Filtering method and device for cross-component prediction, storage medium and program product

Abstract

The embodiment of the invention provides a filtering method and device for cross-component prediction, a storage medium and a program product, relates to the technical field of video coding, and can improve the accuracy of cross-component prediction. The method comprises the following steps: acquiring a chroma prediction value of a target pixel block of cross-component nonlinear intra-frame prediction CCNPM in a video frame; and carrying out filtering processing on the chrominance prediction value through a preset intra-frame prediction filter (IPF) to obtain the filtered chrominance prediction value.

Description

Technical Field

[0001] This disclosure relates to the field of video coding technology, and in particular to a filtering method, device, storage medium, and program product for cross-component prediction. Background Technology

[0002] As video scenarios become more diverse, the amount of video data also increases. In order to improve video encoding efficiency, video data typically needs to undergo video encoding processes such as acquisition, prediction, transformation, and entropy coding to reduce the amount of video data.

[0003] Currently, in the process of encoding video data, the cross-component nonlinear intra prediction method (CCNPM) is usually used to predict the content of the current pixel block by utilizing the known information of neighboring pixel blocks. That is, in multi-component video signals, CCNPM can predict the chrominance component from the luma component based on the correlation between the chrominance component and the luma component, so as to achieve cross-component prediction.

[0004] However, in the aforementioned technical solutions, CCNPM only considers the luminance components of adjacent pixel blocks and the correlation between chrominance and luminance components when predicting the chrominance components of the current pixel block, resulting in low accuracy in cross-component prediction. Therefore, improving the accuracy of cross-component prediction has become an urgent technical problem to be solved. Summary of the Invention

[0005] This disclosure provides a filtering method, apparatus, storage medium, and program product for cross-component prediction, which can improve the accuracy of cross-component prediction.

[0006] On the one hand, a filtering method for cross-component prediction is provided, the method comprising: obtaining the chroma prediction value of the target pixel block of cross-component nonlinear intra-frame prediction CCNPM in a video frame; and filtering the chroma prediction value by a preset intra-frame prediction filter IPF to obtain the filtered chroma prediction value.

[0007] On the other hand, a filtering device for cross-component prediction is provided, the device comprising: an acquisition module and a processing module.

[0008] The acquisition module is used to acquire the chroma prediction values ​​of target pixel blocks in the video frame using cross-component nonlinear intra-frame prediction (CCNPM). The processing module is used to filter the chroma prediction values ​​using a preset intra-frame prediction filter (IPF) to obtain the filtered chroma prediction values.

[0009] In another aspect, an electronic device is provided, comprising: a memory and a processor. The memory and the processor are coupled. The memory is used to store a computer program. When the processor executes the computer program, it implements the filtering method for cross-component prediction of any of the above embodiments.

[0010] In another aspect, a computer-readable storage medium is provided, on which computer program instructions are stored, which, when executed by a processor, implement the filtering method for cross-component prediction of any of the above embodiments.

[0011] In another aspect, a computer program product is provided, comprising computer program instructions that, when executed, implement the filtering method for cross-component prediction of any of the above embodiments.

[0012] This disclosure presents an embodiment in which, based on CCNPM chroma prediction, filtering is performed using IPF to obtain more accurate chroma prediction values. In other words, to improve coding performance, the results of CCNPM prediction are filtered to enhance the spatial correlation of chroma components, thereby improving the accuracy of cross-component prediction. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in this disclosure, the accompanying drawings used in some embodiments of this disclosure will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings.

[0014] Figure 1 A schematic diagram illustrating a framework process for video encoding provided for some embodiments of this disclosure;

[0015] Figure 2 A schematic diagram of a video encoding and decoding framework provided for some embodiments of this disclosure;

[0016] Figure 3 A schematic diagram illustrating an example of a CCNPM provided for some embodiments of this disclosure;

[0017] Figure 4 This is a schematic diagram illustrating the positional relationship between pixel blocks provided in some embodiments of this disclosure;

[0018] Figure 5 A schematic diagram illustrating an example of CCNPM predicting the chromaticity value of a central block based on the luminance values ​​of surrounding blocks, provided for some embodiments of this disclosure;

[0019] Figure 6 A schematic diagram illustrating an example of IPF filtering provided in some embodiments of this disclosure;

[0020] Figure 7 A schematic diagram of a system architecture provided for some embodiments of this disclosure;

[0021] Figure 8 A flowchart illustrating a filtering method for cross-component prediction provided for some embodiments of this disclosure;

[0022] Figure 9 A schematic diagram illustrating the row / column index of a pixel block in the left and top directions, provided for some embodiments of this disclosure;

[0023] Figure 10 A schematic diagram illustrating the row / column index of a pixel block for some embodiments of this disclosure, showing its left / top / bottom left / top right orientation.

[0024] Figure 11 A schematic diagram of the structure of a filtering device for cross-component prediction provided for some embodiments of this disclosure. Figure 1 ;

[0025] Figure 12 A schematic diagram of the structure of a filtering device for cross-component prediction provided for some embodiments of this disclosure. Figure 2 . Detailed Implementation

[0026] The technical solutions of this disclosure will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0027] It should be noted that, in this disclosure, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in this disclosure should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0028] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0029] In the description of this disclosure, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. "And / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. Furthermore, "at least one" means one or more, and "more than one" means two or more.

[0030] As video scenarios become more diverse, the amount of video data also increases. In order to improve video encoding efficiency, video data typically needs to undergo video encoding processes such as acquisition, prediction, transformation, and entropy coding to reduce the amount of video data.

[0031] For example, such as Figure 1 The diagram illustrates the framework of video coding, specifically a block-based hybrid video coding and decoding framework. The original YUV (luminance, blue difference, and red difference) is compressed into video through several key modules: prediction, transform, quantization, entropy coding, bitrate control, and post-processing. Video compression primarily addresses temporal and spatial redundancy. The block-based hybrid video coding framework can be described as follows:

[0032] (1) First, divide the current block according to several partitioning types;

[0033] (2) Prediction is made based on the results of the partitioning, mainly involving intra-frame prediction and inter-frame prediction, which are respectively for removing spatial redundancy and temporal redundancy.

[0034] (3) For the reconstructed image obtained by prediction, the difference is calculated with the original image. That is, the residual is further reduced by transformation and quantization, and then binary encoding is performed by entropy coding.

[0035] (4) Finally, block effects and other problems are eliminated by post-processing modules such as deblocking filtering and sample adaptive offset.

[0036] For example, such as Figure 2 The diagram illustrates the framework of video encoding and decoding, representing the current video encoding and decoding framework of video encoding standards. The overall framework flow at the decoding end can be summarized as follows:

[0037] (1) First, decode the encoded binary bitstream (e.g., context-adaptive binary arithmetic coding (CABAC));

[0038] (2) Then, the decoded result is dequantized and inverse transformed;

[0039] (3) The prediction results based on the mode selection (such as motion compensation and intra-frame prediction) are added to the results after inverse quantization and inverse transformation to obtain the reconstructed image;

[0040] (4) Finally, the reconstructed image is post-processed, including deblocking filter (DBF), sample adaptive offset (SAO), adaptive loop filter (ALF), etc., and finally stored in the decoded image buffer to output the video signal.

[0041] It should be noted that, currently, whether it is the latest audio-video coding standard (AVS) 4 which is still in the exploratory stage, or H.267, versatile video coding (VVC), etc., they all use this block-based hybrid video coding framework.

[0042] Currently, video data encoding typically employs two-step cross-component prediction (TSCPM) for cross-component prediction. In AVS, the Intra Prediction Filter (IPF) was initially used for the luma component and later for the chroma component. For the chroma component, when the intra-component prediction mode is horizontal or TSCPM_L, a vertical 2-tap filter is used to filter the predicted value; when the intra-component prediction mode is vertical or TSCPM_T, a horizontal 2-tap filter is used. However, another cross-component prediction tool exists: the cross-component nonlinear intra prediction method (CCNPM). CCNPM, similar to TSCPM, also uses an upper and left template.

[0043] The following section introduces CCNPM with specific examples. Figure 3 As shown, it illustrates an example of CCNPM, including:

[0044] (1) The brightness of the current block and the adjacent template area ( Figure 3 The black area in the middle is downsampled to obtain downsampled brightness samples (i.e., downsampled brightness components).

[0045] The brightness is downsampled using the existing error vector magnitude (EVM) downsampling, as shown in Formula 1:

[0046]

[0047] (2) Based on the neighboring template, construct a cross-component prediction model (such as a nonlinear model) for luminance (Y) (i.e., downsampled luminance component) and chrominance (U / V) (i.e. chrominance component), and predict the chrominance result based on the model.

[0048] The selection of templates for neighboring blocks can be referenced as follows: Figure 4 The positional relationship between the pixel blocks shown is based on the current chroma block (i.e., the current pixel block): the upper left, upper, upper right, left, and lower left of the current block (i.e., the current pixel block) are selected to construct the template; the width w of area C is equal to the width w of the current block, and the height h of area E is equal to the height h of the current block; the template width θ is fixed at 6 here, and will be adaptively adjusted according to the availability of neighboring sample points; if the lower right corner of area C (area E) is not reconstructed or exceeds the image boundary, then area C (area E) is unusable.

[0049] For example, such as Figure 5 As shown, it illustrates an example of CCNPM predicting the chromaticity value of the central block based on the luminance values ​​of the surrounding blocks, including: the cross-component nonlinear prediction model selects the target chromaticity sample point, the associated position C in the downsampled luminance image, and the downsampled luminance sample points around it.

[0050] The specific nonlinear model structure is shown in Formula 2 below:

[0051]

[0052] Where C′ represents the target chromaticity sample point, p i These are the model parameters.

[0053] To reduce the complexity of template calculations, only a subset of sample points within the template region are used for calculating the cross-component nonlinear prediction model. Specifically, only a portion of the sample points are selected. Figure 5 Sample points in the template region whose horizontal and vertical coordinates satisfy the following constraint: neither the horizontal nor the vertical coordinates are odd numbers.

[0054] For example! (x%2==1&&y%2==1).

[0055] In addition, multiple equations can be constructed using a nonlinear model to solve a system of linear equations, thereby obtaining the model parameters. The model solution employs the LDL (Local Level Dictation) method, and the entire process utilizes integer-based computation.

[0056] (3) Based on the cross-component model, the predicted value of chromaticity (U / V) is obtained by inputting the downsampled luminance sample point corresponding to the current block in (1).

[0057] Furthermore, IPF addresses the issue that current intra-frame prediction often ignores the correlation between some reference pixels and the current prediction unit. Predictive filtering can effectively enhance spatial correlation, thereby improving intra-frame prediction accuracy. For example... Figure 6 As shown, the prediction direction is from the upper right to the lower left. The multi-resolution bitstream (MRB) reference pixels are mainly used to generate the current intra-prediction block. The left side of the prediction sample block has poor prediction performance because it does not consider the correlation with the universal serial bus request block (URB). To solve this problem, IPF uses reference pixels from the URB to filter the intra-prediction block. IPF filters include three types: horizontal 2-tap filters, vertical 2-tap filters, and 3-tap filters that filter both horizontally and vertically.

[0058] The algorithms for the above-mentioned horizontal 2-tap filter, vertical 2-tap filter, and 3-tap filter can be represented by the following formulas: Formula 3 (horizontal 2-tap filter), Formula 4 (vertical 2-tap filter), and Formula 5 (3-tap filter):

[0059] P′(x,y)=f(x)·P(-1,y)+(1-f(x))·P(x,y) Formula 3.

[0060] P′(x,y)=f(y)·P(x,-1)+(1-f(y))·P(x,y) Formula 4.

[0061] P′(x,y)=f(x)·P(-1,y)+f(y)·P(x,-1)+(1-f(x)-f(y))·P(x,y) Formula 5.

[0062] Wherein, P′(x,y) is used to indicate the predicted chroma value after filtering, f(x) is used to indicate the filtering parameters of the horizontal 2-tap filter, P(-1,y) is used to indicate the chroma value of the pixel block directly to the left of the current pixel block, P(x,y) is used to indicate the chroma value of the current pixel block, f(y) is used to indicate the filtering parameters of the vertical 2-tap filter, and P(x,-1) is used to indicate the chroma value of the pixel block directly above the current pixel block.

[0063] For the luminance component, a filter is selected from the intra-frame prediction modes to filter the current prediction value. A horizontal 2-tap filter is applied to the prediction mode closer to the vertical downward direction, a vertical 2-tap filter is applied to the prediction mode closer to the horizontal left direction, and a 3-tap filter is applied to the non-angular prediction mode and the lower right diagonal mode.

[0064] For the chroma component, when the intra-frame prediction chroma component prediction mode is horizontal or TSCPM_L, a vertical 2-tap filter is used to filter the predicted value; when the intra-frame prediction chroma component prediction mode is vertical or TSCPM_T, a horizontal 2-tap filter is used to filter the predicted value.

[0065] If the current intra-frame prediction block size is M×N, for a pixel with intra-block coordinates (i, j), its corresponding filter coefficients f(i) and f(j) are obtained by looking up table 1 from M, i and N, j respectively.

[0066] Table 1 Intra-frame prediction boundary filter coefficients

[0067]

[0068]

[0069] However, in the above technical solution, the pixel blocks of the video frame are not filtered after passing through CCNPM. In other words, CCNPM only refers to the luminance components of adjacent pixel blocks and the correlation between the chrominance components and the luminance components for predicting the chrominance components of the current pixel block, which results in low accuracy of cross-component prediction.

[0070] Therefore, how to improve the accuracy of cross-component prediction has become a technical problem that urgently needs to be solved.

[0071] To address the aforementioned technical problems, this disclosure provides a filtering method for cross-component prediction, applicable to video encoding and decoding scenarios. Based on CCNPM chroma prediction, filtering using IPF yields more accurate chroma prediction values. In other words, to improve coding performance, filtering the CCNPM prediction results enhances the spatial correlation of chroma components, thereby improving the accuracy of cross-component prediction.

[0072] The implementation environment of the embodiments of this disclosure is described below.

[0073] like Figure 7 The diagram shown is a schematic of a system architecture provided in an embodiment of this disclosure. The filtering device (such as electronic device 700) for cross-component prediction may include: an intra-frame chroma prediction module 701 and a filtering processing module 702.

[0074] The intra-frame chroma prediction module 701 can determine the chroma prediction value of a pixel block (such as a coding unit (CU)) based on CCNPM, and then pass the chroma prediction value to the filtering module 702 for filtering.

[0075] The filtering module 702 can filter the chroma prediction values ​​from the intra-frame chroma prediction module 701 based on the IPF to obtain the filtered chroma prediction values.

[0076] In other words, the embodiments of this disclosure focus on chroma prediction in intra-frame prediction. For the chroma prediction tool CCNPM, a filtering operation is added to improve spatial correlation and thus improve prediction accuracy.

[0077] It should be noted that, in the embodiments disclosed herein, the electronic device 700 may be a terminal or a server.

[0078] The server can be a single physical server, or a server cluster consisting of multiple servers. Alternatively, the server cluster can be a distributed cluster. Alternatively, the server can be a cloud server. This disclosure does not limit the specific implementation of the server.

[0079] A terminal can be a device with wireless transceiver capabilities. Terminals can be mobile phones, tablets, computers with wireless transceiver capabilities, virtual reality (VR) terminals, augmented reality (AR) terminals, wireless terminals in industrial control, wireless terminals in self-driving vehicles, wireless terminals in remote medical care, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, and so on. The embodiments of this disclosure do not limit the application scenarios. A terminal may also be referred to as a user, user equipment (UE), A-IoT device, access terminal, UE unit, UE station, mobile station, mobile station, remote station, transmitter, remote terminal, mobile device, UE terminal, wireless communication device, UE agent, or UE device, etc., and the embodiments of this disclosure do not limit this to these terms.

[0080] It should be noted that, Figure 7 This is just an example framework diagram. Figure 7The number of modules included, and the names of each module, are unlimited, except for... Figure 7 In addition to the modules shown, electronic devices may also include other modules, such as input modules and output modules.

[0081] The application scenarios of the embodiments disclosed herein are not limited. The system architecture and business scenarios described in the embodiments of this disclosure are for the purpose of more clearly illustrating the technical solutions of the embodiments of this disclosure, and do not constitute a limitation on the technical solutions provided by the embodiments of this disclosure. As those skilled in the art will know, with the evolution of system architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of this disclosure are also applicable to similar technical problems.

[0082] Figure 8 A flowchart illustrating a filtering method for cross-component prediction is shown, as follows: Figure 8 As shown, the method includes:

[0083] S801. Obtain the chromaticity prediction value of the target pixel block in the video frame using cross-component nonlinear intra-frame prediction.

[0084] The video frame can be any frame in the video to be encoded, and the target pixel block can be any pixel block in the video frame.

[0085] It should be noted that, in the embodiments of this disclosure, the chromaticity prediction mode of CCNPM for the target pixel block may include a first prediction mode and a second prediction mode. The first prediction mode is a mode that performs CCNPM based on the pixel block directly above the target pixel block (i.e., CCNPM_T), and the second prediction mode is a mode that performs CCNPM based on the pixel block directly to the left of the target pixel block (i.e., CCNPM_L).

[0086] In other words, the chromaticity prediction value of the target pixel block can be the prediction value corresponding to CCNPM_L, or the chromaticity prediction value of the target pixel block can be the prediction value corresponding to CCNPM_T.

[0087] It should be noted that the process for electronic devices to obtain the chromaticity prediction values ​​of target pixel blocks can be referred to the above. Figure 3 , Figure 4 and Figure 5 The description of CCNPM in the illustrated embodiments will not be repeated here.

[0088] S802. The chroma prediction value is filtered by a preset intra-frame prediction filter to obtain the filtered chroma prediction value.

[0089] In other words, after performing chromaticity prediction on the target pixel block based on CCNPM, the electronic device can further filter the predicted value using IPF to improve the accuracy of the chromaticity prediction.

[0090] It should be noted that, in the embodiments of this disclosure, the preset IPF used for filtering the chromaticity prediction value of CCNPM can be of various types, including at least one of the following (1)-(5):

[0091] (1) A horizontal 2-tap filter for horizontal direction filtering;

[0092] (2) Vertical 2-tap filter for vertical direction filtering;

[0093] (3) A 3-tap filter that filters both horizontal and vertical directions simultaneously;

[0094] (4) A newly constructed vertical 2-tap filter;

[0095] (5) Newly constructed horizontal 2-tap filter.

[0096] For the algorithms in the horizontal 2-tap filter, vertical 2-tap filter and 3-tap filter, please refer to Formulas 3, 4 and 5 shown above, which will not be elaborated here.

[0097] Furthermore, the algorithms for the newly constructed horizontal 2-tap filter and the newly constructed vertical 2-tap filter can be represented by the following formulas: Formula 6 (newly constructed horizontal 2-tap filter) and Formula 7 (newly constructed vertical 2-tap filter):

[0098] P′(x,y)=w1·f(x)·P(-1,y)+w2·f(x)·P(-1,y+h)+(1-w1·f(x)-w2·f(x))·P(x,y)

[0099] Formula 6.

[0100] P′(x,y)=w3·f(y)·P(x,-1)+w4·f(y)·P(x+w,-1)+(1-w3·f(y)-w4·f(y))·P(x,y)

[0101] Formula 7.

[0102] Where w1 is used to indicate the reference weight in the positive left direction, w2 is used to indicate the reference weight in the lower left direction, P(-1,y+h) is used to indicate the chromaticity value of the pixel block in the lower left direction of the current pixel block, w3 is used to indicate the reference weight in the positive top direction, w4 is used to indicate the reference weight in the upper right direction, and P(x+w,-1) is used to indicate the chromaticity value of the pixel block in the upper right direction of the current pixel block.

[0103] In other words, the vertical 2-tap filter only references the samples of the left template (i.e., the pixel block in the left direction) of the current block during the filtering process, while the newly constructed vertical 2-tap filter references the samples of the left and lower left sides simultaneously during the filtering process, and sets corresponding reference weights in different reference directions.

[0104] Similarly, the horizontal 2-tap filter only references the samples of the upper template of the current block (i.e., the pixel block in the upper direction) during the filtering process, while the newly constructed horizontal 2-tap filter references the samples of the upper and upper right sides at the same time during the filtering process, and sets corresponding reference weights in different reference directions.

[0105] This allows us to consider more input samples, increasing the richness of the input samples.

[0106] As one possible implementation, in the process of filtering the chromaticity prediction value using a preset IPF to obtain the filtered chromaticity prediction value, the electronic device can select a matching filter from the preset IPFs by referring to the chromaticity prediction mode of the CCNPM for the target pixel block to obtain the filtered chromaticity prediction value, including:

[0107] Electronic devices can select a target IPF from preset IPFs according to the chromaticity prediction mode of CCNPM, and filter the chromaticity prediction value through the target IPF to obtain the filtered chromaticity prediction value.

[0108] In other words, by establishing the correlation between the chromaticity prediction model and the IPF, the chromaticity prediction value can be reasonably filtered during the filtering process, thereby improving the filtering effect.

[0109] It should be noted that, in the embodiments of this disclosure, different chromaticity prediction modes may correspond to different IPFs, including any one of the following (a)-(d):

[0110] (a) When CCNPM is the first prediction mode, the target IPF can be a horizontal 2-tap filter;

[0111] (b) When CCNPM is the second prediction mode, the target IPF can be a vertical 2-tap filter;

[0112] (c) When CCNPM is the first prediction mode, the target IPF can be a newly constructed horizontal 2-tap filter;

[0113] (d) When CCNPM is the second prediction mode, the target IPF can be a newly constructed vertical 2-tap filter.

[0114] In other words, when the electronic device traverses the two chromaticity modes, CCNPM_T or CCNPM_L, the chromaticity prediction results are filtered.

[0115] The following describes the situations shown in (a)-(d) above in conjunction with specific embodiments, in the process of filtering the chroma prediction value through a preset intra-frame prediction filter to obtain the filtered chroma prediction value.

[0116] In Example 1, when CCNPM is in the first prediction mode, the electronic device can obtain the first chroma value of the pixel block directly to the left of the target pixel block in the video frame. Then, the electronic device can use a horizontal 2-tap filter to determine the product of the chroma prediction value and a first preset weight, and the product of the first chroma value and a second preset weight, and sum all the product results to obtain the filtered chroma prediction value.

[0117] The second preset weight can be the filtering parameter f(x) for the left pixel block in Formula 3 above, and the first preset weight can be the filtering parameter (1-f(x)) for the current pixel block in Formula 3 above.

[0118] In other words, when CCNPM is in the first prediction mode, the electronic device can use the horizontal 2-tap filter shown in Formula 3 to filter the chroma prediction value of CCNPM. That is, when the intra-frame prediction chroma component prediction mode is CCNPM_T, the upper sample is filtered by the horizontal 2-tap filter to filter the prediction value.

[0119] In Example 2, when CCNPM is in the first prediction mode, the electronic device can acquire the first chromaticity value of the pixel block directly to the left of the target pixel block in the video frame, and the third chromaticity value of the pixel block directly to the lower left. The first and third chromaticity values ​​are then fused according to a first preset ratio to obtain a first reference chromaticity value. Next, the electronic device can use a horizontal 2-tap filter to determine the product of the chromaticity prediction value and a first preset weight, and the product of the first reference chromaticity value and a second preset weight. All product results are then summed to obtain the filtered chromaticity prediction value.

[0120] The first reference chromaticity value can be used as the chromaticity value of the newly constructed pixel block in the left direction (that is, it is equivalent to using the chromaticity value of the pixel block in the lower left direction to correct the chromaticity value of the pixel block in the left direction). Substituting it into P(-1,y) in Formula 3 above, the second preset weight can be the filtering parameter f(x) for the left pixel block in Formula 3 above, and the first preset weight can be the filtering parameter (1-f(x)) for the current pixel block in Formula 3 above.

[0121] In other words, when CCNPM is in the first prediction mode, the electronic device can use the chromaticity value of the pixel block in the lower left direction to correct the chromaticity value of the pixel block in the directly left direction. Based on the corrected chromaticity value of the pixel block in the directly left direction, the horizontal 2-tap filter shown in Formula 3 is used to filter the chromaticity prediction value of CCNPM. That is, when the intra-frame prediction chromaticity component prediction mode is CCNPM_T, the upper sample and the upper right sample are first fused according to a certain ratio, and then the horizontal 2-tap filter is used to filter the prediction value.

[0122] In Example 3, when CCNPM is in the first prediction mode, the electronic device can acquire the first chromaticity value of the pixel block directly to the left of the target pixel block in the video frame, and the third chromaticity value of the pixel block to the lower left. Then, the electronic device can use a newly constructed horizontal 2-tap filter to determine the product of the chromaticity prediction value and the first preset weight, the product of the first chromaticity value and the second preset weight, and the product of the third chromaticity value and the third preset weight. All product results are then summed to obtain the filtered chromaticity prediction value.

[0123] The second preset weight can be the filtering parameter w1·f(x) for the left pixel block in Formula 6 above, the third preset weight can be the filtering parameter w2·f(x) for the lower left pixel block in Formula 6 above, and the first preset weight can be the filtering parameter (1-w1·f(x)-w2·f(x)) for the current pixel block in Formula 6 above.

[0124] In other words, when CCNPM is in the first prediction mode, the electronic device can use the newly constructed horizontal 2-tap filter shown in Formula 6 to filter the chroma prediction value of CCNPM by combining the chroma values ​​of the pixel blocks in the left and lower left directions, as well as the reference weights of the two directions. That is, when the intra-frame prediction chroma component prediction mode is CCNPM_T, the newly constructed horizontal 2-tap filter is used to filter the prediction value of the samples on the upper and upper right sides.

[0125] Example 4: When CCNPM is in the second prediction mode, the electronic device can obtain the second chroma value of the pixel block directly above the target pixel block in the video frame. Then, the electronic device can use a vertical 2-tap filter to determine the product of the chroma prediction value and the first preset weight, and the product of the second chroma value and the fourth preset weight, and sum all the product results to obtain the filtered chroma prediction value.

[0126] The fourth preset weight can be the filtering parameter f(y) for the upper pixel block in Formula 4 above, and the first preset weight can be the filtering parameter (1-f(y)) for the current pixel block in Formula 4 above.

[0127] In other words, when CCNPM is in the second prediction mode, the electronic device can use the vertical 2-tap filter shown in Formula 4 to filter the chroma prediction value of CCNPM. That is, when the intra-frame prediction chroma component prediction mode is CCNPM_L, only the left template is used, and a vertical 2-tap filter is used to filter the prediction value.

[0128] Example 5: When CCNPM is in the second prediction mode, the electronic device can acquire the second chromaticity value of the pixel block directly above the target pixel block in the video frame and the fourth chromaticity value of the pixel block to the upper right. The second and fourth chromaticity values ​​are then fused according to a second preset ratio to obtain a second reference chromaticity value. Next, the electronic device can use a vertical 2-tap filter to determine the product of the chromaticity prediction value and a first preset weight, and the product of the second reference chromaticity value and a fourth preset weight. All product results are then summed to obtain the filtered chromaticity prediction value.

[0129] The second reference chromaticity value can be used as the chromaticity value of the newly constructed pixel block in the top direction (that is, it is equivalent to using the chromaticity value of the pixel block in the upper right direction to correct the chromaticity value of the pixel block in the top direction). Substituting it into P(x,-1) in Formula 4 above, the fourth preset weight can be the filtering parameter f(y) for the upper pixel block in Formula 4 above, and the first preset weight can be the filtering parameter (1-f(y)) for the current pixel block in Formula 4 above.

[0130] In other words, when CCNPM is in the second prediction mode, the electronic device can use the chromaticity value of the pixel block in the upper right direction to correct the chromaticity value of the pixel block in the upper direction. Based on the corrected chromaticity value of the pixel block in the upper direction, the vertical 2-tap filter shown in Formula 4 is used to filter the chromaticity prediction value of CCNPM. That is, when the intra-frame prediction chromaticity component prediction mode is CCNPM_L, the samples on the left and lower left sides are first fused according to a certain ratio, and then the vertical 2-tap filter is used to filter the prediction value.

[0131] Example 6: When CCNPM is in the second prediction mode, the electronic device can acquire the second chromaticity value of the pixel block directly above the target pixel block in the video frame, and the fourth chromaticity value of the pixel block to the upper right. Then, the electronic device can use a newly constructed vertical 2-tap filter to determine the product of the chromaticity prediction value and the first preset weight, the product of the second chromaticity value and the fourth preset weight, and the product of the fourth chromaticity value and the fifth preset weight. All product results are then summed to obtain the filtered chromaticity prediction value.

[0132] Among them, the fourth preset weight can be the filtering parameter w3·f(y) for the upper pixel block in Formula 7 above, the fifth preset weight can be the filtering parameter w4·f(y) for the upper right pixel block in Formula 7 above, and the first preset weight can be the filtering parameter (1-w3·f(y)-w4·f(y)) for the current pixel block in Formula 7 above.

[0133] In other words, when CCNPM is in the second prediction mode, the electronic device can use the newly constructed vertical 2-tap filter shown in Formula 7 to filter the chroma prediction value of CCNPM by combining the chroma values ​​of the pixel blocks in the top and top right directions, as well as the reference weights in the two directions. That is, when the intra-frame prediction chroma component prediction mode is CCNPM_L, the newly constructed vertical 2-tap filter is used to filter the prediction value of the samples on the left and bottom left sides.

[0134] It should be noted that the pixel block referred to in the leftward direction in the above embodiments one, two and three can be the adjacent pixel block in the leftward direction of the target pixel block in the video frame, or the pixel block referred to in the leftward direction can be the non-adjacent pixel block in the leftward direction of the target pixel block in the video frame.

[0135] Similarly, the pixel block referenced in the above embodiments four, five and six can be the adjacent pixel block in the direction directly above the target pixel block in the video frame, or the pixel block referenced in the direction directly above the target pixel block in the video frame can be a non-adjacent pixel block in the direction directly above the target pixel block in the video frame.

[0136] Combining the vertical 2-tap filter and horizontal 2-tap filter shown in Formulas 3 and 4 above, another algorithm for horizontal 2-tap filters and vertical 2-tap filters can be obtained, as shown in Formulas 8 (horizontal 2-tap filter) and 9 (vertical 2-tap filter) below:

[0137] P′(x,y)=f(x)·P(-index,y)+(1-f(x))·P(x,y) Formula 8.

[0138] P′(x,y)=f(y)·P(x,-index)+(1-f(y))·P(x,y) Formula 9.

[0139] Here, index is used to indicate the index of the non-adjacent / adjacent row or column of the target pixel block in the left or top direction.

[0140] For example, such as Figure 9 As shown, this diagram illustrates the row / column indices in the left and top directions of a pixel block. Here, `index` can be any index value.

[0141] Optionally, the lower left pixel block referenced in Embodiments 2 and 3 above can be a pixel block in the video frame that is in the same vertical direction as the pixel block directly to the left of the target pixel block, or the lower left pixel block referenced can be a pixel block in the video frame that is not in the same vertical direction as the pixel block directly to the left of the target pixel block.

[0142] Similarly, the pixel block in the upper right direction referred to in Embodiments 5 and 6 above can be a pixel block in the video frame that is in the same horizontal direction as the pixel block directly above the target pixel block, or the pixel block in the upper right direction referred to can be a pixel block in the video frame that is not in the same horizontal direction as the pixel block directly above the target pixel block.

[0143] Combining the newly constructed vertical 2-tap filter and the newly constructed horizontal 2-tap filter shown in Formulas 6 and 7 above, we can obtain another algorithm for newly constructed horizontal 2-tap filter and newly constructed vertical 2-tap filter, as shown in Formulas 10 (newly constructed horizontal 2-tap filter) and 11 (newly constructed vertical 2-tap filter):

[0144] P′(x,y)=w1·f(x)·P(-index1,y)+w2·f(x)·P(-index2,y+h)+(1-w1·f(x)-w2·f(x))·P(x,y) Formula 10.

[0145] P′(x,y)=w3·f(y)·P(x,-index3)+w4·f(y)·P(x+w,-index4)+(1-w3·f(x)-w4·f(x))·P(x,y) Formula 11.

[0146] Here, index1 indicates the non-adjacent / adjacent column index of the target pixel block in the left direction, index2 indicates the column index of the target pixel block in the lower left direction, index3 indicates the non-adjacent / adjacent row index of the target pixel block in the upper direction, and index4 indicates the row index of the target pixel block in the upper right direction.

[0147] Furthermore, index1 and index2 can be the same (i.e., the pixel block in the left direction and the pixel block in the lower left direction are in the same vertical direction), or index1 and index2 can be different (i.e., the pixel block in the left direction and the pixel block in the lower left direction are not in the same vertical direction).

[0148] Similarly, index3 and index4 can be the same (i.e., the pixel block directly above and the pixel block to the upper right are in the same horizontal direction), or index3 and index4 can be different (i.e., the pixel block directly above and the pixel block to the upper right are not in the same horizontal direction).

[0149] For example, such as Figure 10 As shown, it illustrates the row / column indices of a pixel block for the left, top, bottom left, and top right directions. Here, index1 can be 0 and index2 can be 1 (meaning the pixel block in the left direction and the pixel block in the bottom left direction are not in the same vertical direction), and both index1 and index2 can be 0 (meaning the pixel block in the left direction and the pixel block in the bottom left direction are in the same vertical direction).

[0150] Alternatively, index3 can be 1 and index4 can be 0 (meaning the pixel block directly above and the pixel block to the upper right are in the same horizontal direction), or both index3 and index4 can be 2 (meaning the pixel block directly above and the pixel block to the upper right are not in the same horizontal direction).

[0151] In summary, by applying IPF filtering to the CCNPM chroma prediction, more accurate chroma prediction values ​​can be obtained. In other words, to improve coding performance, filtering the CCNPM prediction results enhances the spatial correlation of chroma components, thereby improving the accuracy of cross-component prediction.

[0152] It is understood that, in order to achieve the above-mentioned functions, the filtering device for cross-component prediction includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the algorithmic steps of the examples described in conjunction with the embodiments of this disclosure, this disclosure can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0153] This disclosure embodiment can divide the filtering device for cross-component prediction into functional modules according to the above method embodiment. For example, each function can be divided into a separate functional module, or two or more functions can be integrated into one functional module. The integrated module can be implemented in hardware or software. It should be noted that the module division in this disclosure embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods. The following description uses the example of dividing each functional module according to each function.

[0154] Figure 11 This is a schematic diagram of the structure of a filtering device for cross-component prediction provided in an embodiment of this disclosure. Figure 1 The cross-component prediction filtering device 1100 includes: an acquisition module 1101 and a processing module 1102.

[0155] The acquisition module 1101 is used to acquire the chroma prediction value of the target pixel block of the cross-component nonlinear intra-frame prediction (CCNPM) in the video frame. The processing module 1102 is used to filter the chroma prediction value through a preset intra-frame prediction filter (IPF) to obtain the filtered chroma prediction value.

[0156] In some embodiments, the preset IPF includes at least one of the following: a horizontal 2-tap filter for filtering in the horizontal direction, a vertical 2-tap filter for filtering in the vertical direction, a 3-tap filter for filtering in both the horizontal and vertical directions, a newly constructed vertical 2-tap filter, and a newly constructed horizontal 2-tap filter.

[0157] In some embodiments, the processing module 1102 is specifically configured to select a target IPF from preset IPFs according to the chromaticity prediction mode of CCNPM. The processing module 1102 is further configured to filter the chromaticity prediction value using the target IPF to obtain a filtered chromaticity prediction value. The chromaticity prediction mode of CCNPM includes a first prediction mode and a second prediction mode. The first prediction mode is a mode that performs CCNPM based on pixel blocks directly above the target pixel block, and the second prediction mode is a mode that performs CCNPM based on pixel blocks directly to the left of the target pixel block.

[0158] In some embodiments, when CCNPM is in the first prediction mode, the target IPF is a horizontal 2-tap filter. The acquisition module 1101 is further configured to acquire the first chroma value of the pixel block directly to the left of the target pixel block in the video frame when CCNPM is in the first prediction mode. The processing module 1102 is specifically configured to use the horizontal 2-tap filter to determine the product of the chroma prediction value and a first preset weight, and the product of the first chroma value and a second preset weight, and to sum all the product results to obtain the filtered chroma prediction value.

[0159] In some embodiments, when CCNPM is in the first prediction mode, the target IPF is a horizontal 2-tap filter. The acquisition module 1101 is further configured to, when CCNPM is in the first prediction mode, acquire the first chromaticity value of the pixel block directly to the left of the target pixel block in the video frame, and the third chromaticity value of the pixel block directly to the lower left. The processing module 1102 is specifically configured to fuse the first chromaticity value and the third chromaticity value according to a first preset ratio to obtain a first reference chromaticity value. The processing module 1102 is further configured to, using a horizontal 2-tap filter, determine the product of the chromaticity prediction value and a first preset weight, and the product of the first reference chromaticity value and a second preset weight, and sum all product results to obtain the filtered chromaticity prediction value.

[0160] In some embodiments, when CCNPM is in the first prediction mode, the target IPF is a newly constructed horizontal 2-tap filter. The acquisition module 1101 is further configured to, when CCNPM is in the first prediction mode, acquire the first chromaticity value of the pixel block directly to the left of the target pixel block in the video frame, and the third chromaticity value of the pixel block to the lower left. The processing module 1102 is specifically configured to, using the newly constructed horizontal 2-tap filter, determine the product of the chromaticity prediction value and a first preset weight, the product of the first chromaticity value and a second preset weight, and the product of the third chromaticity value and a third preset weight, and sum all the product results to obtain the filtered chromaticity prediction value.

[0161] In some embodiments, the pixel block in the left direction is the pixel block adjacent to the target pixel block in the left direction in the video frame, or the pixel block in the left direction is the non-adjacent pixel block in the left direction of the target pixel block in the video frame.

[0162] In some embodiments, when CCNPM is in the second prediction mode, the target IPF is a vertical 2-tap filter. The acquisition module 1101 is further configured to acquire the second chroma value of the pixel block directly above the target pixel block in the video frame when CCNPM is in the second prediction mode. The processing module 1102 is specifically configured to use the vertical 2-tap filter to determine the product of the chroma prediction value and a first preset weight, and the product of the second chroma value and a fourth preset weight, and to sum all the product results to obtain the filtered chroma prediction value.

[0163] In some embodiments, when CCNPM is in the second prediction mode, the target IPF is a vertical 2-tap filter. The acquisition module 1101 is further configured to, when CCNPM is in the second prediction mode, acquire the second chromaticity value of the pixel block directly above the target pixel block in the video frame, and the fourth chromaticity value of the pixel block to the upper right. The processing module 1102 is specifically configured to fuse the second chromaticity value and the fourth chromaticity value according to a second preset ratio to obtain a second reference chromaticity value. The processing module 1102 is further configured to, using the vertical 2-tap filter, determine the product of the chromaticity prediction value and a first preset weight, and the product of the second reference chromaticity value and a fourth preset weight, and sum all product results to obtain the filtered chromaticity prediction value.

[0164] In some embodiments, when CCNPM is in the second prediction mode, the target IPF is a newly constructed vertical 2-tap filter. The acquisition module 1101 is further configured to, when CCNPM is in the second prediction mode, acquire the second chromaticity value of the pixel block directly above the target pixel block in the video frame, and the fourth chromaticity value of the pixel block to the upper right. The processing module 1102 is specifically configured to, using the newly constructed vertical 2-tap filter, determine the product of the chromaticity prediction value and a first preset weight, the product of the second chromaticity value and a fourth preset weight, and the product of the fourth chromaticity value and a fifth preset weight, and sum all the product results to obtain the filtered chromaticity prediction value.

[0165] In some embodiments, the pixel block in the upward direction is the pixel block adjacent to the target pixel block in the upward direction in the video frame, or the pixel block in the upward direction is the non-adjacent pixel block in the upward direction of the target pixel block in the video frame.

[0166] In implementing the functionality of the integrated modules described above in hardware, this disclosure provides another possible structure for the filtering device for cross-component prediction described in the above embodiments. For example... Figure 12 As shown, the filtering device 1200 for cross-component prediction includes: a processor 1202 and a bus 1204. Optionally, the filtering device for cross-component prediction may also include a memory 1201; alternatively, the filtering device for cross-component prediction may also include a communication interface 1203.

[0167] Processor 1202 may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with embodiments of this disclosure. Processor 1202 may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with embodiments of this disclosure. Processor 1202 may also be a combination of functions implementing computational capabilities, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0168] The communication interface 1203 is used to connect with other devices via a communication network. This communication network can be Ethernet, wireless access network, wireless local area network (WLAN), etc.

[0169] The memory 1201 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), disk storage medium or other magnetic storage device, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto.

[0170] As one possible implementation, the memory 1201 can exist independently of the processor 1202. The memory 1201 can be connected to the processor 1202 via a bus 1204 and is used to store instructions or program code. When the processor 1202 calls and executes the instructions or program code stored in the memory 1201, it can implement the filtering method for cross-component prediction provided in the embodiments of this disclosure.

[0171] In another possible implementation, the memory 1201 can also be integrated with the processor 1202.

[0172] Bus 1204 can be an extended industry standard architecture (EISA) bus, etc. Bus 1204 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 12 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0173] Some embodiments of this disclosure provide a computer-readable storage medium (e.g., a non-transitory computer-readable storage medium) storing computer program instructions that, when executed on a computer, cause the computer to perform a filtering method for cross-component prediction as described in any of the embodiments above.

[0174] Exemplary examples of computer-readable storage media may include, but are not limited to: magnetic storage devices (e.g., hard disks, floppy disks, or magnetic tapes), optical discs (e.g., compact disks (CDs), digital versatile disks (DVDs), etc.), smart cards, and flash memory devices (e.g., erasable programmable read-only memory (EPROMs), cards, sticks, or key drives, etc.). The various computer-readable storage media described in this disclosure may represent one or more devices and / or other machine-readable storage media for storing information. The term "machine-readable storage medium" may include, but is not limited to, wireless channels and various other media capable of storing, containing, and / or carrying instructions and / or data.

[0175] This disclosure provides a computer program product containing instructions that, when run on a computer, cause the computer to perform the filtering method for cross-component prediction as described in any of the above embodiments.

[0176] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any changes or substitutions within the technical scope disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A filtering method for cross-component prediction, characterized in that, The method includes: Obtain the chromaticity prediction value of the target pixel block in the video frame using cross-component nonlinear intra-frame prediction (CCNPM). The chroma prediction value is filtered by a preset intra-frame prediction filter (IPF) to obtain the filtered chroma prediction value.

2. The method according to claim 1, characterized in that, The preset IPF includes at least one of the following: a horizontal 2-tap filter for filtering in the horizontal direction, a vertical 2-tap filter for filtering in the vertical direction, a 3-tap filter for filtering in both the horizontal and vertical directions, a newly constructed vertical 2-tap filter, and a newly constructed horizontal 2-tap filter.

3. The method according to claim 2, characterized in that, The step of filtering the chroma prediction value using a preset intra-frame prediction filter (IPF) includes: Based on the chromaticity prediction mode of the CCNPM, a target IPF is selected from the preset IPFs; The chromaticity prediction value is filtered by the target IPF to obtain the filtered chromaticity prediction value. The chromaticity prediction mode of the CCNPM includes a first prediction mode and a second prediction mode. The first prediction mode is a CCNPM mode based on the pixel block directly above the target pixel block, and the second prediction mode is a CCNPM mode based on the pixel block directly to the left of the target pixel block.

4. The method according to claim 3, characterized in that, When the CCNPM is the first prediction mode, the target IPF is the horizontal 2-tap filter; the step of filtering the chromaticity prediction value through the target IPF to obtain the filtered chromaticity prediction value includes: When the CCNPM is in the first prediction mode, the first chromaticity value of the pixel block in the left direction of the target pixel block in the video frame is obtained; Using the horizontal 2-tap filter, the product of the predicted chromaticity value and the first preset weight, and the product of the first chromaticity value and the second preset weight are determined, and all product results are summed to obtain the filtered predicted chromaticity value.

5. The method according to claim 3, characterized in that, When the CCNPM is the first prediction mode, the target IPF is the horizontal 2-tap filter; the step of filtering the chromaticity prediction value through the target IPF to obtain the filtered chromaticity prediction value includes: When the CCNPM is in the first prediction mode, the first chromaticity value of the pixel block in the left direction of the target pixel block in the video frame and the third chromaticity value of the pixel block in the lower left direction are obtained. The first chromaticity value and the third chromaticity value are fused according to a first preset ratio to obtain a first reference chromaticity value; Using the horizontal 2-tap filter, the product of the predicted chromaticity value and the first preset weight, and the product of the first reference chromaticity value and the second preset weight are determined, and all product results are summed to obtain the filtered predicted chromaticity value.

6. The method according to claim 3, characterized in that, When the CCNPM is the first prediction mode, the target IPF is the newly constructed horizontal 2-tap filter; The step of filtering the chromaticity prediction value using the target IPF to obtain the filtered chromaticity prediction value includes: When the CCNPM is in the first prediction mode, the first chromaticity value of the pixel block in the left direction of the target pixel block in the video frame and the third chromaticity value of the pixel block in the lower left direction are obtained. Using the newly constructed horizontal 2-tap filter, the product of the chromaticity prediction value and the first preset weight, the product of the first chromaticity value and the second preset weight, and the product of the third chromaticity value and the third preset weight are determined, and all product results are summed to obtain the filtered chromaticity prediction value.

7. The method according to any one of claims 4-6, characterized in that, The pixel block in the left direction is either the pixel block adjacent to the target pixel block in the left direction in the video frame, or the pixel block in the left direction is a non-adjacent pixel block in the left direction of the target pixel block in the video frame.

8. The method according to claim 3, characterized in that, When the CCNPM is the second prediction mode, the target IPF is the vertical 2-tap filter; the step of filtering the chromaticity prediction value through the target IPF to obtain the filtered chromaticity prediction value includes: When the CCNPM is in the second prediction mode, the second chromaticity value of the pixel block directly above the target pixel block in the video frame is obtained; Using the vertical 2-tap filter, the product of the predicted chromaticity value and the first preset weight, and the product of the second chromaticity value and the fourth preset weight are determined, and all product results are summed to obtain the filtered predicted chromaticity value.

9. The method according to claim 3, characterized in that, When the CCNPM is the second prediction mode, the target IPF is the vertical 2-tap filter; the step of filtering the chromaticity prediction value through the target IPF to obtain the filtered chromaticity prediction value includes: When the CCNPM is in the second prediction mode, the second chromaticity value of the pixel block directly above the target pixel block in the video frame and the fourth chromaticity value of the pixel block to the upper right are obtained. The second chromaticity value and the fourth chromaticity value are fused according to a second preset ratio to obtain a second reference chromaticity value; Using the vertical 2-tap filter, the product of the predicted chromaticity value and the first preset weight, and the product of the second reference chromaticity value and the fourth preset weight are determined, and all product results are summed to obtain the filtered predicted chromaticity value.

10. The method according to claim 3, characterized in that, When the CCNPM is the second prediction mode, the target IPF is the newly constructed vertical 2-tap filter; the filtering process of the chromaticity prediction value through the target IPF to obtain the filtered chromaticity prediction value includes: When the CCNPM is in the second prediction mode, the second chromaticity value of the pixel block directly above the target pixel block in the video frame and the fourth chromaticity value of the pixel block to the upper right are obtained. Using the newly constructed vertical 2-tap filter, the product of the chromaticity prediction value and the first preset weight, the product of the second chromaticity value and the fourth preset weight, and the product of the fourth chromaticity value and the fifth preset weight are determined, and all product results are summed to obtain the filtered chromaticity prediction value.

11. The method according to any one of claims 8-10, characterized in that, The pixel block in the upward direction is either the pixel block directly above the target pixel block in the video frame, or the pixel block in the upward direction is a non-adjacent pixel block directly above the target pixel block in the video frame.

12. An electronic device, characterized in that, include: Memory and processor; Memory and processor are coupled; The memory is used to store instructions that can be executed by the processor; When the processor executes the instructions, it performs the method as described in any one of claims 1-11.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1-11.

14. A computer program product, characterized in that, The computer program product includes computer program instructions that, when executed, implement the method as described in any one of claims 1-11.

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