps, the final eliminated prediction mode set corresponding to each weight derivation mode and transition parameter among the F weight derivation modes can be determined, so that R second combinations can be constructed based on the F weight derivation modes and their respective corresponding final eliminated prediction mode sets. It should be noted that the above embodiment shows a method of screening prediction modes in the form of combination. Optionally, any one of the weight derivation modes and transition parameters can also be screened in the form of combination to finally construct R second combinations. After the decoding end determines R second combinations according to the above methods, for any second combination of the R second combinations, the weight derivation mode, transition parameters and K prediction modes in the second combination are used to predict the first component block to obtain the prediction value of the first component block corresponding to the second combination. The following introduces an implementation process of using any second combination to predict the first component block corresponding to the current component block in an embodiment of the present application to obtain a predicted value of the first component block. In the embodiment of the present application, for any second combination, the first component block is predicted according to the weight derivation mode, transition parameters and K prediction modes included in the second combination to obtain a prediction value of the first component block corresponding to the second combination. The embodiment of the present application does not limit the specific implementation method of predicting the first component block according to the weight derivation mode, transition parameters and K prediction modes included in the second combination to obtain the prediction value of the first component block corresponding to the second combination. For example, firstly, according to the weight derivation mode and K prediction modes included in the second combination, a prediction value of the first component block is determined, and then according to the transition parameters and the determined prediction value of the first component block, the prediction value of the first component block corresponding to the second combination is obtained. In some embodiments, the weight derivation mode and transition parameters included in the second combination can be used to determine the weight of the first component block, and then, K first component block prediction values ​​are determined according to the K prediction modes included in the second combination, and the first component block prediction value corresponding to the second combination is determined according to the weight of the first component block and the K first component block prediction values. In some embodiments, determining the weight of the first component block according to the weight derivation mode comprises the following steps: Step 1: Determine the angle index and distance index according to the weight derivation mode; Step 2: Determine the weight of the first component block according to the angle index, the distance index, the transition parameter and the size of the first component block. The present application can derive the weight of the first component block in the same manner as the weight of the derived prediction value. For example, first determine the angle index and distance index according to the weight derivation mode, where the angle index can be understood as the angle index of the dividing line of each weight derived by the weight derivation mode. Exemplarily, the angle index and distance index corresponding to the weight derivation mode can be determined according to Table 2 above. For example, if the weight derivation mode is 27, the corresponding angle index is 12 and the distance index is 3. Then, determine the weight of the first component block according to the angle index, the distance index and the size of the first component block. In the above step 2, the method of determining the weight of the first component block according to the angle index, the distance index and the size of the first component block includes but is not limited to the following methods: Method 1: Determine the weight of the first component block according to the angle index, the distance index, the transition parameter and the size of the first component block. In this case, the above step 2 includes the following steps 21 to 23: Step 21: determining a first parameter of a pixel in the first component block according to the angle index, the distance index and the size of the first component block; Step 22: Determine the weight of the pixel in the first component block according to the first parameter and the transition parameter of the pixel in the first component block; Step 23: Determine the weight of the first component block according to the weights of the pixels in the first component block. In this implementation, the weights of the pixels in the first component block are determined based on the angle index, the distance index, the size of the first component block and the size of the current component block, and then the weight matrix composed of the weights of each point in the first component block is determined as the weight of the first component block. The first parameter of the present application is used to determine the weight. In some embodiments, the first parameter is also referred to as a weight index. In some embodiments, the first parameter may be understood as the third weight corresponding to the first component block and the fourth weight corresponding to the first component block in the above embodiments. In a possible implementation, the offset and the first parameter may be determined in the following manner: The inputs of the first component block weight derivation process are: the width nCbW of the first component block, the height nCbH of the first component block; the "division" angle index variable angleId of GFM; the distance index variable distanceIdx of GFM; the component index variable cIdx, taking the first component block as an example, so cIdx is 0, indicating the brightness component. Among them, the variables nW, nH, shift1, offset1, displacementX, displacementY, partFlip and shiftHor are derived as follows: nW=(cIdx==0)? nCbW:nCbW*EubWidthC nH=(cIdx==0)? nCbH:nCbH*EubHeightC shift1 = Max(5,17-BitDepth) where BitDepth is the bit depth of the codec offset1=1<<(shift1-1) displacementX=angleIdx displacementY=(angleIdx+8)%32 partFlip=(angleIdx>=13&&angleIdx<=27)? 0:1 shiftHor=(angleIdx%16==8||(angleIdx%16!=0&&nH>=nW))? 0:1 Among them, the offsets offsetX and offsetY are derived as follows: – If the value of shiftHor is 0: offsetX=(-nW)>>1 offsetY=((-nH)>>1)+(angleIdx<16?(distanceIdx*nH)>>3:-((distanceIdx*nH)>>3)) – Otherwise (i.e. the value of shiftHor is 1): offsetX=((-nW)>>1)+(angleIdx<16?(distanceIdx*nW)>>3:-((distanceIdx*nW)>>3) offsetY=(-nH)>>1 The weight matrix of the first component block wVemplateValue[x][y] (where x = -nVmW..nCbW–1, y = -nVmH..nCbH-1, excluding the case where x and y are both greater than or equal to 0) Note that in this example, the coordinates of the upper left corner of the first component block are (0, 0) and are derived as follows: – The variables xL and yL are derived as follows: xL=(cIdx==0)? x:x*EubWidthC yL=(cIdx==0)? y:y*EubHeightC Where disLut is determined according to Table 3 above Among them, the first parameter weightIdx is derived as follows: weightIdx=(((xL+offsetX)<<1)+1)*disLut[displacementX]+(((yL+offsetY)<<1)+1)*disLut[displacementY] In some embodiments, according to the above method, after the first parameter weightIdx is determined, the first parameter is then adjusted using the transition parameter to obtain the adjusted first parameter. In one example, the first parameter is adjusted by the following formula: weightIdx=weightIdx*blendingCoeff Among them, blendingCoeff is the transition parameter. Next, according to the adjusted first parameter, the weights of the pixels in the first component block are determined in the following ways, including but not limited to: Method 1, determining the second parameter of the pixel in the first component block according to the adjusted first parameter of the pixel in the first component block; determining the weight of the pixel in the first component block according to the second parameter of the pixel in the first component block. The second parameter is also used to determine the weight. In some embodiments, the second parameter is also called a weight index under the first component, and the first component can be a brightness component, a chrominance component, etc. For example, the weights of the pixels in the first component block are determined according to the formula: weightIdxL=partFlip? 32+weightIdx:32-weightIdx wVemplateValue[x][y]=Clip3(0,8,(weightIdxL+4)>>3) Wherein, wVemplateValue[x][y] is the weight of the midpoint (x, y) of the first component block, weightIdxL is the second parameter of the midpoint (x, y) of the first component block, also known as the weight index under the first component (e.g., brightness component), wVemplateValue[x][y] is the weight of the midpoint (x, y) of the first component block, partFlip is an intermediate variable, determined according to the angle index angleIdx, for example, as described above: partFlip=(angleIdx>=13&&angleIdx<=27)? 0:1, that is, the value of partFlip is 1 or 0, when partFlip is 0, weightIdxL is 32-weightIdx, when partFlip is 1, weightIdxL is 32+weightIdx, it should be noted that 32 here is only an example, and the present application is not limited to this. Mode 2: determining the weight of the pixel in the first component block according to the adjusted first parameter, the first threshold, and the second threshold of the pixel in the first component block. In order to reduce the computational complexity of the weight of the first component block, in method 2, the weight of the pixel points in the first component block is limited to the first threshold or the second threshold, that is, the weight of the pixel points in the first component block is either the first threshold or the second threshold, thereby reducing the computational complexity of the weight of the first component block. The present application does not limit the specific values ​​of the first threshold and the second threshold. Optionally, the first threshold is 1. Optionally, the second threshold is 0. In one example, the weight of the pixel in the first component block may be determined by the following formula: wVemplateValue[x][y]=(partFlip?weightIdx:-weightIdx)>0?1:0 Among them, wVemplateValue[x][y] is the weight of the midpoint (x, y) of the first component block, and the 1 in the above "1:0" is the first threshold and 0 is the second threshold. In the above-mentioned method 1, the weight of each point in the first component block is determined by the weight derivation mode, and the weight matrix composed of the weight of each point in the first component block is used as the weight of the first component block. According to the above method, after determining the weight of the first component block corresponding to the weight derivation mode included in the second combination, the K prediction modes in the second combination are used to predict the first component block to obtain K prediction values, and the K prediction values ​​are weighted according to the weight of the first component block to obtain the prediction value of the first component block. Next, the cost of the second combination is determined according to the predicted value and the reconstructed value of the first component block. According to the above method, the cost of each second combination in the R second combinations can be determined. Next, according to the cost of each second combination in the R second combinations, a candidate combination list as shown in Table 8 is constructed. In this way, the decoding end searches for the candidate combination corresponding to the first index in the candidate combination list shown in Table 8 according to the first index, and determines the candidate combination corresponding to the first index as the first combination, that is, determines the weight derivation mode included in the candidate combination as the first weight derivation mode, determines the K prediction modes included in the candidate combination as K first prediction modes, and determines the transition parameters included in the candidate combination as the second transition parameters. In the above situation 2, the implementation process of the above S101 is introduced by taking the first combination including the first weight derivation mode, K first prediction modes and the second transition parameter as an example. Case 3: The first combination includes the first weight derivation mode and K first prediction modes, and the first weight derivation mode includes a third transition parameter, and the third transition parameter is used to determine the weight. In this case 3, the first weight derivation mode can be understood as a data set, which includes multiple parameters, such as the third transition parameter, and these multiple parameters are used together to determine the weight. In this case 3, determining the first combination in S101 includes the following steps: S101-E, decoding a bitstream, determining a candidate combination list, the candidate combination list including at least one candidate combination, at least any candidate combination in the candidate combination including a weight derivation mode and K prediction modes, wherein the weight derivation mode includes a transition parameter; S101-F. Determine a first combination according to the candidate combination list. Exemplarily, the candidate combination list is shown in Table 9: Table 9 As shown in Table 9, the candidate combination list includes at least one candidate combination, any two of which are not completely the same, that is, at least one of the weight derivation mode and the K prediction modes included in any two candidate combinations is different. Illustratively, in the above Table 9, the ranking of the candidate combinations in the candidate combination list is used as the index. Optionally, the index of the candidate combination in the candidate combination list may also be reflected in other ways, which is not limited in the embodiment of the present application. In this embodiment, the decoding end determines the first combination according to the candidate combination list in the following ways, including but not limited to: In mode 1, the candidate combination list includes one candidate combination. In this case, the candidate combination included in the candidate combination list is determined as the first combination. Mode 2, the candidate combination list includes multiple candidate combinations. At this time, the code stream is decoded to obtain a first index, and the first index is used to indicate the first combination; the candidate combination corresponding to the first index in the candidate combination list is determined as the first combination. In the method 2, the decoding end decodes the code stream to obtain the first index, and determines a candidate combination list as shown in the above Table 9, and searches the candidate combination list according to the first index to obtain the first combination indicated by the first index. For example, the first index is index 1, and in the candidate combination list shown in Table 9, the candidate combination corresponding to index 1 is candidate combination 2, that is, the first combination indicated by the first index is candidate combination 2. In this way, the decoding end determines the weight derivation mode and K prediction modes included in candidate combination 2 as the first weight derivation mode and K first prediction modes included in the first combination, and uses the third transition parameter included in the first weight derivation mode and the K first prediction modes to predict the current component block, and obtains the predicted value of the current component block. The specific process of determining the candidate combination list in the above S101-E is introduced below. In some embodiments, the candidate combination list is already available. After obtaining the first index by decoding the code stream, the decoding end can obtain or read the candidate combination list according to the first index, and then query the candidate combination corresponding to the first index in the candidate combination list according to the first index. In some embodiments, the candidate combination list is sent from the encoding end to the decoding end, for example, the encoding end sends it to the decoding end before encoding the current component block. In some embodiments, the candidate combination list is uploaded to the cloud by the encoding end, and the decoding end reads the candidate combination list from the cloud. In some embodiments, the candidate combination list is constructed by the decoding end. The embodiment of the present application does not limit the way in which the decoding end constructs the candidate combination list. For example, the information related to the current component block is used to analyze the probability of occurrence of each combination composed of different prediction modes and different transition parameters, and the candidate combination list is constructed according to the probability of occurrence of each combination. Optionally, the information related to the current component block includes pattern information of surrounding blocks of the current component block, reconstructed pixels of a first component block corresponding to the current component block, and the like. In some embodiments, the decoding end constructs a candidate combination list through the following steps S101-E1 and S101-E2: S101-E1, decoding a bit stream, and determining a first component block corresponding to a current component block; S101-E2. Construct a candidate combination list based on the first component block. The specific implementation process of S101-E1 refers to the description of S101-A1 above and will not be repeated here. Since the first component block corresponding to the current component block is correlated with the current component block, based on this, the embodiment of the present application constructs a candidate combination list of the current component block based on the first component block. For example, for each combination, the first component block is predicted using the combination to obtain the predicted value of the first component block under each combination, and a candidate combination list is constructed based on the predicted value of the first component block under each combination. For example, the weight of the first component block is derived using the weight derivation mode included in the combination, and the first component block is predicted using the K prediction modes included in the combination to obtain K predicted values ​​of the first component block, and the K predicted values ​​of the first component block are weighted according to the derived weight of the first component block to obtain the predicted value of the first component block under the combination. Finally, a candidate combination list is constructed based on the predicted value of the first component block under each combination. It should be noted that the weight derived according to the weight derivation mode can be understood as the weight corresponding to each pixel in the first component block, or as the weight matrix corresponding to the first component block. Using the transition parameter to adjust the weight of the first component block can be understood as adjusting the weight corresponding to each pixel in the first component block, or adjusting the weight matrix of the first component block. Wherein, when determining the predicted value of the first component block based on the adjusted weight of the first component block, it can be determined that the K predicted values ​​corresponding to each pixel in the first component block, and the predicted value corresponding to each pixel is determined according to the K predicted values ​​corresponding to each pixel and the adjusted weight, and the predicted value corresponding to each pixel in the first component block constitutes the predicted value of the first component block. Optionally, when determining the predicted value of the first component block based on the adjusted weight, it can also be performed according to the block, for example, the predicted value of the first component block is determined, and the K predicted values ​​of the first component block are weighted according to the adjusted weight matrix of the first component block to obtain the predicted value of the first component block. In some embodiments, S101-E2 includes the following steps S101-E21 to S101-E23: S101-E21. Determine R second combinations, any second combination among the R second combinations includes a weight derivation mode and K prediction modes, the weight derivation mode includes a transition parameter, and the weight derivation mode and the K prediction modes included in any two combinations among the R second combinations are not completely the same, and R is a positive integer greater than 1. S101-E22. For any second combination among the R second combinations, determine a cost corresponding to the second combination for predicting the first component block using the weight derivation mode and the K prediction modes in the second combination. S101-E23. Construct a candidate combination list according to the cost corresponding to each second combination in the R second combinations. In this embodiment, when constructing a candidate combination list, the decoding end first determines R second combinations. The present application does not limit the specific values ​​of the R second combinations, such as 8, 16, 32, etc. Each of the R second combinations includes a weight derivation mode and K prediction modes. The weight derivation mode includes a transition parameter, and the weight derivation mode and the K prediction modes included in any two of the R second combinations are not completely the same. Then, for each of the R second combinations, determine the cost corresponding to the second combination when the weight derivation mode and the K prediction modes included in the second combination are used to predict the first component block. Finally, construct a candidate combination list based on the cost corresponding to each of the R second combinations. In some embodiments, when determining in S101-E22 to use the weight derivation mode and K prediction modes in the second combination to predict the first component block, the cost corresponding to the second combination includes at least the following methods: Mode 1, S101-E22 includes the following S101-E22-11 to S101-E22-14: S101-E22-11. Determine the weight of the first component block according to the weight derivation mode included in the second combination; S101-E22-12, predicting the first component block according to the K prediction modes in the second combination to obtain K prediction values ​​of the first component block; S101-E22-13, weighting the K prediction values ​​of the first component block according to the weight of the first component block to obtain a prediction value of the first component block corresponding to the second combination; S101-E22-14. Determine a cost corresponding to the second combination according to the predicted value of the first component block corresponding to the second combination and the reconstructed value of the first component block. In the embodiment of the present application, the process of determining the cost corresponding to each second combination in the R second combinations is consistent. For the convenience of description, one second combination in the R second combinations is taken as an example for description. In the embodiment of the present application, the second combination includes a weight derivation mode and K prediction modes. When the second combination is used to predict the first component block, exemplarily, the decoding end can determine the weight of the first component block according to the weight derivation mode included in the second combination, predict the first component block according to the K prediction modes included in the second combination, obtain K prediction values ​​of the first component block, and then use the weight of the first component block to perform weighted processing on the K prediction values ​​of the first component block to obtain the prediction value of the first component block corresponding to the second combination. Then, according to the prediction value of the first component block corresponding to the second combination and the reconstruction value of the first component block, the cost corresponding to the second combination is determined. The embodiment of the present application does not limit the specific method of determining the weight of the first component block according to the weight derivation mode included in the second combination in the above S101-E22-11. For example, the weight derivation mode in the second combination includes a transition parameter, and therefore, the weight of the first component block can be determined according to the transition parameter. Mode 2, S101-E22 includes the following S101-E22-11 to S101-E22-14: S101-E22-21, determining, according to the weight derivation mode in the second combination, prediction values ​​of the first component blocks respectively corresponding to the K prediction modes in the second combination; S101-E22-22, determining costs corresponding to the K prediction modes in the second combination according to the predicted values ​​of the first component blocks respectively corresponding to the K prediction modes in the second combination and the reconstructed values ​​of the first component blocks; S101-E22-23, determine the cost corresponding to the second combination according to the costs corresponding to the K prediction modes in the second combination. For example, determine the sum of the costs corresponding to the K prediction modes in the second combination as the cost corresponding to the second combination. For example, assuming that K=2, the two prediction modes included in the second combination are respectively recorded as prediction mode 1 and prediction mode 2. First, according to the weight derivation mode included in the second combination, the weight and prediction value of the first component block corresponding to prediction mode 1 are determined, and the prediction value corresponding to prediction mode 1 is processed using the weight of the first component block corresponding to prediction mode 1. For example, for each pixel in the first component block corresponding to prediction mode 1, the prediction value of the pixel in the first component block corresponding to prediction mode 1 is multiplied by the weight of the first component block corresponding to the pixel to obtain the prediction value of the pixel. In this way, the prediction value of the first component block corresponding to prediction mode 1 can be determined. Then, according to the prediction value of the first component block corresponding to prediction mode 1 and the reconstruction value of the first component block, the cost corresponding to prediction mode 1 is determined, wherein the method for determining the cost corresponding to prediction mode 1 includes but is not limited to SAD, SATD, SEE, etc. Similarly, the cost corresponding to prediction mode 2 can be determined. Then, according to the cost corresponding to prediction mode 1 and the cost corresponding to prediction mode 2, the cost corresponding to the second combination is determined. For example, the cost corresponding to prediction mode 1 and the cost corresponding to prediction mode 2 are added to determine the cost corresponding to the second combination. The manner of constructing the candidate combination list according to the cost corresponding to each second combination in the R second combinations in the above S101-E23 can refer to the description of the above S101-A23, which will not be repeated here. The process of determining the R second combinations in the above S101-E21 is introduced below. In some embodiments, the above R second combinations are preset. In some embodiments, S101-E21 includes the following steps: S101-E21-1. Determine C weight derivation modes and D prediction modes, where C is a positive integer and D is a positive integer greater than or equal to K; S101-E21-2. Construct R second combinations based on C weight derivation modes and D prediction modes, wherein any second combination of the R second combinations includes a weight derivation mode from the C weight derivation modes and K prediction modes from the D prediction modes. In this embodiment, the decoding end first determines C weight derivation modes and D prediction modes, and then constructs R second combinations based on the determined C weight derivation modes and D prediction modes. The embodiment of the present application does not limit the specific number of the above-mentioned C weight derivation modes and D prediction modes. Assume that K=2, the above K prediction modes include the first prediction mode and the second prediction mode, assume that there are D types of all available prediction modes, and the first prediction mode has D possibilities. Since the second prediction mode is different from the first prediction mode, there are D-1 types of second prediction modes. Assume that there are C types of weight derivation modes, then the present application may use any two different prediction modes, any weight derivation mode and any transition gradient coefficient to form a second combination, and there are a total of C*D*(D-1) possible second combinations. In this implementation, the C weight derivation modes are all possible weight derivation modes, and the weight derivation modes include transition parameters, that is, the C weight derivation modes include all possible transition parameters, and the D prediction modes are all possible prediction modes, and an exhaustive method is used to obtain all possible second combinations. Each second combination of all possible second combinations is used to predict the first component block, and the distortion cost of each second combination is calculated, and then according to the distortion cost of each second combination, a candidate combination list corresponding to the current component block is obtained. In some embodiments, in order to reduce the amount of data and increase the speed of building the candidate combination list, not every prediction mode is tried, but some of the prediction modes may be selected for trying. At this time, the implementation methods of determining the D prediction modes in the above S101-E21-1 include but are not limited to the following methods: Method 1: D prediction modes are preset prediction modes. Method 2: Determine a candidate prediction mode list for the current component block, a candidate prediction mode list corresponding to the K first prediction modes, a prediction mode corresponding to the weighted derivative mode, and at least one of the preset modes; and determine D prediction modes based on the candidate prediction mode list, the alternative prediction mode list corresponding to the K first prediction modes, the prediction mode corresponding to the weighted derivative mode, and at least one of the preset modes. The manner of determining the third candidate prediction mode list of the current component block includes at least the following examples: Example 1: Determine a third candidate prediction mode list according to a prediction mode used by at least one block adjacent to the current component block. Example 2: if the third candidate prediction mode list does not include the preset mode, determining the preset mode corresponding to the current component block; and adding the preset mode to the third candidate prediction mode list. In an example, the above-mentioned preset modes are several preset prediction modes. In another example, the preset mode is determined by determining the image type corresponding to the current component block and according to the image type corresponding to the current component block. For example, if the image type corresponding to the current component block is B type or P type, the preset mode includes at least one of DC, a horizontal mode, a vertical mode and an angle mode. Example 3, determine the image type corresponding to the current component block, and determine the third candidate prediction mode list according to the image type corresponding to the current component block. For example, if the image type corresponding to the current component block is B type or P type, then DC, at least one of the horizontal mode, vertical mode and some angle modes can be added to the third candidate prediction mode list. For another example, if the image type corresponding to the current component block is I type, then DC, at least one of the horizontal mode and vertical mode can be added to the third candidate prediction mode list. Example 4, determining at least one of the second prediction mode used by the first component block at a preset position, at least one component block among the second component block and the third component block (for example, a chroma block and / or a luminance block), the third prediction mode used by the decoded first component block, the second component block and at least one component block among the third component block (for example, a luminance block and / or a chroma block) around the current component block, the fourth prediction mode used by the first component block (for example, a luminance block) corresponding to the internal preset area of ​​the current component block, and the fifth prediction mode related to the first component block corresponding to the current component block; and determining a candidate prediction mode list for the current component block based on at least one of the second prediction mode, the third prediction mode, the fourth prediction mode and the fifth prediction mode. In the embodiment of the present application, the specific implementation of the above determination of D prediction modes can refer to the specific description of determining Q prediction modes in the above S101-A21-1, which will not be repeated here. In some embodiments, the above D is equal to Q. The following is an introduction to the process of determining C weight derivation modes in S101-E21-1. In some embodiments, the above-mentioned C weight derivation modes are preset. In some embodiments, the C weight derivation modes are selected from a plurality of preset weight derivation modes, for example, the C weight derivation modes are obtained by screening according to information such as the size of the current component block and / or the image type corresponding to the current component block. Optionally, C weight derivation modes with smaller costs can be selected from a plurality of preset weight derivation modes according to the cost. In some embodiments, X transition parameters are determined, and C weight derivation modes are determined based on the X transition parameters. The embodiment of the present application does not limit the size relationship between X and C. In the embodiment of the present application, since each of the C weight derivation modes includes a transition parameter, the C weight derivation modes can be determined according to the X transition parameters. For example, if the weight derivation mode includes other parameters in addition to the transition parameter, at this time, the transition parameters included in at least one or two of the C weight derivation modes can be the same or different, and then the C weight derivation modes can be determined according to the X transition parameters. For example, a plurality of different weight derivation modes composed of X transition parameters are used to determine the cost corresponding to each weight derivation mode in the plurality of different weight derivation modes, and then the C weight derivation modes with the smallest cost are selected. The embodiment of the present application does not limit the specific method of determining the X transition parameters. In some embodiments, the X transition parameters are preset transition parameters, such as 1 / 4, 1 / 2, 1, 2, 4, etc. In some embodiments, X transition parameters are determined according to the size of the current component block. For example, if the size of the current component block is smaller than the third set threshold, a transition parameter greater than or equal to the fifth value among the at least one preset transition parameter is used as the X transition parameters. For another example, if the size of the current component block is greater than or equal to the third set threshold, a transition parameter of the at least one transition parameter that is less than or equal to a sixth value is used as X transition parameters, and the sixth value is less than the fifth value. For another example, if the size of the current component block is greater than or equal to the third set threshold, a transition parameter of the at least one transition parameter that is less than or equal to a sixth value is used as X transition parameters, and the sixth value is less than the fifth value. For another example, if the size of the current component block is smaller than the third set threshold, the X transition parameter is determined to be one or more transition parameters of which at least one preset transition parameter is within the fifth transition parameter value range. For another example, if the size of the current component block is greater than or equal to the third set threshold, the X transition parameter is determined to be one or more transition parameters in which at least one transition parameter is within a sixth transition parameter value range, and the minimum value of the sixth transition parameter value range is less than the minimum value of the fifth transition parameter value range. The embodiment of the present application does not limit the specific values ​​of the third set threshold, the fifth value, the sixth value, the fifth transition parameter value range and the sixth transition parameter value range. Optionally, if the size of the current component block is represented by the number of pixels included in the current component block, the third set threshold is 256. Optionally, the fifth value is 1. Optionally, the sixth value is 1 / 2. In some embodiments, image information of the current component block is determined; and X transition parameters are determined according to the image information of the current component block. Example 1: If the clarity of the image edge of the current component block is less than a preset value, at least one third-category transition parameter among the preset Y transition parameters is determined as X transition parameters, where Y is a positive integer greater than X. The third type of transition parameter may be understood as a transition parameter that may form a wider transition region, such as 1 / 4, 1 / 2, and the like. Example 2: If the clarity of the image edge of the current component block is greater than or equal to a preset value, at least one fourth-type transition parameter among the Y transition parameters is determined as X transition parameters, and the fourth-type transition parameter is greater than the third-type transition parameter. The fourth type of transition parameter may be understood as a transition parameter that may form a narrower transition region, such as 2, 4, etc. After the decoding end determines D prediction modes, C weight derivation modes, and W transition parameters according to the above steps, R different second combinations are formed according to the D prediction modes and C weight derivation modes. Then, a candidate combination list is determined according to the R second combinations, and then the first weight derivation mode and K first prediction modes are determined from the candidate combination list. In some embodiments, in order to further improve the speed of constructing the candidate combination list, the decoding end screens the above-determined D prediction modes and C weight derivation modes. At this time, the above S101-E21-2 comprises the following steps S101-E21-21 to S101-E21-24 according to the determined C weight derivation modes and D prediction modes: S101-E21-21. Select C1 weight derivation modes from C weight derivation modes, where C1 is a positive integer less than or equal to C. The specific implementation process of the above S101-E21-21 can refer to the description of the above S101-A11-21, which will not be repeated here. According to the above steps, after the decoding end selects C1 weight derivation mode from C weight derivation modes, it executes the following steps S101-E21-22. S101-E21-22. Select D1 prediction modes from D prediction modes, where D1 is a positive integer less than or equal to D. The specific implementation process of the above S101-E21-22 can refer to the description of the above S101-A11-22, which will not be repeated here. According to the above steps, C1 weight derivation modes are selected from C weight derivation modes, and D1 prediction modes are selected from D prediction modes. Then, the following S101-E21-23 are executed. S101-C21-23. According to C1 weight derivation modes and D1 prediction modes, R second combinations are formed. The specific implementation process of the above S101-E21-23 can refer to the description of the above S101-A11-23, which will not be repeated here. The following introduces an implementation process of using any second combination to predict the first component block corresponding to the current component block in an embodiment of the present application to obtain a predicted value of the first component block. First, the weight of the first component block is determined using the weight derivation mode included in the second combination. In some embodiments, determining the weight of the first component block according to the weight derivation mode comprises the following steps: Step 3: Determine the angle index, distance index and transition parameter according to the weight derivation mode; Step 4: Determine the weight of the first component block according to the angle index, the distance index, the transition parameter and the size of the first component block. The present application may derive the weight of the first component block in the same manner as the weight of the predicted value. For example, firstly, according to the weight derivation mode, parameters such as the angle index, the distance index and the transition parameter are determined. In the above step 2, the method of determining the weight of the first component block according to the angle index, the distance index, the transition parameter and the size of the first component block includes but is not limited to the following methods: Method 1: Determine the weight of the first component block according to the angle index, the distance index, the transition parameter and the size of the first component block. In this case, the above step 4 includes the following steps 41 to 43: Step 41: Determine a first parameter of a pixel in the first component block according to the angle index, the distance index and the size of the first component block; Step 42: Determine the weight of the pixel in the first component block according to the first parameter and the transition parameter of the pixel in the first component block; Step 43: Determine the weight of the first component block according to the weights of the pixels in the first component block. In this implementation, the weig...

Claims

1. A video decoding method, characterized in that In, including ： Decode the bitstream and determine a first combination, wherein the first combination includes a first weight derivation mode and K first prediction modes, where K is a positive integer greater than 1. ； Predicting a current component block according to the first weight derivation mode and the K first prediction modes to obtain a prediction value of the current component block, wherein the current component block includes the second component block or the third component block 。 2. The method according to claim 1, wherein The feature is that, the decoding bitstream determines the first combination, including: Decoding the bitstream to determine a candidate combination list, wherein the candidate combination list includes at least one candidate combination, and any candidate combination of the at least one candidate combination includes a weight derivation mode and K prediction modes; According to the candidate combination list, determine the first combination.

3. The method according to claim 2, The method is characterized in that the candidate combination list includes a candidate combination, and determining the first combination according to the candidate combination list includes: The candidate combination included in the candidate combination list is determined as the First combination.

4. The method according to claim 2 The method is characterized in that the candidate combination list includes multiple candidate combinations, and determining the first combination according to the candidate combinations includes: Decoding the code stream to obtain a first index, where the first index is used to indicate the first combination; The candidate combination corresponding to the first index in the candidate combination list is determined as The first combination.

5. According to any one of claims 2 to 4 The method is characterized in that the decoding of the code stream to determine the candidate combination list includes: Decoding the bitstream to determine a first component block corresponding to the current component block; Based on the first component block, construct The candidate combination list.

6. According to claim 5 The method is characterized in that the first component block is the same as the current component block in the current image. A spatial first component block.

7. According to the rights The method of claim 5, wherein constructing the candidate combination list based on the first component block comprises: Determine R second combinations, any second combination of the R second combinations includes a weight derivation mode and K prediction modes, and R is a positive integer greater than 1; For any second combination among the R second combinations, determining a cost corresponding to the second combination when the first component block is predicted using the second combination; According to the generation corresponding to each second combination in the R second combinations The candidate combination list is constructed.

8. According to the rights The method of claim 7, characterized in that the determining of the cost corresponding to the second combination when using the second combination to predict the first component block includes: Determining a weight of the first component block according to a weight derivation mode included in the second combination; Predicting the first component block according to the K prediction modes in the second combination to obtain K prediction values ​​of the first component block; Weighting the K prediction values ​​of the first component block according to the weight of the first component block to obtain a prediction value of the first component block corresponding to the second combination; According to the predicted value of the first component block corresponding to the second combination and the reconstructed value of the first component block , determine the cost corresponding to the second combination.

9. Root The method according to claim 7, characterized in that the determining of the cost corresponding to the second combination when using the second combination to predict the first component block comprises: Determine, according to the weight derivation mode in the second combination, prediction values ​​of the first component blocks respectively corresponding to the K prediction modes in the second combination; Determine costs corresponding to the K prediction modes in the second combination according to the predicted values ​​of the first component blocks respectively corresponding to the K prediction modes in the second combination and the reconstructed value of the first component block; According to the K prediction modes in the second combination respectively corresponding to Cost, determining the cost corresponding to the second combination. 1 0. The method according to claim 9, characterized in that the step of determining the cost corresponding to the second combination according to the costs respectively corresponding to the K prediction modes in the second combination comprises: The K prediction modes in the second combination correspond to The sum of the costs is determined as the cost corresponding to the second combination.

11. Root The method according to any one of claims 7 to 10, characterized in that the determining of the R second combinations comprises: Determine P weight derivation modes and Q prediction modes, where P is a positive integer and Q is a positive integer greater than or equal to K; The R second combinations are constructed according to the P weight derivation modes and the Q prediction modes, wherein any second combination of the R second combinations includes a weight in the P weight derivation modes. Re-derive the mode and the K predictions in the Q prediction modes model.

12. The method according to claim 11, wherein determining Q prediction modes comprises: Determine a candidate prediction mode list of the current component block, a candidate prediction mode list corresponding to each of the K first prediction modes, a prediction mode corresponding to a weight derivation mode, and at least one of a preset mode, wherein the candidate prediction mode list includes a plurality of candidate prediction modes, and the candidate prediction mode list corresponding to any prediction mode of the K prediction modes includes at least one candidate prediction mode; According to the candidate prediction mode list, the candidate prediction mode lists corresponding to the K prediction modes, and the weight derivation mode At least one of the prediction modes corresponding to the formula determines the Q A prediction model.

13. The method according to claim 11, characterized in that the determining of the candidate prediction mode list of the current component block comprises: Determine at least one of a second prediction mode used by a first component block at a preset position, at least one of a second component block and a third component block, a third prediction mode used by a decoded first component block, at least one of a second component block and a third component block around the current component block, a fourth prediction mode used by a first component block corresponding to an internal preset area of ​​the current component block, and a fifth prediction mode related to a first component block corresponding to the current component block; According to the second prediction mode, the third prediction mode, the fourth prediction mode and the fifth prediction mode mode, determine the current component block A list of candidate prediction modes.

14. The method according to claim 13, characterized in that determining the fifth prediction mode associated with the first component block corresponding to the current component block comprises: Determine the current component block corresponding to The texture direction of the first component block; According to the texture direction , determine the fifth prediction mode.

15. The method according to claim 14, characterized in that the determining the fifth prediction mode according to the texture direction comprises: Determine a prediction mode whose prediction direction is parallel to the texture direction as the fifth prediction mode; and / or, The prediction direction is perpendicular to the texture direction. Mode is determined to be the fifth prediction mode.

16. The method according to claim 14, characterized in that the determining the texture direction of the first component block corresponding to the current component block comprises: Selecting a plurality of texture points in the first component block according to a preset texture point selection method; Determining texture directions corresponding to the plurality of texture points respectively; The One or more texture directions corresponding to multiple texture points , and determined as the texture direction of the first component block.

17. The method according to claim 16, wherein determining one or more of the texture directions corresponding to the plurality of texture points as the texture direction of the first component block comprises: The multiple patterns The texture direction corresponding to each point has the largest number of occurrences. or more, are determined as the texture direction of the first component block.

18. The method according to claim 10, characterized in that the determining of P weight derivation modes comprises: ： Select the P weight derivation modes from the preset M weight derivation modes, where M is greater than Or a positive integer equal to P.

19. The method according to any one of claims 1-4, 6-10, and 12-18, characterized in that the step of predicting the current component block according to the first weight derivation mode and the K first prediction modes to obtain a predicted value of the current component block comprises: determining a first transition parameter; According to the first transition parameter, The first weight derivation mode and the K first prediction modes The current component block is predicted to obtain a predicted value of the current component block.

20. The method according to claim 19, wherein the step of predicting the current component block according to the first transition parameter, the first weight derivation mode and the K first prediction modes to obtain a predicted value of the current component block comprises: Determining a weight of a prediction value according to the first transition parameter and the first weight derivation mode; The current component block is predicted according to the K first prediction modes. Perform prediction and obtain K predicted values; The K predicted values ​​are weighted according to the weights of the predicted values. , obtain the predicted value of the current component block.

21. The method according to any one of claims 1-4, 6-10, and 12-18, wherein the first combination includes a second transition parameter, and the predicting the current component block according to the first weight derivation mode and the K first prediction modes to obtain a predicted value of the current component block comprises: According to the second transition parameter, the first weight derivation mode and the K The first prediction mode predicts the current component block to obtain a prediction value of the current component block.

22. The method according to claim 21, characterized in that the step of predicting the current component block according to the second transition parameter, the first weight derivation mode and the K first prediction modes to obtain a predicted value of the current component block comprises: Determining a weight of a prediction value according to the second transition parameter and the first weight derivation mode; According to the K first prediction modes, The current component block is predicted to obtain K predicted values; The K predicted values ​​are assigned according to the weights of the predicted values. The measured values ​​are weighted to obtain the predicted value of the current component block.

23. The method according to any one of claims 1-4, 6-10, 12-18, characterized in that the first weight derivation mode includes a third transition parameter, and the current component block is predicted according to the first weight derivation mode and the K first prediction modes to obtain the current component block. Predicted values ​​of gauge blocks, including: According to the third transition parameter The number and the K first prediction modes are used to predict the current component block to obtain a predicted value of the current component block.

24. The method according to claim 23, characterized in that the step of predicting the current component block according to the third transition parameter and the K first prediction modes to obtain a predicted value of the current component block comprises: Determining a weight of a predicted value according to the third transition parameter; According to the K first prediction The current component block is predicted in a prediction mode to obtain K prediction values; According to the weight of the predicted value The K prediction values ​​are weighted to obtain a prediction value of the current component block.

25. The method according to any one of claims 1-4, 6-10, 12-18, characterized in that the method further comprises: Decoding the bitstream to obtain at least one flag, wherein the at least one flag is used to indicate whether to use the first combination to decode the current component block; Said Decoding the code stream and determining the first combination includes: If the When at least one flag indicates that the first combination is used to decode the current component block, the code stream is decoded to determine the first combination.

26. The method according to claim 25 method, The at least one flag comprises at least one of a sequence level flag, a picture level flag, a slice level flag, a unit level flag and a block level flag. one.

27. A video encoding method, comprising: Determine a first combination, the first combination comprising a first weight derivation mode and K first prediction modes, wherein K is a positive integer greater than 1 ； According to the first weight-deriving mode and the K A prediction mode predicts a current component block to obtain a prediction value of the current component block, where the current component block includes the second component block or the third component block.

28. The method according to claim 27, wherein determining the first combination comprises: Determine a candidate combination list, the The candidate combination list includes at least one candidate combination. Any candidate combination of at least one candidate combination includes a weight derivation mode and K prediction modes; The first combination is determined according to the candidate combination list.

29. The method according to claim 28, characterized in that The method further comprises: If the candidate combination list includes one candidate combination, writing a first index in the bitstream is skipped, where the first index is used to indicate the first combination.

30. The method according to claim 28, characterized in that The law also includes: If the candidate combination list includes multiple candidate combinations, a first index is written into the bitstream, and the first index is used to indicate the first combination. 3 1. The method according to any one of claims 28 to 30 The method is characterized in that the determining of the candidate combination list comprises: Determine the current component block corresponding to The first component block; Based on the first component block, construct the A list of candidate combinations is given.

32. The method according to claim 31, characterized in that the first component block is the first component block in the current image that is in the same space as the current component block.

33. The method according to claim 31, wherein constructing the candidate combination list based on the first component block comprises: Determine R second combinations, any second combination of the R second combinations includes a weight derivation mode and K prediction modes, and R is a positive integer greater than 1; For any second combination of the R second combinations, determine determining a cost corresponding to the second combination when the second combination is used to predict the first component block; The candidate combination list is constructed according to the cost corresponding to each second combination in the R second combinations.

34. The method according to claim 33, wherein the determining of the cost corresponding to the second combination when using the second combination to predict the first component block comprises: Determining a weight of the first component block according to a weight derivation mode included in the second combination; Predicting the first component block according to the K prediction modes in the second combination to obtain K prediction values ​​of the first component block; According to the first component The weights of the blocks are used to calculate the K predicted values ​​of the first component block. weighted to obtain a predicted value of the first component block corresponding to the second combination; The cost corresponding to the second combination is determined according to the predicted value of the first component block corresponding to the second combination and the reconstructed value of the first component block.

35. The method according to claim 33, wherein the determining the cost corresponding to the second combination when using the second combination to predict the first component block comprises: Determine, according to the weight derivation mode in the second combination, prediction values ​​of the first component blocks respectively corresponding to the K prediction modes in the second combination; According to the second combination The prediction of the first component block corresponding to the K prediction modes value and the reconstructed value of the first component block, determining costs respectively corresponding to K prediction modes in the second combination; The cost corresponding to the second combination is determined according to the costs respectively corresponding to the K prediction modes in the second combination.

36. According to the rights The method of claim 35, characterized in that the The costs corresponding to the K prediction modes are respectively determined, and the cost corresponding to the second combination is determined, including: The sum of the costs corresponding to the K prediction modes in the second combination is determined as the cost corresponding to the second combination.

37. The method according to any one of claims 33 to 36, wherein determining R second combinations comprises: Determine P weight derivation modes and Q prediction modes, where P is a positive integer and Q is a is a positive integer greater than or equal to K; According to the P weights Re-derive the mode and the Q prediction modes to construct the R second combinations, wherein any second combination of the R second combinations includes a weight derivation mode of the P weight derivation modes and K prediction modes of the Q prediction modes.

38. The method according to claim 37, wherein determining Q prediction modes comprises: Determine at least one of a candidate prediction mode list of the current component block, a candidate prediction mode list corresponding to the K first prediction modes, a prediction mode corresponding to a weight derivation mode, and a preset mode, wherein the candidate prediction mode list includes multiple candidate prediction modes, the K first prediction modes respectively correspond to the candidate prediction mode lists, the prediction mode corresponding to the weight derivation mode, and the preset mode. The list of alternative prediction modes corresponding to any prediction mode in the test mode The table contains at least one alternative prediction mode; The Q prediction modes are determined according to at least one of the candidate prediction mode list, the alternative prediction mode lists corresponding to the K prediction modes respectively, and the prediction mode corresponding to the weight derivation mode.

39. The method according to claim 11, characterized in that the determining of the candidate prediction mode list of the current component block comprises: Determine the second prediction mode used by at least one of the first component block, the second component block, and the third component block at the preset position, the third prediction mode used by the first component block, the second component block, and at least one component block of the third component block that have been encoded around the current component block, and the first component block corresponding to the internal preset area of ​​the current component block. The fourth prediction mode of the current component block and the first at least one of the corresponding fifth prediction modes associated with the component block; Determine a candidate for the current component block according to at least one of the second prediction mode, the third prediction mode, the fourth prediction mode, and the fifth prediction mode. List of prediction modes.

40. According to claim 39 The method is characterized in that determining the corresponding fifth prediction mode related to the first component block corresponding to the current component block comprises: Determining a texture direction of a first component block corresponding to the current component block; The fifth prediction mode is determined according to the texture direction.

41. The method according to claim 40, characterized in that The determining the fifth prediction mode according to the texture direction includes: Determine a prediction mode that is parallel to the angle of the texture direction as the fifth prediction mode; and / or, A prediction mode that is perpendicular to the angle of the texture direction is determined as the fifth prediction mode.

42. The method according to claim 40, characterized in that the determining The texture direction of the first component block corresponding to the current component block, include: Selecting a plurality of texture points in the first component block according to a preset texture point selection method; Determining texture directions corresponding to the plurality of texture points respectively; One or more of the texture directions corresponding to the plurality of texture points are determined as the texture direction of the first component block.

43. The method according to claim 42, wherein The feature is that determining one or more of the texture directions corresponding to the plurality of texture points as the texture direction of the first component block comprises: The plurality of texture points One or more of the texture directions that appear the most times in the corresponding texture directions are determined as the texture directions of the first component block. 。 44. The method according to claim 37, wherein determining P weight derivation modes comprises: The P weight derivation modes are selected from the preset M weight derivation modes, where M is a positive integer greater than or equal to P.

45. The method according to any one of claims 27-30, 32-36, 38-44, characterized in that: The first weight-derived mode and the K first A prediction mode predicts the current component block to obtain a prediction value of the current component block, including: determining a first transition parameter; The current component block is predicted according to the first transition parameter, the first weight derivation mode and the K first prediction modes to obtain a prediction value of the current component block.

46. ​​The method according to claim 45, characterized in that the current segment is derived according to the first transition parameter, the first weight derivation mode and the K first prediction modes. The method of performing prediction on the current component block to obtain the predicted value of the current component block includes: According to the first transition parameter and the The first weight derivation mode determines the weight of the predicted value; Predicting the current component block according to the K first prediction modes to obtain K prediction values; The K prediction values ​​are weighted according to the weights of the prediction values ​​to obtain a prediction value of the current component block.

47. The method according to any one of claims 27-30, 32-36, 38-44, characterized in that If the first combination includes a second transition parameter, then the Predicting the current component block according to the first weight derivation mode and the K first prediction modes to obtain a prediction value of the current component block includes: The current component block is predicted according to the second transition parameter, the first weight derivation mode and the K first prediction modes to obtain a prediction value of the current component block.

48. The method according to claim 47, characterized in that the second transition parameter, the first weight derivation mode and the K first prediction modes Predicting the current component block to obtain a predicted value of the current component block includes: According to the second The weight of the predicted value is determined by using the transition parameter and the first weight derivation mode; Predicting the current component block according to the K first prediction modes to obtain K prediction values; The K prediction values ​​are weighted according to the weights of the prediction values ​​to obtain a prediction value of the current component block.

49. According to claims 27-30, 32-36, 38-44 Any method described in claim 1, characterized in that the first The re-derivation mode includes a third transition parameter, and the predicting of the current component block according to the first weight derivation mode and the K first prediction modes to obtain a predicted value of the current component block includes: The current component block is predicted according to the third transition parameter and the K first prediction modes to obtain a prediction value of the current component block.

50. The method according to claim 49, characterized in that The third transition parameter and the K first prediction modes are used to predict the current component block to obtain the current component The predicted value of the block, including: Determining a weight of a predicted value according to the third transition parameter; Predicting the current component block according to the K first prediction modes to obtain K prediction values; The K prediction values ​​are weighted according to the weights of the prediction values ​​to obtain a prediction value of the current component block. 51.According to Claims 27-30, 32-36, 38-4 The method according to any one of claims 4, characterized in that the method further comprises: Determine at least one flag, the at least one flag being used to indicate Indicates whether to use the first combination to Gauge block decoding; The determining of the first combination comprises: If the at least one flag indicates that the first combination is used to decode the current component block, determining the first combination 。 52. The method according to claim 51, characterized in that the at least one mark comprises a sequence level mark, a picture level mark, a slice level mark, a unit level mark, At least one of a flag and a block-level flag. 5 3. A A video decoding device, characterized in that it comprises: A decoding unit, configured to decode a bit stream and determine a first combination, wherein the first combination includes a first weight derivation mode and K first prediction modes, where K is a positive integer greater than 1; A prediction unit is configured to predict the current segment according to the first weight derivation mode and the K first prediction modes. The block is predicted to obtain the current The predicted value of the component block.

54. A video encoding device, comprising: A determining unit, configured to determine a first combination, wherein the first combination includes a first weight derivation mode and K first prediction modes, where K is a positive integer greater than 1; A prediction unit is configured to predict the Export Module Formula and the K first prediction mode pairs The current component block is predicted to obtain a predicted value of the current component block.

55. An electronic A device, characterized in that it comprises a processor and a memory; The memory shown is used to store computer programs sequence; The processor is used to call and execute the stored A computer program stored in a memory to implement the method described in any one of claims 1 to 26 or 27 to 52. 56.A video coding and decoding system The system is characterized by comprising: Video encoders and video decoders; The video decoder is used to implement the above rights The method according to any one of claims 1 to 26; The video encoder is used to implement the method described in any one of claims 27 to 52.

57. A computer-readable storage medium, characterized in that it is used to store a computer program; The computer program enables a computer to execute the method as claimed in any one of claims 1 to 26 or 27 to 52 above.

58. A code stream, characterized in that the code stream is generated based on the method described in any one of claims 27 to 52.

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