Method and device for predicting image component and computer storage medium

Abstract

To provide a method and a device for predicting an image component, and a computer storage medium, which integrate a process of deriving a model parameter without changing encoding / decoding prediction performance.SOLUTION: A method includes steps of: obtaining a first reference pixel set corresponding to a predicted image component of a coding block in a video image (S501); using a preset component value as a prediction value corresponding to the predicted image component if a number of effective pixel points is less than a preset number (S502); screening the first reference pixel set to obtain a second reference pixel set if the number of effective pixel points is greater than or equal to the preset number (S503); using the preset component value as a prediction value corresponding to a predicted image component (S504); determining a model parameter via a second reference pixel set, and obtaining the prediction model corresponding to the predicted image component (S505). The prediction model is used to implement prediction processing on the image component to be predicted to obtain a prediction value.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present embodiment relates to the field of video encoding and decoding, and more particularly to a method, apparatus, and computer storage medium for predicting image components. [Background technology]

[0002] As people's demands for video display quality increase, new forms of video applications such as high-definition and ultra-high-definition video have emerged. H.265 / High Efficiency Video Coding (HEVC) cannot meet the requirements of the rapid development of video applications. Therefore, the Joint Video Exploration Team (JVET) proposed the next-generation video coding standard, H.266 / Versatile Video Coding (VVC), and the corresponding test model is the VVC Reference Software Test Platform (VTM).

[0003] Currently, VTM integrates a prediction model-based image component prediction method, which can predict the chrominance component from the luma component of the current coding block (CB) through the prediction model. However, when constructing the prediction model, the number of neighboring reference pixels used to derive the model parameters varies, which not only increases additional processing but also increases the computational complexity. Summary of the Invention [Problem to be solved by the invention]

[0004] The present embodiment provides a method, device, and computer storage medium for predicting image components, which integrates the model parameter derivation process without changing the encoding and decoding prediction performance. At the same time, if the number of valid pixel points in the neighboring reference pixel set is smaller than the preset number, no additional processing modules are added, so no additional processing is required and calculation complexity is reduced. [Means for solving the problem]

[0005] The technical solution of the present embodiment can be realized as follows:

[0006] In a first aspect, the present embodiments provide a method for predicting image components, the method comprising: Obtaining a first set of reference pixels corresponding to a predicted image component of a coding block in a video image; If the number of valid pixel points in the first reference pixel set is less than a preset number, using a preset component value as a predicted value corresponding to the predicted image component; if the number of valid pixel points in the first reference pixel set is greater than or equal to a preset number, screening the first reference pixel set to obtain a second reference pixel set, where the number of valid pixel points in the second reference pixel set is less than or equal to a preset number; If the number of valid pixel points in the second reference pixel set is smaller than the number of presets, using the preset component values ​​as predicted values ​​corresponding to the predicted image component; and if the number of valid pixel points in the second reference pixel set is equal to the number of presets, determining model parameters via the second reference pixel set and obtaining a prediction model corresponding to the predicted image component according to the model parameters, wherein the prediction model is used to realize a prediction process for the predicted image component and obtain a predicted value corresponding to the predicted image component.

[0007] In a second aspect, the present embodiment provides an apparatus for predicting an image component, comprising an acquisition unit, a prediction unit and a screening unit, wherein: The obtaining unit is configured to obtain a first set of reference pixels corresponding to a predicted image component of a coding block in a video image; the prediction unit is configured to use a preset component value as a prediction value corresponding to the image component to be predicted when a number of valid pixel points in the first reference pixel set is smaller than a preset number; the screening unit is configured to screen the first reference pixel set to obtain a second reference pixel set when the number of valid pixel points in the first reference pixel set is greater than or equal to a preset number, where the number of valid pixel points in the second reference pixel set is less than or equal to a preset number; The prediction unit is further configured to: use a preset component value as a predicted value corresponding to the predicted image component when the number of valid pixel points in the second reference pixel set is smaller than a preset number; and determine model parameters via the second reference pixel set when the number of valid pixel points in the second reference pixel set is equal to the preset number; and obtain a prediction model corresponding to the predicted image component according to the model parameters, wherein the prediction model is used to realize a prediction process for the predicted image component and obtain a predicted value corresponding to the predicted image component.

[0008] In a third aspect, embodiments of the present application provide an apparatus for predicting an image component, comprising: a memory; and a processor; the memory is configured to store a computer program executable by the processor; The processor, when executing the computer program, is configured to perform the method according to the first aspect.

[0009] In a fourth aspect, an embodiment of the present application provides a computer storage medium storing an image component prediction program, the image component prediction program implementing the method of the first aspect when executed by at least one processor. [Effects of the Invention]

[0010] The present embodiment provides a method, an apparatus, and a computer storage medium for predicting an image component, the method comprising: obtaining a first reference pixel set corresponding to a predicted image component of a coding block in a video image; if the number of valid pixel points in the first reference pixel set is less than a preset number, using the preset component values ​​as predicted values ​​corresponding to the image component to be predicted; if the number of valid pixel points in the first reference pixel set is greater than or equal to the preset number, screening the first reference pixel set to obtain a second reference pixel set, the number of valid pixel points in the second reference pixel set is less than or equal to the preset number, using the preset component values ​​as predicted values ​​corresponding to the image component to be predicted; if the number of valid pixel points in the second reference pixel set is equal to the preset number, determining model parameters via the second reference pixel set; obtaining a prediction model corresponding to the predicted image component according to the model parameters; and The rule is used to realize a prediction process for a predicted image component to obtain a predicted value corresponding to the predicted image component. In this way, if the number of effective pixel points in the first reference pixel set is smaller than the preset number or the number of effective pixel points in the second reference pixel set is smaller than the preset number, a default value of the preset is directly used as a predicted value corresponding to the predicted image component. Only if the number of effective pixel points in the second reference pixel set satisfies the preset number, model parameters are determined according to the first reference pixel set to establish a prediction model for the predicted image component, thereby integrating the derivation process of the model parameters. Furthermore, if the number of effective pixel points in the first reference pixel set or the second reference pixel set is smaller than the preset number, particularly if the effective pixel points are 0 or 2, no additional processing module is added, and the default value of the preset is directly used as a predicted value corresponding to the predicted image component, so that no additional processing is required and the calculation complexity is reduced. [Brief explanation of the drawings]

[0011] [Figure 1]FIG. 10 is a schematic diagram of the distribution of effective adjacent regions according to an embodiment of the present invention. [Figure 2] 10A and 10B are schematic diagrams of distribution of selected areas in three modes according to an embodiment of the present invention. [Figure 3] 1 is a block diagram of an exemplary configuration of a video encoding system according to an embodiment of the present invention; [Figure 4] FIG. 1 is a block diagram of an exemplary configuration of a video decoding system according to an embodiment of the present invention. [Figure 5] 1 is an exemplary flowchart of a method for predicting image components according to an embodiment of the present disclosure. [Figure 6A] 10 is an exemplary structural diagram of the selection of neighboring reference pixel points in INTRA_LT_CCLM mode according to an embodiment of the present invention; [Figure 6B] 10 is an exemplary structural diagram of the selection of neighboring reference pixel points in INTRA_L_CCLM mode according to an embodiment of the present invention; [Figure 6C] 10 is an exemplary structural diagram of the selection of neighboring reference pixel points in INTRA_T_CCLM mode according to an embodiment of the present invention; [Figure 7] 10 is an exemplary flowchart of a method for predicting another image component according to an embodiment of the present disclosure. [Figure 8A] FIG. 10 is an exemplary structural diagram of generating 0 effective pixel points in INTRA_LT_CCLM mode according to an embodiment of the present invention. [Figure 8B] FIG. 10 is an exemplary structural diagram of generating 0 effective pixel points in INTRA_L_CCLM mode according to an embodiment of the present invention. [Figure 8C] FIG. 10 is an exemplary structural diagram of generating 0 effective pixel points in INTRA_T_CCLM mode according to an embodiment of the present invention. [Figure 9A] FIG. 10 is an exemplary structural diagram of generating two effective pixel points in INTRA_LT_CCLM mode according to an embodiment of the present invention. [Figure 9B] FIG. 10 is an exemplary structural diagram of generating two effective pixel points in INTRA_L_CCLM mode according to an embodiment of the present invention. [Figure 9C] FIG. 10 is an exemplary structural diagram of generating two effective pixel points in INTRA_T_CCLM mode according to an embodiment of the present invention. [Figure 10] 1 is an exemplary flowchart for deriving model parameters according to an embodiment of the present invention. [Figure 11] 1 is an exemplary simplified flowchart for deriving model parameters according to an embodiment of the present invention. [Figure 12] 10 is another exemplary simplified flowchart for deriving model parameters according to an embodiment of the present disclosure. [Figure 13] 1 is an exemplary structural diagram of an image component prediction device according to an embodiment of the present invention; [Figure 14] 1 is an exemplary structural diagram of specific hardware of an image component prediction device according to an embodiment of the present application; [Figure 15] FIG. 2 is an exemplary structural diagram of an encoder according to an embodiment of the present invention; [Figure 16] FIG. 2 is an exemplary structural diagram of a decoder configuration according to an embodiment of the present invention; DETAILED DESCRIPTION OF THE INVENTION

[0012] In order to more fully understand the features and technical contents of the present embodiment, the following detailed description of the implementation of the present embodiment will be given with reference to the accompanying drawings, which are for reference purposes only and are not intended to limit the present embodiment.

[0013] In a video image, a first image component, a second image component, and a third image component are usually used to represent a coding block, where the three image components are one luminance component, one blue chrominance component, and one red chrominance component, respectively. Specifically, the luminance component is usually represented by the symbol Y, the blue chrominance component is usually represented by the symbol Cb or U, and the red chrominance component is usually represented by the symbol Cr or V. In this way, the video image can be represented in the format of YCbCr, and can also be represented in the format of YUV.

[0014] In the present embodiment, the first image component may be a luminance component, the second image component may be a blue chroma component, and the third image component may be a red chroma component, but the present embodiment is not particularly limited thereto.

[0015] In current video image or video encoding and decoding processes, cross-component prediction technologies mainly include cross-component linear model prediction (CCLM) mode and multi-directional linear model prediction (MDLM) mode. Regardless of the model parameters derived according to the CCLM mode or the MDLM mode, the corresponding prediction models can all realize prediction between image components, such as from the first image component to the second image component, from the second image component to the first image component, from the first image component to the third image component, from the third image component to the first image component, from the second image component to the third image component, or from the third image component to the second image component.

[0016] Taking prediction from the first image component to the second image component as an example, in order to reduce the redundancy between the first image component and the second image component, CCLM mode is used in VVC, where the first image component and the second image component are from the same coding block, that is, the predicted value of the second image component is constructed according to the reconstructed value of the first image component of the same coding block, as shown in the following equation (1):

number

[0017] JPEG2025148530000003.jpg49170

[0018] For a coding block, its neighboring regions may include a left neighboring region, an upper neighboring region, a lower-left neighboring region, and an upper-right neighboring region. VVC may include three cross-component linear model prediction modes, which are left and upper neighboring intra-CCLM mode (which can be represented by INTRA_LT_CCLM mode), left and lower-left neighboring intra-CCLM mode (which can be represented by INTRA_L_CCLM mode), and upper and upper neighboring intra-CCLM mode (which can be represented by INTRA_T_CCLM mode). In these three modes, each mode can select a preset number (for example, four) of neighboring reference pixel points to use in deriving the model parameters α and β, and the biggest difference between these three modes is that the selected regions corresponding to the neighboring reference pixel points for deriving the model parameters α and β are different.

[0019] JPEG2025148530000004.jpg98170

[0020] JPEG2025148530000005.jpg106170

[0021] FIG. 1 shows a schematic diagram of the distribution of valid neighboring regions according to an embodiment of the present invention. In FIG. 1, the left neighboring region, the lower-left neighboring region, the upper neighboring region, and the upper-right neighboring region are all valid. Based on FIG. 1, the selection regions for the three modes are as shown in FIG. 2. In FIG. 2, (a) shows the selection region for the INTRA_LT_CCLM mode, including the left neighboring region and the upper neighboring region; (b) shows the selection region for the INTRA_L_CCLM mode, including the left neighboring region and the lower-left neighboring region; and (c) shows the selection region for the INTRA_T_CCLM mode, including the upper neighboring region and the upper-right neighboring region. After the selection regions for the three modes are determined in this manner, reference points for deriving model parameters can be selected in the selection regions. The reference points selected in this manner are called neighboring reference pixel points. Typically, the number of neighboring reference pixel points is up to four. The positions of the neighboring reference pixel points are typically determined for a single coding block of size W × H.

[0022] However, in some special cases, such as in the case of the boundary of the coding block, when it is not possible to predict and when neighboring reference pixel points cannot be obtained due to the coding order, and further, when dividing the coding block according to tiles or slices, the neighboring region may be invalid, so that the number of neighboring reference pixel points selected from the neighboring region may be less than four, that is, only 0 or 2 neighboring reference pixel points may be selected, thereby making the number of neighboring reference pixel points used for deriving the model parameters unintegrated, thereby increasing the additional "duplication" operation and at the same time increasing the computational complexity.

[0023] In order to unify the process of deriving model parameters and reduce the computational complexity while maintaining the performance of encoding and decoding prediction, an embodiment of the present application provides a method for predicting an image component, by obtaining a first reference pixel set corresponding to a predicted image component of a coding block in a video image, and if the number of valid pixel points in the first reference pixel set is less than a preset number, using the preset component values ​​as predicted values ​​corresponding to the predicted image component; if the number of valid pixel points in the first reference pixel set is greater than or equal to the preset number, screening the first reference pixel set to obtain a second reference pixel set, and if the number of valid pixel points in the second reference pixel set is less than or equal to the preset number, using the preset component values ​​as predicted values ​​corresponding to the predicted image component; if the number of valid pixel points in the second ... using the preset component values ​​as predicted values ​​corresponding to the predicted image component; If the number of valid pixel points in the first reference pixel set is equal to the preset number, determine model parameters through the first reference pixel set, and obtain a prediction model corresponding to the image component to be predicted according to the model parameters. Here, the prediction model is used to realize prediction processing for the image component to be predicted and obtain a predicted value corresponding to the image component to be predicted. In this way, if the number of valid pixel points in the first reference pixel set is smaller than the preset number or if the number of valid pixel points in the second reference pixel set is smaller than the preset number, disable the CCLM mode and directly use the default value of the preset as the predicted value corresponding to the image component to be predicted. This does not require additional processing modules, and at the same time reduces calculation complexity. Furthermore, only if the number of valid pixel points in the second reference pixel set is equal to the preset number, perform the derivation of model parameters, i.e., perform the CCLM mode to unify the derivation process of model parameters.

[0024] Hereinafter, each embodiment of the present application will be described in detail with reference to the drawings.

[0025] Referring to FIG. 3, an exemplary block diagram of a configuration of a video encoding system according to an embodiment of the present application is shown. As shown in FIG. 3, the video encoding system 300 includes a transform and quantization unit 301, an intra estimation unit 302, an intra prediction unit 303, a motion compensation unit 304, a motion estimation unit 305, an inverse transform and inverse quantization unit 306, a filter control analysis unit 307, a filtering unit 308, an encoding unit 309, and a decoded image cache unit 310, etc., where the filtering unit 308 can realize deblocking filtering and Sample Adaptive Offset (SAO) filtering, and the encoding unit 309 can realize header coding and Context-based Adaptive Binary Arithmetic Coding (CABAC). For an input original video signal, a video coding block can be obtained through division of a coding tree unit (CTU), and then the video coding block is transformed through a transform and quantization unit 301 for residual pixel information obtained by intra or inter prediction, and the residual information is converted from a pixel field to a transform field, and the obtained transform coefficients are quantized to reduce the bit rate.The intra estimation unit 302 and the intra prediction unit 303 are configured to perform intra prediction on the video coding block, specifically, the intra estimation unit 302 and the intra prediction unit 303 are configured to determine an intra prediction mode to be used for coding the video coding block, the motion compensation unit 304 and the motion estimation unit 305 are configured to perform inter-predictive coding of the received video coding block corresponding to one or more blocks in one or more reference frames to provide temporal prediction information, the motion estimation performed by the motion estimation unit 305 is a process of generating a motion vector, which can estimate the motion of the video coding block, and then the motion compensation unit 304 performs motion compensation based on the motion vector determined by the motion estimation unit 305. After determining the intra prediction mode, the intra prediction unit 303 is further configured to provide the selected intra prediction data to the encoding unit 309, and the motion estimation unit 305 also sends the calculated and determined motion vector data to the encoding unit 309. In addition, the inverse transform and inverse quantization unit 306 is configured to reconstruct the video coding block and reconstruct a residual block in a pixel field, and the reconstructed residual block is filtered through the filter control analysis unit 307 and the filtering unit 308 to remove block effect artifacts, and then adds the reconstructed residual block to one prediction block in a frame of the decoding image cache unit 310 to generate a reconstructed video coding block.The encoding unit 309 is configured to code various coding parameters and quantized transform coefficients, and in a CABAC-based coding algorithm, the content of the context can be based on neighboring coding blocks, and is configured to code information of an intra-prediction mode determined by an instruction, and output a bitstream of the video signal. The decoding picture cache unit 310 is configured to store reconstructed video coding blocks for predicting references. As video image coding is performed, new reconstructed video coding blocks continue to be generated, and all of these reconstructed video coding blocks are stored in the decoding picture cache unit 310.

[0026] 4 illustrates an exemplary block diagram of a video decoding system according to an embodiment of the present disclosure. As shown in FIG. 4, the video decoding system 400 includes a decoding unit 401, an inverse transform and inverse quantization unit 402, an intra prediction unit 403, a motion compensation unit 404, a filtering unit 405, and a decoded image cache unit 406. The decoding unit 401 performs header decoding and CABAC decoding, and the filtering unit 405 performs deblocking filtering and SAO filtering. An input video signal undergoes the coding process of FIG. 2, outputting a bitstream of the video signal. The bitstream is input to the video decoding system 400, where it first passes through the decoding unit 401 to obtain decoded transform coefficients, and then the decoded transform coefficients are processed by the inverse transform and inverse quantization unit 402 to generate residual blocks in a pixel field. The intra prediction unit 403 is configured to generate prediction data for the current video decoding block based on the determined intra prediction mode and data passing through the decoding block from the current frame or picture. The motion compensation unit 404 is configured to determine prediction information for the video decoding block by analyzing the motion vector and other related grammar elements, and use the prediction information to generate a prediction block for the video decoding block being decoded. The residual block from the inverse transform and inverse quantization unit 402 is added to the corresponding prediction block generated by the intra prediction unit 403 or the motion compensation unit 404 to form a decoded video block. The decoded video signal can pass through a filtering unit 405 to remove block effect artifacts and improve video quality. The decoded video block is then stored in a decoded image cache unit 406. The decoded image cache unit 406 is configured to store a reference image for subsequent intra prediction or motion compensation and output a video signal, i.e., obtain a restored original video signal.

[0027] The image component prediction method in this embodiment is mainly applied to the intra prediction unit 303 shown in Figure 3 and the intra prediction unit 403 shown in Figure 4, specifically to the CCLM prediction unit in intra prediction. That is, the image component prediction method in this embodiment may be applied to a video encoding system, a video decoding system, or even simultaneously to a video encoding system and a video decoding system, but is not particularly limited in this embodiment. When this method is applied to the intra prediction unit 303, the "coded block in a video image" specifically refers to a current coded block in intra prediction, and when this method is applied to the intra prediction unit 403, the "coded block in a video image" specifically refers to a current decoded block in intra prediction.

[0028] Based on the application scenario example of Fig. 3 or Fig. 4 above, an exemplary flowchart of an image component prediction method according to an embodiment of the present application is shown in Fig. 5. As shown in Fig. 5, the method may include the following steps:

[0029] In S501, a first reference pixel set corresponding to a predicted image component of a coding block in a video image is obtained.

[0030] It should be noted that a video image can be divided into multiple coding blocks, and each coding block may include a first image component, a second image component, and a third image component, and the coding block in this embodiment is the current block to be coded in the video image. When the first image component needs to be predicted through a prediction model, the predicted image component is the first image component; when the second image component needs to be predicted through a prediction model, the predicted image component is the second image component; and when the third image component needs to be predicted through a prediction model, the predicted image component is the third image component.

[0031] Furthermore, it should be noted that if the left neighboring region, the lower-left neighboring region, the upper neighboring region, and the upper-right neighboring region are all valid regions, then for the INTRA_LT_CCLM mode, the first reference pixel set is formed by neighboring reference pixel points in the left neighboring region and upper neighboring region of the coding block, as shown in (a) of Figure 2; for the INTRA_L_CCLM mode, the first reference pixel set is formed by neighboring reference pixel points in the left neighboring region and lower-left neighboring region of the coding block, as shown in (b) of Figure 2; and for the INTRA_T_CCLM mode, the first reference pixel set is formed by neighboring reference pixel points in the upper neighboring region and upper-right neighboring region of the coding block, as shown in (c) of Figure 2.

[0032] In some embodiments, illustratively for S501, obtaining a first reference pixel set corresponding to a predicted image component of a coding block in the video image may include the following steps:

[0033] In S501a-1, a reference pixel point adjacent to at least one side of the coding block is obtained, where the at least one side includes the left side of the coding block and / or the top side of the coding block.

[0034] In S501a-2, a first reference pixel set corresponding to the predicted image component is formed based on the reference pixel points.

[0035] At least one edge of the coding block may include the left edge of the coding block and / or the top edge of the coding block, i.e., at least one edge of the coding block may refer to the top edge of the coding block, may refer to the left edge of the coding block, or may further refer to the top edge and the left edge of the coding block, and it should be noted that this is not particularly limited in the present embodiment.

[0036] In this way, for the INTRA_LT_CCLM mode, if the left-side adjacent region and the upper-side adjacent region are all valid regions, the first reference pixel set can be formed by the reference pixel points adjacent to the left edge of the coding block and the reference pixel points adjacent to the upper edge of the coding block; if the left-side adjacent region is a valid region and the upper-side adjacent region is an invalid region, the first reference pixel set can be formed by the reference pixel points adjacent to the left edge of the coding block; if the left-side adjacent region is an invalid region and the upper-side adjacent region is a valid region, the first reference pixel set can be formed by the reference pixel points adjacent to the upper edge of the coding block.

[0037] In some embodiments, illustratively for S501, obtaining a first reference pixel set corresponding to a predicted image component of a coding block in the video image may include the following steps:

[0038] In S501b-1, a reference pixel point in a reference row or reference column adjacent to the coding block is obtained, where the reference row is formed by rows adjacent to the upper side and upper right side of the coding block, and the reference column is formed by columns adjacent to the left side and lower left side of the coding block.

[0039] In S501b-2, a first reference pixel set corresponding to the predicted image component is formed based on the reference pixel points.

[0040] The reference row adjacent to a coding block may be formed by a row adjacent to the upper side and the upper right side of the coding block, and the reference column adjacent to a coding block may be formed by a column adjacent to the left side and the lower left side of the coding block, and the reference row or the reference column adjacent to a coding block may refer to the reference row adjacent to the upper side of the coding block, or may refer to the reference column adjacent to the left side of the coding block, or may further refer to the reference row or the reference column adjacent to the other edge of the coding block, and it should be noted that this is not particularly limited in the present embodiment. For convenience of explanation, in the present embodiment, the reference row adjacent to the coding block will be described as the reference row adjacent to the upper side, and the reference column adjacent to the coding block will be described as the reference column adjacent to the left side.

[0041] Here, the reference pixel points in the reference row adjacent to the coding block may include reference pixel points adjacent to the upper edge and the upper right edge (which may also be referred to as adjacent reference pixel points corresponding to the upper edge and the upper right edge), where the upper edge represents the upper edge of the coding block, and the upper right edge represents the length of the edge that extends horizontally to the right from the upper edge of the coding block and has the same height as the current coding block; and the reference pixel points in the reference column adjacent to the coding block may further include reference pixel points adjacent to the left edge and the lower left edge (which may also be referred to as adjacent reference pixel points corresponding to the left edge and the lower left edge), where the left edge represents the left edge of the coding block, and the lower left edge represents the length of the edge that extends vertically downward from the left edge of the coding block and has the same width as the current decoding block, although this is not particularly limited in the present embodiment.

[0042] In this way, for INTRA_L_CCLM mode, if the left adjacent area and the lower left adjacent area are valid areas, the first reference pixel set can be formed by reference pixel points in a reference column adjacent to the coding block, and for INTRA_T_CCLM mode, if the upper adjacent area and the upper right adjacent area are valid areas, the first reference pixel set can be formed by reference pixel points in a reference row adjacent to the coding block.

[0043] In S502, if the number of valid pixel points in the first reference pixel set is smaller than the preset number, the preset component value is used as the predicted value corresponding to the image component to be predicted.

[0044] It should be noted that the number of valid pixel points can be determined according to the validity of adjacent regions, or according to the number of valid pixel points in the selected region. In some special cases, such as in the case of a boundary of a coding block, when it is unpredictable, or when adjacent reference pixel points cannot be obtained due to the coding order, and when dividing the coding block according to tiles and slices, the left adjacent region, the lower left adjacent region, the upper adjacent region, and the upper right adjacent region may not all be valid regions, and there may be invalid regions, so that the number of valid pixel points in the selected region is smaller than the preset number, and the number of valid pixel points in the first reference pixel set is smaller than the preset number.

[0045] Furthermore, the number of presets is a predetermined determined value of the number of valid pixel points, which is used to determine whether the image component to be predicted is to be used to perform the steps of deriving model parameters and constructing a prediction model, where the number of presets may be four, but is not particularly limited in the present embodiment. In this way, assuming that the number of presets is four, that is, if the number of valid pixel points in the first reference pixel set is 0 or 2, the component values ​​of the presets can be directly used as predicted values ​​corresponding to the image component to be predicted, thereby reducing the complexity of calculation.

[0046] Furthermore, the preset component value is used to represent a fixed value (which may also be referred to as a default value) corresponding to a predetermined predicted image component. Here, the preset component value mainly relates to bit information of a current video image. Therefore, in some embodiments, for S502, if the number of valid pixel points in the first reference pixel set is smaller than the preset number, using the preset component value as a predicted value corresponding to the predicted image component may include the following steps:

[0047] In S502a, a preset component range corresponding to the predicted image component is determined based on bit information of the video image.

[0048] In S502b, an intermediate value of the preset component range is determined according to the preset component range, and the intermediate value is used as a predicted value corresponding to the predicted image component, where the intermediate value is indicated in the preset component value.

[0049] It should be noted that in this embodiment, the intermediate value of the preset component range corresponding to the predicted image component can be used as the preset component value, and then used as the predicted value corresponding to the predicted image component. Here, assuming that the bit depth of the predicted image component is represented by BitDepthC, it can be obtained that the calculation method of the intermediate value of the predicted image component is 1<<(BitDepthC-1), and this calculation method can be set according to actual situations and is not particularly limited in this embodiment.

[0050] For example, taking the predicted image component as a chrominance component, if the current video image is an 8-bit video, the component range corresponding to the chrominance component is 0 to 255, where the intermediate value is 128, and in this case, the preset component value may be 128, i.e., the default value may be 128. If the current video image is a 10-bit video, the component range corresponding to the chrominance component is 0 to 1023, where the intermediate value is 512, and in this case, the preset component value may be 512, i.e., the default value is 512. In this embodiment, the bit information of the video image is taken as 10 bits, and the preset component value is 512.

[0051] Furthermore, in some embodiments, after using the preset component values ​​as predicted values ​​corresponding to the predicted image components in S502, the method may further include the following steps:

[0052] At S502c, for each pixel point in the coding block, the preset component values ​​are used to perform predicted value filling for the predicted image component of each pixel point.

[0053] It should be noted that when the number of valid pixel points in the first reference pixel set is smaller than the preset number, the fixed default value is directly used to perform filling of the predicted value for the predicted image component in the coding block without the need to add additional processing modules.

[0054] For example, assuming that the preset component value is 512 and the predicted image component is a chrominance component, for the chrominance predicted value corresponding to each pixel point in the coding block, 512 can be directly used to fill in the chrominance predicted value.

[0055] In S503, if the number of valid pixel points in the first reference pixel set is greater than or equal to a preset number, the first reference pixel set is screened to obtain a second reference pixel set.

[0056] In the first parameter pixel set, there may be some unimportant reference pixel points (for example, the relevance of these reference pixel points is poor) or some abnormal reference pixel points. In order to ensure the accuracy of the prediction model, these reference pixel points need to be deleted to obtain the second reference pixel set, where the number of effective pixel points in the second reference pixel set is less than or equal to the preset number. Here, in practical applications, the number of effective pixel points included in the second reference pixel set is usually selected as four, but is not particularly limited in the present embodiment.

[0057] Furthermore, if the number of valid pixel points in the first reference pixel set is greater than or equal to the preset number, the first reference pixel set can also be screened to obtain a second reference pixel set, and after obtaining the second reference pixel set, it is still necessary to make a decision according to the number of valid pixel points in the second reference pixel set and the number of presets. Here, if the number of valid pixel points in the second reference pixel set is less than the number of presets, the component value of the preset can be adopted and used as the predicted value corresponding to the image component to be predicted; if the number of valid pixel points in the second reference pixel set is equal to the number of presets, the model parameters can be derived according to the second reference pixel set.

[0058] Further, in some embodiments, for S503, screening the first set of reference pixels to obtain a second set of reference pixels further comprises: determining a selected pixel point location based on pixel locations and / or image component intensities corresponding to each neighboring reference pixel point in the first reference pixel set; According to the determined selected pixel point position, selecting an effective pixel point corresponding to the selected pixel point position from the first reference pixel set, and forming a second reference pixel set with the effective pixel points obtained by selection, wherein the number of effective pixel points in the second reference pixel set is less than or equal to a preset number.

[0059] Specifically, the first reference pixel set may be screened according to the positions of the selected reference pixel points, or according to the image component intensities (luminance values, chromaticity values, etc.), thereby forming the second reference pixel set by the screened selected reference pixel points. The following description takes the positions of the selected reference pixel points as an example.

[0060] Assuming that the number of available pixel point samples in the upper and upper right regions adjacent to the current coding block is numSampT, and the number of available pixel point samples in the left and lower left regions adjacent to the current coding block is numSampL, the screening process is as follows (where availT represents the availability of the row adjacent to the top of the current coding block, availL represents the availability of the column adjacent to the left of the current coding block, nTbW represents the width of the current coding block, and nTbH represents the height of the current coding block):

[0061] If the intra prediction mode of the current block is INTRA_LT_CCLM mode, numSampT=availT?nTbW:0 numSampL=availL?nTbH:0, If not, numSampT=(availT&&predModeIntra==INTRA_T_CCLM)?(nTbW+Min(numTopRight,nTbH)):0 numSampL=(availL&&predModeIntra==INTRA_L_CCLM)?(nTbH+Min(numLeftBelow,nTbW)):0.

[0062] Here, numTopRight represents the number of valid pixel points in the upper right nTbW range, and numLeftBelow represents the number of valid pixel points in the lower left nTbH range. The number of pixel points screened on each edge is indicated by cntN, the start point position is indicated by startPosN, the selection interval is indicated by pickStepN, and the selected pixel point position is indicated by pickPosN[pos]. The derivation process is as follows:

[0063] The variable numIs4N indicates whether to screen the pixel points on one side: numIs4N=((availT&&availL&&predModeIntra==INTRA_LT_CCLM)?0:1) The variable startPosN represents the starting position: startPosN=numSampN>>(2+numIs4N) The variable pickStepN represents the selection interval: pickStepN=Max(1,numSampN>>(1+numIs4N)) Here, N is replaced with T and L, respectively, representing the case of screening pixel points on the top side and the case of screening on the left side, that is, N side here represents T side or L side. Here, when the availability of N side availN is TRUE and the selected intra mode predModeIntra is INTRA_LT_CCLM mode or INTRA_N_CCLM mode, the number of pixel points screened on N side cntN and the selected pixel point position pickPosN[pos] are as follows (it should be noted that the total number of pixel points screened should be cntT+cntL):

[0064] cntN=Min(numSampN,(1+numIs4N)<<1) pickPosN[pos]=(startPosN+pos*pickStepN),with pos=0...cntN-1 Otherwise, cntN is set to 0, that is, the number of screened pixel points is 0.

[0065] Assuming that the predicted samples of the current coding block are predSamples[x][y] with x=0...nTbW-1, y=0...nTbH-1, the derivation is as follows:

[0066] If numSampL and numSampT are both invalid, they will default to preset values, as follows:

[0067] predSamples[x][y]=1<<(BitDepth C -1) Otherwise, In the first step, obtain the luminance reconstruction samples pY[x][y] with x=0...nTbW*2-1, y=0...nTbH*2-1 of the same luminance block; In the second step, we obtain the adjacent luminance reconstruction samples pY[x][y], In the third step, obtain the downsampled luminance reconstruction samples pDsY[x][y] with x=0...nTbW-1, y=0...nTbH-1, In the fourth step, if numSampL is greater than 0, set the chromaticity value pSelC[idx] of the point selected by the left side to p[-1][pickPosL[idx]] with idx=0...cntL-1, and get the downsampled reconstructed luminance value pSelDsY[idx] with idx=0...cntL-1 of the point selected by the left side.

[0068] In the fifth step, if numSampT is greater than 0, set the chromaticity value pSelC[idx] of the point selected by the top side to p[pickPosT[idx-cntL]][-1] with idx=cntL...cntL+cntT-1, and get the downsampled reconstructed luminance value pSelDsY[idx] with idx=0...cntL+cntT-1 of the point selected by the top side.

[0069] In step 6, if cntT+cntL is different from 0, the derivation of variables minY, maxY, minC and maxC is as follows:

[0070] If cntT+cntL is equal to 2, then let pSelComp[3] be pSelComp[0], pSelComp[2] be pSelComp[1], pSelComp[0] be pSelComp[1], and pSelComp[1] be pSelComp[3], where Comp is replaced by DsY and C, respectively, to represent the reconstructed luma and chroma of the selected neighboring sample.

[0071] The derivation of the arrays minGrpIdx and maxGrpIdx is as follows:

[0072] minGrpIdx[0]=0 minGrpIdx[1]=2 maxGrpIdx[0]=1 maxGrpIdx[1]=3 If pSelDsY[minGrpIdx[0]] is greater than pSelDsY[minGrpIdx[1]], minGrpIdx[0] is swapped with minGrpIdx[1], (minGrpIdx[0],minGrpIdx[1])=Swap(minGrpIdx[0],minGrpIdx[1]) If pSelDsY[maxGrpIdx[0]] is greater than pSelDsY[maxGrpIdx[1]], then maxGrpIdx[0] is swapped with maxGrpIdx[1], (maxGrpIdx[0],maxGrpIdx[1])=Swap(maxGrpIdx[0],maxGrpIdx[1]) If pSelDsY[minGrpIdx[0]] is greater than pSelDsY[maxGrpIdx[1]], the array minGrpIdx is swapped with maxGrpIdx; (minGrpIdx,maxGrpIdx)=Swap(minGrpIdx,maxGrpIdx) If pSelDsY[minGrpIdx[1]] is greater than pSelDsY[maxGrpIdx[0]], minGrpIdx[1] is swapped with maxGrpIdx[0], (minGrpIdx[1],maxGrpIdx[0])=Swap(minGrpIdx[1],maxGrpIdx[0]) The calculations of the variables maxY, maxC, minY and minC are as follows (each representing the mean value of the two groups):

[0073] maxY=(pSelDsY[maxGrpIdx[0]]+pSelDsY[maxGrpIdx[1]]+1)>>1 maxC=(pSelC[maxGrpIdx[0]]+pSelC[maxGrpIdx[1]]+1)>>1 minY=(pSelDsY[minGrpIdx[0]]+pSelDsY[minGrpIdx[1]]+1)>>1 minC=(pSelC[minGrpIdx[0]]+pSelC[minGrpIdx[1]]+1)>>1 In the seventh step, the derivation process of the linear model parameters a, b and k is as follows (where a is the slope (the ratio of the chromaticity difference to the luminance difference), b is the intercept, and k is the shift of a, and a is stored as an integer):

[0074] If numSampL is equal to 0 and numSampT is equal to 0, k=0 a=0 b=1<<(BitDepth C -1) If not, diff=maxY-minY If diff is different from 0, diffC=maxC-minC x=Floor(Log2(diff)) normDiff=((diff<<4)>>x)&15 x+=(normDiff!=0)?1:0 y=Floor(Log2(Abs(diffC)))+1 a=(diffC*(divSigTable[normDiff]|8)+2y-1)>>y k=((3+xy)<1)?1:3+xy a=((3+xy)<1)?Sign(a)*15:a b=minC-((a*minY)>>k) Here, divSigTable[ ] is divSigTable[ ]={0,7,6,5,5,4,4,3,3,2,2,1,1,1,1,0}, Otherwise (if diff is equal to 0), k=0 a=0 b=minC In step 8, the chrominance prediction samples predSamples[x][y] with x=0...nTbW-1, y=0...nTbH-1 are obtained via the following calculation (where Clip1C limits the predicted values ​​between 0 and 1023): predSamples[x][y]=Clip1C(((pDsY[x][y]*a)>>k)+b)

[0075] JPEG2025148530000006.jpg49170

[0076] JPEG2025148530000007.jpg99170

[0077] JPEG2025148530000008.jpg85170

[0078] JPEG2025148530000009.jpg86170

[0079] In this way, a second reference pixel set can be obtained by screening the first reference pixel set for cases where the number of valid pixel points in the first reference pixel set is greater than or equal to a preset number, and the second reference pixel set includes four valid pixel points.

[0080] In S504, if the number of valid pixel points in the second reference pixel set is smaller than the preset number, the preset component value is used as the predicted value corresponding to the image component to be predicted.

[0081] In S505, if the number of effective pixel points in the second reference pixel set is equal to the number of presets, model parameters are determined through the second reference pixel set, and a prediction model corresponding to the predicted image component is obtained according to the model parameters.

[0082] It should be noted that after screening the first reference pixel set, a second reference pixel set is obtained. The number of effective pixel points in the second reference pixel set may be less than the number of presets, or greater than or equal to the number of presets. If the number of effective pixel points in the second reference pixel set is less than the number of presets, the component values ​​of the presets are directly used as predicted values ​​corresponding to the image components to be predicted. If the number of effective pixel points in the second reference pixel set is greater than or equal to the number of presets, model parameters are determined through the second reference pixel set, and a prediction model corresponding to the image components to be predicted is obtained according to the model parameters. Note that, since the number of reference pixel points used to derive the model parameters is usually four, the second reference pixel set obtained by screening is either less than the number of presets (the second reference pixel set is less than four effective pixel points) or equal to the number of presets (the second reference pixel set includes four effective pixel points).

[0083] Furthermore, it should be noted that the prediction model may be a linear model or a nonlinear model. Here, the nonlinear model may be a nonlinear form such as a quadratic curve, or a nonlinear form formed by multiple linear models. For example, the cross-component prediction technology of multi-model CCLM (MMLM: Multiple Model CCLM) is a nonlinear form formed by multiple linear models, and is not particularly limited in the present embodiment. Here, the prediction model can be used to perform a prediction process on the image component to be predicted and obtain a predicted value corresponding to the image component to be predicted.

[0084] After obtaining the second reference pixel set, if the number of valid pixel points in the second reference pixel set is equal to the preset number, the model parameters can be determined according to the second reference pixel set. After deriving the model parameters, a prediction model corresponding to the chrominance component can be further obtained according to the model parameters as shown in Equation (1), and then the prediction model is used to perform a prediction process on the chrominance component to obtain a predicted value corresponding to the chrominance component.

[0085] Further, in some embodiments, for S505, after obtaining a prediction model corresponding to the predicted image component according to the model parameters, the method may further include: The method may further include performing a prediction process on predicted image components of each pixel point in the encoding block based on the prediction model to obtain predicted values ​​corresponding to the predicted image components of each pixel point.

[0086] It should be noted that when the number of valid pixel points in the first reference pixel set is greater than or equal to the preset number, in order to obtain a predicted value corresponding to the predicted image component of each pixel point in the coding block, it is necessary to determine model parameters (e.g., α and β) through the first reference pixel set, and then obtain a prediction model corresponding to the predicted image component according to the model parameters. For example, assuming that the predicted image component is a chrominance component, it is possible to obtain a prediction model corresponding to the chrominance component shown in Equation (1) according to the model parameters α and β, and then perform a prediction process on the chrominance component of each pixel point in the coding block using the prediction model shown in Equation (1), thereby obtaining a predicted value corresponding to the chrominance component of each pixel point.

[0087] In some embodiments, the left adjacent region, the lower left adjacent region, the upper adjacent region, and the upper right adjacent region may have valid regions and invalid regions, so that the number of valid pixel points selected from the adjacent regions may be smaller than a preset number. Therefore, in some embodiments, referring to FIG. 7, an exemplary flowchart of a method for predicting another image component according to an embodiment of the present invention is shown. As shown in FIG. 7, after S501, the method may further include the following steps:

[0088] In S701, the number of valid pixel points in the first reference pixel set is determined, and it is determined whether the number of valid pixel points is smaller than a preset number.

[0089] Furthermore, after S503, the method may further include the following steps:

[0090] In S702, it is determined whether the number of valid pixel points in the second reference pixel set is smaller than a preset number.

[0091] It should be noted that the determination of the number of valid pixel points can be determined according to the effectiveness of the neighboring region. After determining the number of valid pixel points in this way, by comparing the number of valid pixel points with a preset number, if the number of valid pixel points in the first reference pixel set is less than the preset number, execute step S502; if the number of valid pixel points in the second reference pixel set is less than the preset number, execute step S504; if the number of valid pixel points in the second reference pixel set is greater than or equal to the preset number, execute step S505.

[0092] Furthermore, it should be noted that the number of presets can be 4. The following will be described in detail taking the number of presets as 4 as an example.

[0093] In one possible embodiment, if the number of effective pixel points in the first reference pixel set is greater than or equal to the preset number, since the reference pixel points used to derive the model parameters are usually four, the first reference pixel set is first screened to make the number of effective pixel points in the first reference pixel set four, and then model parameters are derived according to the four effective pixel points, and a prediction model corresponding to the image component to be predicted is obtained according to the model parameters, and a predicted value corresponding to the image component to be predicted is obtained.

[0094] Specifically, assume that the image components to be predicted are chrominance components, and that the chrominance components are predicted via the luminance component. Assume that the numbers of the four effective pixel points selected by screening are 0, 1, 2, and 3, respectively. By comparing the four selected effective pixel points, two pixel points with relatively large luminance values ​​(which may include the pixel point with the largest luminance value and the pixel point with the second largest luminance value) and two pixel points with relatively small luminance values ​​(which may include the pixel point with the smallest luminance value and the pixel point with the second smallest luminance value) can be further selected based on the four comparisons. Furthermore, two arrays, minIdx[2] and maxIdx[2], are set to store two groups of pixel points, respectively. Initially, the effective pixel points numbered 0 and 2 are first entered into minIdx[2], and the effective pixel points numbered 1 and 3 are entered into maxIdx[2], as follows:

[0095] Init:minIdx[2]={0,2},maxIdx[2]={1,3} Then, through four comparisons, the two pixel points with relatively small luminance values ​​are stored in minIdx[2], and the two pixel points with relatively large luminance values ​​are stored in maxIdx[2], as follows:

[0096] Step 1: if(L[minIdx[0]]>L[minIdx[1]],swap(minIdx[0],minIdx[1]) Step 2: if(L[maxIdx[0]]>L[maxIdx[1]],swap(maxIdx[0],maxIdx[1]) Step 3: if(L[minIdx[0]]>L[maxIdx[1]],swap(minIdx,maxIdx) Step 4: if(L[minIdx[1]]>L[maxIdx[0]],swap(minIdx[1],maxIdx[0]) In this way, two pixel points with relatively small brightness values ​​can be obtained, and the corresponding brightness values ​​can be expressed as luma 0 min and luma 1 minand the corresponding chromaticity values ​​are 0 min and chroma 1 min At the same time, two pixels with relatively large luminance values ​​can be obtained, and the corresponding luminance values ​​are respectively represented as luma 0 max and luma 1 max and the corresponding chromaticity values ​​are 0 max and chroma 1 max Furthermore, the luminance values ​​corresponding to two relatively small pixel points can be averaged to obtain the luminance value corresponding to the first average point, and the luminance value corresponding to the first average point can be calculated as follows: min The luminance values ​​corresponding to the two larger pixel points can be averaged to obtain the luminance value corresponding to the second average point. max Similarly, we can obtain the chromaticity values ​​corresponding to the two average points, which are chroma min and chroma max Specifically, it is as follows:

[0097] luma min =(luma 0 min +luma 1 min +1)>>1 luma max =(luma 0 max +luma 1 max +1)>>1 chroma min =(chroma 0 min +chroma 1 min +1)>>1 chroma max =(chroma 0 max +chroma 1 max +1)>>1 In other words, the average value of the two (luma min ,chroma min) and (luma max ,chroma max After obtaining the model parameters, the model parameters can be obtained by using these two points in a calculation manner in which two points determine a line. Specifically, the model parameters α and β can be calculated using Equation (2).

number

[0098] Here, the model parameter α is the slope in the prediction model, and the model parameter β is the intercept in the prediction model. After deriving the model parameters in this way, a prediction model corresponding to the chrominance component can be obtained according to the model parameters as shown in Equation (1), and then the prediction model is used to perform a prediction process on the chrominance component to obtain a predicted value corresponding to the chrominance component.

[0099] In another possible embodiment, for some special cases, such as in the case of the boundary of the coding block, when it is not possible to predict, and when adjacent reference pixel points cannot be obtained due to the coding order, and further, when dividing the coding block according to tiles and slices, the left adjacent area, the lower left adjacent area, the upper adjacent area, and the upper right adjacent area may not all be valid areas, and there may be invalid areas, thereby making the number of valid pixel points in the first reference pixel set smaller than the preset number.

[0100] In this way, since the number of presets is four, in some embodiments, for S502, when the number of valid pixel points in the first reference pixel set is smaller than the number of presets, using the component value of the preset as the predicted value corresponding to the image component to be predicted is: If the number of valid pixel points in the first reference pixel set is 0 or 2, a preset component value may be used as a predicted value corresponding to the image component to be predicted.

[0101] In some embodiments, for S504, if the number of valid pixel points in the current second reference pixel set is smaller than the preset number, using the preset component value as the predicted value corresponding to the predicted image component includes: If the number of valid pixel points in the second reference pixel set is 0 or 2, a preset component value may be used as a predicted value corresponding to the image component to be predicted.

[0102] In other words, when the number of presets is four, even if the number of valid pixel points in the first reference pixel set is smaller than the number of presets, or even if the number of valid pixel points in the second reference pixel set is smaller than the number of presets, the number of valid pixel points is either 0 or 2.

[0103] Specifically, if the sum of the adjacent reference pixel points in the selection area used for the coding block is 0, select an effective pixel point of 0. In the following three special cases, an effective pixel point of 0 is obtained.

[0104] JPEG2025148530000011.jpg33170

[0105] JPEG2025148530000012.jpg34170

[0106] JPEG2025148530000013.jpg34170

[0107] It should be further noted that whether the valid pixel point is 0 is determined according to the validity of the neighboring region, that is, the number of valid pixel points in the first reference pixel set can be determined according to the validity of the neighboring region. If the number of valid pixel points is 0, the model parameter α can be set to 0, and the model parameter β can be set to a preset component value corresponding to the image component to be predicted.

[0108] JPEG2025148530000014.jpg80170

[0109] JPEG2025148530000015.jpg59170

[0110] JPEG2025148530000016.jpg46170

[0111] JPEG2025148530000017.jpg40170

[0112] JPEG2025148530000018.jpg41170

[0113] It should be further noted that the number of valid pixel points is two, and can be determined according to the validity of the neighboring region, the number of valid pixel points in the selected region, or other criteria, and is not particularly limited in this embodiment. In this way, the number of valid pixel points in the first reference pixel set can be determined according to the validity of the neighboring region.

[0114] In the prior art technical solution, when there are two effective pixel points, four pixel points need to be obtained by duplicating the two effective pixel points. For example, assuming that the four pixel points are numbered 0, 1, 2, and 3, number 0 is the second effective pixel point selected, number 1 is the first effective pixel point selected, number 2 is the second effective pixel point selected, and number 3 is the first effective pixel point selected. According to the four pixel points numbered 0, 1, 2, and 3, the model parameters α and β can be determined to establish the prediction model shown in Equation (1), and a predicted value corresponding to the image component to be predicted can be obtained through the prediction model.

[0115] JPEG2025148530000019.jpg75170

[0116] Therefore, in the prior art technical solution, when the number of effective pixel points is two, an additional "duplication" operation is required to use the same processing module to obtain four pixel points, thereby deriving model parameters according to the same operation process as when the number of effective pixel points is four, and the additional "duplication" operation can be added. The four obtained pixel points still require four comparisons and four average calculations, thereby increasing the calculation complexity. In the present embodiment, the processing when the number of effective pixel points is two is matched with the processing when the number of effective pixel points is zero, and in this case, the same processing module can be directly used without adding any additional operations, thereby reducing the calculation complexity.

[0117] 10 illustrates an exemplary flowchart for deriving model parameters according to an embodiment of the present invention. In FIG. 10, assuming that the image component to be predicted is a chrominance component, first, neighboring reference pixel points are obtained from a selected region to form a first neighboring reference pixel set, and then the number of valid pixel points in the first neighboring reference pixel set is determined. If the number of valid pixel points is greater than or equal to four, a screening process is performed on the first reference pixel set to obtain a second reference pixel set, and then the number of valid pixel points in the second neighboring reference pixel set is determined. If the number of valid pixel points in the first reference pixel set or the second reference pixel set is zero, the model parameter α is set to zero, and the model parameter β is set to a default value. In this case, the predicted value corresponding to the chrominance component is filled with the default value. If the number of valid pixel points in the first reference pixel set or the second reference pixel set is two, the processing steps are the same as those when the number of valid pixel points is zero. For example, if the number of valid pixel points in the second reference pixel set is four, two pixel points with relatively large chrominance components and two pixel points with relatively small chrominance components are first obtained through four comparisons, and then the two average points are obtained. Based on the two average points, model parameters α and β are derived, and chrominance component prediction processing is performed according to the constructed prediction model. Therefore, only for coding blocks with four valid pixel points in the second reference pixel set, model parameters in CCLM mode can be derived. For coding blocks with less than four valid pixel points, a default value filling method is directly used, thereby reducing computational complexity when the number of reference pixel points in the selected region is four or less, and maintaining essentially unchanged encoding and decoding performance.

[0118] In this embodiment, the model parameter derivation process is integrated. That is, for the number of effective pixel points in a first reference pixel set used to derive the model parameters, if the number of effective pixel points in the first reference pixel set is greater than or equal to a preset number, a second reference pixel set is obtained by screening the effective pixel points in the first reference pixel set, and then the number of effective pixel points in a second adjacent reference pixel set is determined. If the number of effective pixel points in the second reference pixel set meets the preset number, the current coding block needs to perform the steps of deriving model parameters in CCLM and constructing a prediction model. If the number of effective pixel points in the first reference pixel set or the second reference pixel set is less than the preset number, the current coding block can use default values ​​to fill in the predicted values ​​corresponding to the predicted image components of the coding block. Therefore, as shown in FIG. 11, this embodiment can further provide a simplified process for deriving model parameters.

[0119] Compared with Figure 10, the model parameter derivation process shown in Figure 11 is more streamlined. In Figure 11, assuming that the image component to be predicted is a chrominance component and the preset component value is 512, first, neighboring reference pixel points are obtained from the selected region to form a first neighboring reference pixel set, then the number of valid pixel points in the first neighboring reference pixel set is determined, and if the number of valid pixel points in the first reference pixel set is greater than or equal to the preset number, a screening process is performed on the first reference pixel set to obtain a second reference pixel set. Then, the number of valid pixel points in the second neighboring reference pixel set is determined, and if the number of valid pixel points in the first reference pixel set or the second reference pixel set is less than the preset number, the model parameter α is set to 0 and the model parameter β is set to 512. In this case, the predicted value corresponding to the chrominance component is filled in 512. If the number of valid pixel points in the second reference pixel set satisfies the preset number, first, two pixel points of the relatively large chrominance component and two pixel points of the relatively small chrominance component are obtained by four comparisons, and then the two average points are obtained. Based on the two average points, model parameters α and β are derived, and chrominance component prediction processing is performed according to the constructed prediction model. Only for coding blocks whose number of valid pixel points in the second reference pixel set satisfies the preset number, model parameter derivation in CCLM mode can be performed. For coding blocks whose number of valid pixel points is less than the preset number, the default value filling method is used directly, which can reduce calculation complexity when the number of reference pixel points in the selected region is less than the preset number, and furthermore, can maintain essentially unchanged encoding and decoding performance. Typically, the number of presets in this embodiment can be four.

[0120] Furthermore, in this embodiment, the number of valid pixel points in the first reference pixel set can be determined according to the number of valid pixel points in the selected region, so as shown in Figure 12, this embodiment can further provide a simplified process for deriving other model parameters.

[0121] 12, assuming that the image component to be predicted is a chrominance component and the preset component value is 512, a selection region is first determined to obtain a first reference pixel set, and then the number of valid pixel points in the first reference pixel set is determined. If the number of valid pixel points in the first reference pixel set is greater than or equal to the preset number, a screening process is performed on the first reference pixel set to obtain a second reference pixel set. Then, the number of valid pixel points in a second adjacent reference pixel set is determined. If the number of valid pixel points in the first reference pixel set or the second reference pixel set is less than the preset number, the predicted value corresponding to the chrominance component is filled in 512. If the number of valid pixel points in the second reference pixel set meets the preset number, two relatively large pixel points and two relatively small pixel points of the chrominance component are first obtained by four comparisons, and then the two average values ​​are obtained. Based on the two average values, model parameters α and β are derived, and a prediction process for the chrominance component is performed according to the constructed prediction model. Therefore, the model parameter derivation in CCLM mode can be performed only for the coding blocks whose number of valid pixel points in the second reference pixel set satisfies the preset number, and for the coding blocks whose number of valid pixel points is less than the preset number, the default value is used directly to fill in the selected region, thereby reducing the calculation complexity when the number of reference pixel points in the selected region is less than the preset number and maintaining essentially unchanged encoding and decoding performance. Typically, the number of presets in this embodiment may be four.

[0122] JPEG2025148530000020.jpg123170

[0123] Furthermore, VVC defines the case where the variables numSampL and numSampT are both 0 (in this case, the number of effective pixel points to be screened and used to derive the model parameters can be 0), and the predicted value corresponding to the chromaticity component is directly set to the default value; otherwise, the model parameters need to be derived, specifically as follows:

[0124] if(numSampL==0&&numSampT==0) setting the predicted values ​​corresponding to the chrominance components to default values; else The model parameters are derived, and the constructed prediction model is used to predict the chrominance components to obtain predicted values ​​corresponding to the chrominance components.

[0125] JPEG2025148530000021.jpg55170

[0126] if(numSampL+numSampT<number of presets) setting the predicted values ​​corresponding to the chrominance components to default values; else The model parameters are derived, and the constructed prediction model is used to predict the chrominance components to obtain predicted values ​​corresponding to the chrominance components.

[0127] This embodiment obtains a first reference pixel set corresponding to a predicted image component of a coding block in a video image, and if the number of valid pixel points in the first reference pixel set is less than a preset number, uses the preset component values ​​as predicted values ​​corresponding to the predicted image component; if the number of valid pixel points in the first reference pixel set is greater than or equal to the preset number, screens the first reference pixel set to obtain a second reference pixel set, and the number of valid pixel points in the second reference pixel set is less than or equal to the preset number; if the number of valid pixel points in the second reference pixel set is less than the preset number, uses the preset component values ​​as predicted values ​​corresponding to the predicted image component; If the number of effective pixel points in the adjacent reference pixel set is equal to the preset number, model parameters are determined through a second reference pixel set, and a prediction model corresponding to the image component to be predicted is obtained according to the model parameters. The prediction model is used to perform prediction processing on the image component to be predicted and obtain a predicted value corresponding to the image component to be predicted. In this way, the derivation process of the model parameters is unified on the premise that the encoding and decoding prediction performance is not changed. At the same time, when the number of effective pixel points in the adjacent reference pixel set is less than the preset number, or when there are 0 or 2 effective pixel points, no additional processing module is added, so no additional processing is required and the calculation complexity is reduced.

[0128] In another embodiment of the present application, when the number of valid pixel points in the first reference pixel set is less than the preset number, the CCLM mode can be directly disabled, and the component value of the preset can be used as the predicted value corresponding to the predicted image component. Thus, in some embodiments, after screening the first reference pixel set to obtain a second reference pixel set, the method includes: If the number of valid pixel points in the first reference pixel set is smaller than a preset number, or if the number of valid pixel points in the second reference pixel set is smaller than a preset number, using a preset component value as a predicted value corresponding to the image component to be predicted; The method further includes: if the number of valid pixel points in the second reference pixel set is greater than or equal to the preset number, adopting a CCLM mode to realize prediction processing for the image component to be predicted.

[0129] It should be noted that when the number of valid pixel points in the first reference pixel set or the second reference pixel set is smaller than the preset number, in this case, the CCLM mode can be disabled, for example, the identifier for whether to use the CCLM mode is set to "disable CCLM mode", in which case the predicted value corresponding to the image component to be predicted is directly filled with the default value, and only when the number of valid pixel points in the second reference pixel set is greater than or equal to the preset number, the CCLM mode is used, for example, the identifier for whether to use the CCLM mode is set to "enable CCLM mode", in which case prediction processing for the image component to be predicted can be realized through the CCLM mode.

[0130] Furthermore, assuming that the predicted image components are chromaticity components and the number of presets is four, for all cases where two valid pixel points may be generated (here, the determination method for generating two valid pixel points is not particularly limited in the present embodiment), it is further possible to set the model parameter α to 0 and set the model parameter β to an intermediate value (which may also be referred to as a default value) corresponding to the chromaticity component, thereby filling the predicted values ​​corresponding to the chromaticity components of all pixel points in the coding block with the default value; further, it is further noted that for all cases where two valid pixel points may be generated, it is further possible to set both numSampL and numSampT to 0, thereby filling the predicted values ​​corresponding to the chromaticity components of all pixel points in the coding block with the default value.

[0131] Furthermore, for all cases that may produce two valid pixel points, the predicted values ​​corresponding to the chromaticity components may be directly filled with default values, or for all cases that may produce two valid pixel points, the CCLM mode may be disabled, or for all cases that may produce two or zero valid pixel points, the CCLM mode may be disabled, or for all cases that may produce two or zero valid pixel points, the predicted values ​​corresponding to the chromaticity components may be directly filled with default values.

[0132] Therefore, when the number of effective pixel points used for deriving the model parameters is different, the derivation process of the model parameters is unified. Specifically, when the number of effective pixel points is two, no additional processing is required, and the existing processing module is directly read (i.e., the processing when the number of effective pixel points is two is matched with the processing when the number of effective pixel points is zero), thereby reducing the computational complexity.

[0133] The image component prediction method in this example is based on the latest VVC reference software VTM5.0, and under all intra-frame conditions, the test sequence required for JVET conforms to general test conditions. The average BD-rate changes for the Y, Cb, and Cr components are 0.00%, 0.02%, and 0.02%, respectively, which indicates that there is essentially no impact on encoding and decoding performance.

[0134] Assuming that it does not affect the encoding and decoding performance, this application can have the following beneficial effects:

[0135] First, the present application can unify the process of deriving model parameters in CCLM mode. In the prior art technical solutions, when there are two effective pixel points, an additional "duplication" operation needs to be performed to generate four usable pixel points, so that the same operation can be performed when there are four effective pixel points and further derive model parameters. However, the present application can reduce the additional "duplication" operation and simultaneously align the processing when the number of effective pixel points is two with the processing when the number of effective pixel points is zero. In these cases, the same processing module can be directly used without increasing additional operations, thereby unifying the process of deriving linear model parameters.

[0136] JPEG2025148530000022.jpg93170

[0137] This embodiment provides a method for predicting an image component. Through the technical solution of this embodiment, the number of effective pixel points in a first reference pixel set is compared with a preset number. If the number of effective pixel points in the first reference pixel set or the second reference pixel set is smaller than the preset number, the default value of the preset is directly used as the predicted value corresponding to the image component to be predicted. If the number of effective pixel points in the second reference pixel set is greater than or equal to the preset number, model parameters are determined according to the first reference pixel set to construct a prediction model for the predicted image component, thereby integrating the derivation process of the model parameters. Furthermore, when the number of effective pixel points in the first reference pixel set is smaller than the preset number, no additional processing modules are added, thereby reducing the complexity of calculation.

[0138] Based on the same inventive concept as the above embodiment, referring to Figure 13, an exemplary structural diagram of the configuration of an image component prediction device 130 according to the embodiment of the present application is shown. The image component prediction device 130 can include an acquisition unit 1301, a prediction unit 1302 and a screening unit 1303, where: The obtaining unit 1301 is configured to obtain a first set of reference pixels corresponding to a predicted image component of a coding block in a video image; the prediction unit 1302 is configured to use a preset component value as a prediction value corresponding to the image component to be predicted when the number of valid pixel points in the first reference pixel set is smaller than a preset number; The screening unit 1303 is configured to screen the first reference pixel set to obtain a second reference pixel set when the number of valid pixel points in the first reference pixel set is greater than or equal to a preset number, where the number of valid pixel points in the second reference pixel set is less than or equal to a preset number; The prediction unit 1302 is further configured to: when the number of effective pixel points in the second reference pixel set is smaller than a preset number, use the preset component value as a predicted value corresponding to the predicted image component; and when the number of effective pixel points in the second reference pixel set is equal to the preset number, determine model parameters through the second reference pixel set and obtain a prediction model corresponding to the predicted image component according to the model parameters, wherein the prediction model is used to realize a prediction process for the predicted image component and obtain a predicted value corresponding to the predicted image component.

[0139] In the above technical solution, the obtaining unit 1301 is specifically configured to obtain reference pixel points adjacent to at least one side of the coding block, where the at least one side includes the left side of the coding block and / or the top side of the coding block, and form a first reference pixel set corresponding to the predicted image component based on the reference pixel points.

[0140] In the above technical solution, the obtaining unit 1301 is specifically configured to obtain reference pixel points in a reference row or a reference column adjacent to the coding block, where the reference row is formed by a row adjacent to the upper edge and the upper right edge of the coding block, and the reference column is formed by a column adjacent to the left edge and the lower left edge of the coding block, and to form a first reference pixel set corresponding to the predicted image component based on the reference pixel points.

[0141] In the above technical solution, the screening unit 1303 is specifically configured to determine a selected pixel point position based on the pixel position and / or image component intensity corresponding to each adjacent reference pixel point in the first reference pixel set, select an effective pixel point corresponding to the selected pixel point position from the first reference pixel set according to the determined selected pixel point position, and form a second reference pixel set with the selected effective pixel points, wherein the number of effective pixel points in the second reference pixel set is less than or equal to a preset number.

[0142] In the above technical solution, referring to FIG. 13, the image component prediction device 130 further includes a determination unit 1304 configured to determine a preset component range corresponding to the predicted image component based on bit information of the video image, determine an intermediate value of the preset component range according to the preset component range, and use the intermediate value as a predicted value corresponding to the predicted image component, where the intermediate value is indicated by a preset component value.

[0143] In the above technical proposal, referring to FIG. 13, the image component prediction device 130 further includes a filling unit 1305, which is configured to, for each pixel point in the coding block, perform predicted value filling for the predicted image component of each pixel point using the preset component value.

[0144] In the above technical solution, the prediction unit 1302 is further configured to perform a prediction process on a predicted image component of each pixel point in the coding block based on the prediction model, to obtain a predicted value corresponding to the predicted image component of each pixel point.

[0145] In the above technical solution, the value of the number of presets is 4; and the prediction unit 1302 is further configured to use the preset component value as the predicted value corresponding to the image component to be predicted when the number of valid pixel points in the first reference pixel set is 0 or 2; Correspondingly, the prediction unit 1302 is further configured to use a preset component value as a prediction value corresponding to the image component to be predicted when the number of valid pixel points in the second reference pixel set is 0 or 2.

[0146] In the above technical solution, referring to FIG. 13 , the image component prediction device 130 further includes a judgment unit 1306 configured to use a preset component value as a prediction value corresponding to the image component to be predicted when the number of effective pixel points in the first reference pixel set is smaller than a preset number or when the number of effective pixel points in the second reference pixel set is smaller than a preset number, and to adopt a CCLM mode to realize prediction processing for the image component to be predicted when the number of effective pixel points in the second reference pixel set is greater than or equal to the preset number.

[0147] In this embodiment, it should be understood that a "unit" may be a part of a circuit, a part of a processor, a part of a program or software, etc., and may be modular or non-modular. Furthermore, each component in this embodiment may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The integrated unit described above may be realized in the form of hardware or in the form of a software functional module.

[0148] If the integrated unit is implemented in the form of a software functional module and is not sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this embodiment, in essence or a part that contributes to the prior art, or all or a part of the solution of this technology, can be embodied in the form of a software product, and the computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) or a processor to execute all or a part of the steps of the method described in this embodiment. The aforementioned storage medium includes various media that can store program code, such as a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0149] Therefore, this embodiment provides a computer storage medium, which stores an image component prediction program, and when executed by at least one processor, the image component prediction program implements the steps of the method described in any one of the above embodiments.

[0150] Based on the above combination of the image component prediction device 130 and the computer storage medium, referring to FIG. 14, a specific hardware structure of the image component prediction device 130 according to the embodiment of the present application is shown, which includes a network interface 1401, a memory 1402, and a processor 1403, and each component is coupled together via a bus system 1404. It can be understood that the bus system 1404 is used to realize the connection communication between these components. In addition to a data bus, the bus system 1404 includes a power bus, a control bus, and a status signal bus. However, for clarity of explanation, various buses are represented as the bus system 1404 in FIG. 14. Here, the network interface 1401 is configured to send and receive signals in the process of sending and receiving information to and from other external network elements, The memory 1402 is configured to store a computer program executable by the processor 1403; The processor 1403 is configured to execute the computer program to perform the following steps, which include: Obtaining a first set of reference pixels corresponding to a predicted image component of a coding block in a video image; If the number of valid pixel points in the first reference pixel set is less than a preset number, using a preset component value as a predicted value corresponding to the predicted image component; if the number of valid pixel points in the first reference pixel set is greater than or equal to a preset number, screening the first reference pixel set to obtain a second reference pixel set, where the number of valid pixel points in the second reference pixel set is less than or equal to a preset number; If the number of valid pixel points in the second reference pixel set is smaller than the number of presets, using the preset component values ​​as predicted values ​​corresponding to the predicted image component; and if the number of valid pixel points in the second reference pixel set is equal to the number of presets, determining model parameters via the second reference pixel set and obtaining a prediction model corresponding to the predicted image component according to the model parameters, wherein the prediction model is used to realize a prediction process for the predicted image component and obtain a predicted value corresponding to the predicted image component.

[0151] It should be understood that memory 1402 in this embodiment may be volatile or nonvolatile memory, or may include both volatile and nonvolatile memory. Nonvolatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory may be random access memory (RAM), used as an external cache. Various forms of RAM may be used, such as, by way of example and not limitation, static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchlink dynamic random access memory (SLDRAM), and direct memory bus random access memory (DRRAM). The memory 1402 of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0152] The processor 1403 may be an integrated circuit chip having signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit in hardware within the processor 1403 or by instructions in the form of software. The processor 1403 may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Each method, step, and logic block diagram disclosed in the embodiments of the present application can be realized or executed. The general-purpose processor may be a microprocessor, or the processor may be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application may be directly executed by a hardware decoding processor, or may be executed by a combination of hardware and software modules within the decoding processor. The software modules may be located in conventional storage media such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory 1402, and the processor 1403 reads the information in the memory 1402 and completes the steps of the method in combination with the hardware.

[0153] It will be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For a hardware implementation, the processing unit is implemented in one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processing (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field-Programmable Gate Arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units configured to perform the functions described herein, or a combination thereof.

[0154] For a software implementation, the techniques described herein may be implemented through modules (processes, functions, etc.) that perform the functions described herein. The software code may be stored in a memory and executed by a processor. The memory may be implemented within or external to the processor.

[0155] Illustratively, as another embodiment, the processor 1403 is further configured to execute the computer program to perform the steps of the method according to any one of the above embodiments.

[0156] 15 shows an exemplary structural diagram of an encoder according to an embodiment of the present invention. As shown in FIG. 15, the encoder 150 may include at least the image component prediction device 130 according to any one of the above embodiments.

[0157] 16, an exemplary structural diagram of a decoder configuration according to an embodiment of the present application is shown. As shown in FIG. 16, the decoder 160 may include at least the image component prediction device 130 described in any one of the above embodiments.

[0158] It should be noted that, as used herein, the terms "comprise," "include," or any other variation thereof are intended to have a non-exclusive inclusion, whereby a process, method, item, or apparatus comprising a set of elements not only includes those elements, but also includes other elements not expressly listed, or includes the inherent elements of those processes, methods, items, or apparatus. Without more limitation, an element qualified by the phrase "comprises ..." does not exclude the presence of other related elements in the process, method, item, or apparatus that includes that element.

[0159] The numbers of the above-mentioned embodiments of the present invention do not indicate the superiority or inferiority of the embodiments, but are used for the convenience of explanation.

[0160] The methods disclosed in several method embodiments according to the present application can be combined in any manner without conflict to obtain new method embodiments.

[0161] Features disclosed in several product embodiments according to this application may be combined in any non-conflicting manner to obtain new product embodiments.

[0162] Features disclosed in several method or apparatus embodiments according to the present application may be combined in any non-conflicting manner to obtain new method or apparatus embodiments.

[0163] The above are only specific embodiments of the present application, and the scope of protection of the present application is not limited thereto. Any modifications or replacements that can be easily conceived by those skilled in the art within the technical scope disclosed in the present application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application shall be subject to the scope of protection of the claims. [Industrial Applicability]

[0164] In an embodiment of the present application, a first reference pixel set corresponding to a predicted image component of a coding block in a video image is obtained, and if the number of valid pixel points in the first reference pixel set is smaller than a preset number, the preset component values ​​are used as predicted values ​​corresponding to the predicted image component; if the number of valid pixel points in the first reference pixel set is greater than or equal to the preset number, the first reference pixel set is screened to obtain a second reference pixel set, and if the number of valid pixel points in the second reference pixel set is smaller than or equal to the preset number, the preset component values ​​are used as predicted values ​​corresponding to the predicted image component; if the number of valid pixel points in the second reference pixel set is equal to the preset number, model parameters are determined via the second reference pixel set, and a prediction model corresponding to the predicted image component is obtained according to the model parameters, and the prediction model is used to predict the predicted image component. The prediction process is performed for the first reference pixel set to obtain a predicted value corresponding to the image component to be predicted. In this way, if the number of effective pixel points in the first reference pixel set is smaller than the preset number or if the number of effective pixel points in the second reference pixel set is smaller than the preset number, the preset default value is directly used as the predicted value corresponding to the image component to be predicted. Only if the number of effective pixel points in the second reference pixel set satisfies the preset number, model parameters are determined according to the first reference pixel set to establish a prediction model for the image component to be predicted, thereby integrating the derivation process of the model parameters. Furthermore, if the number of effective pixel points in the first reference pixel set or the second reference pixel set is smaller than the preset number, particularly if the effective pixel points is 0 or 2, no additional processing module is added, and the preset default value is directly used as the predicted value corresponding to the image component to be predicted. This reduces the complexity of calculation.

Claims

1. A method for predicting an image component, applied to a decoder, comprising: obtaining a first set of reference pixels corresponding to a predicted image component of a decoded block in a video image; If the number of valid pixel points in the first reference pixel set is equal to 0, using a preset component value as a predicted value corresponding to the predicted image component; If the number of valid pixel points in the first reference pixel set is greater than or equal to a preset number, screening the first reference pixel set to obtain a second reference pixel set, wherein the number of valid pixel points in the second reference pixel set is less than or equal to a preset number; When the number of valid pixel points in the second reference pixel set is equal to a preset number, determining model parameters through the second reference pixel set, and obtaining a prediction model corresponding to the predicted image component according to the model parameters, wherein the prediction model is used to realize a prediction process for the predicted image component and obtain a predicted value corresponding to the predicted image component; Screening the first set of reference pixels to obtain a second set of reference pixels includes: determining a selected pixel point position based on pixel positions corresponding to neighboring reference pixel points in the first reference pixel set; and selecting, according to the determined selected pixel point positions, effective pixel points corresponding to the selected pixel point positions from the first reference pixel set, and determining a second reference pixel set based on the effective pixel points obtained by the selection, wherein the number of effective pixel points in the second reference pixel set is less than or equal to a preset number.

2. Obtaining a first set of reference pixels corresponding to a predicted image component of a decoded block in the video image includes: Obtaining reference pixel points adjacent to at least one side of the decoded block, where the at least one side includes a left side of the decoded block and / or an upper side of the decoded block; determining a first set of reference pixels corresponding to the predicted image component based on the reference pixel points; The method for predicting image components according to claim 1 .

3. Obtaining a first set of reference pixels corresponding to a predicted image component of a decoded block in the video image includes: Obtaining reference pixel points in reference rows and / or reference columns adjacent to the decoding block, wherein the reference rows are formed by rows adjacent to an upper edge and an upper right edge of the decoding block, and the reference columns are formed by columns adjacent to a left edge and a lower left edge of the decoding block; determining a first set of reference pixels corresponding to the predicted image component based on the reference pixel points; The method for predicting image components according to claim 1 .

4. Using the preset component values ​​as predicted values ​​corresponding to the predicted image components includes: determining the preset component values ​​based on a bit depth of the video image; The method for predicting image components according to claim 1 .

5. The preset component value is 1<<(BitDepth-1), where BitDepth is the bit depth of the predicted image component. The method for predicting image components according to claim 4.

6. The method for predicting image components includes: and performing, for a pixel point in the decoding block, a fill-in of a predicted value for a predicted image component of the pixel point using the preset component value. The method for predicting image components according to claim 1 .

7. After obtaining a prediction model corresponding to the image component to be predicted according to the model parameters, the method for predicting the image component comprises: and performing a prediction process on predicted image components of pixel points in the decoding block based on the prediction model to obtain predicted values ​​corresponding to the predicted image components of the pixel points. The method for predicting image components according to claim 1 .

8. The preset number is 4. The method for predicting an image component according to any one of claims 1 to 7.

9. 1. A method for predicting image components applied to an encoder, comprising: obtaining a first set of reference pixels corresponding to a predicted image component of a coding block in a video image; If the number of valid pixel points in the first reference pixel set is equal to 0, using a preset component value as a predicted value corresponding to the predicted image component; If the number of valid pixel points in the first reference pixel set is greater than or equal to a preset number, screening the first reference pixel set to obtain a second reference pixel set, wherein the number of valid pixel points in the second reference pixel set is less than or equal to a preset number; When the number of valid pixel points in the second reference pixel set is equal to a preset number, determining model parameters through the second reference pixel set, and obtaining a prediction model corresponding to the predicted image component according to the model parameters, wherein the prediction model is used to realize a prediction process for the predicted image component and obtain a predicted value corresponding to the predicted image component; Screening the first set of reference pixels to obtain a second set of reference pixels includes: determining a selected pixel point position based on pixel positions corresponding to neighboring reference pixel points in the first reference pixel set; and selecting, according to the determined selected pixel point positions, effective pixel points corresponding to the selected pixel point positions from the first reference pixel set, and determining a second reference pixel set based on the effective pixel points obtained by the selection, wherein the number of effective pixel points in the second reference pixel set is less than or equal to a preset number.

10. Obtaining a first set of reference pixels corresponding to a predicted image component of a coding block in the video image includes: obtaining reference pixel points adjacent to at least one side of the coding block, wherein the at least one side includes a left side of the coding block and / or an upper side of the coding block; determining a first set of reference pixels corresponding to the predicted image component based on the reference pixel points; The method for predicting image components according to claim 9.

11. Obtaining a first set of reference pixels corresponding to a predicted image component of a coding block in the video image includes: Obtaining reference pixel points in reference rows and / or reference columns adjacent to the coding block, wherein the reference rows are formed by rows adjacent to an upper side and an upper right side of the coding block, and the reference columns are formed by columns adjacent to a left side and a lower left side of the coding block; determining a first set of reference pixels corresponding to the predicted image component based on the reference pixel points; The method for predicting image components according to claim 9.

12. Using the preset component values ​​as predicted values ​​corresponding to the predicted image components includes: determining the preset component values ​​based on a bit depth of the video image; The method for predicting image components according to claim 9.

13. The preset component value is 1<<(BitDepth-1), where BitDepth is the bit depth of the predicted image component. The method for predicting image components according to claim 12.

14. The method for predicting image components comprises: and performing, for a pixel point in the coding block, a fill-in of a predicted value for a predicted image component of the pixel point using the preset component value. The method for predicting image components according to claim 9.

15. After obtaining a prediction model corresponding to the image component to be predicted according to the model parameters, the method for predicting the image component comprises: and performing a prediction process on predicted image components of pixel points in the coding block based on the prediction model to obtain predicted values ​​corresponding to the predicted image components of the pixel points. The method for predicting image components according to claim 9.

16. The preset number is 4. The method for predicting an image component according to any one of claims 9 to 15.

17. 1. A decoder comprising a memory and a processor, the memory is configured to store a computer program executable by the processor; The decoder, wherein the processor, when executing the computer program, is configured to perform the method for predicting an image component according to any one of claims 1 to 7.

18. 1. An encoder comprising a memory and a processor, the memory is configured to store a computer program executable by the processor; The encoder, wherein the processor, when executing the computer program, is configured to perform the method for predicting an image component according to any one of claims 9 to 15.

19. 1. A computer-readable storage medium, comprising: A computer-readable storage medium having stored thereon a computer program which, when executed by at least one processor, causes the processor to perform the method for predicting image components according to any one of claims 1 to 7.

20. a computer-readable storage medium having a computer program and a bitstream stored thereon; The computer-readable storage medium, when the computer program is executed by at least one processor, causes the processor to perform the image component prediction method according to any one of claims 9 to 15 so as to generate the bitstream.

Images