Video processing methods, and device and storage medium

Abstract

Provided in the present application are video processing methods, and a device and a storage medium. A video processing method applied to a decoding end comprises: filtering a luminance component of a reconstructed image to obtain a corresponding luminance component reconstruction value; on the basis of video bitstream parameter information, determining a luminance component filtering mode and luminance component filtering parameters; using the luminance component filtering mode and the luminance component filtering parameters to filter the luminance component reconstruction value, so as to obtain a corresponding first chrominance component sample correction value and a corresponding second chrominance component sample correction value; and superimposing the first chrominance component sample correction value and a first chrominance component reconstruction value to obtain a corrected first chrominance component reconstruction value, and superimposing the second chrominance component sample correction value and a second chrominance component reconstruction value to obtain a corrected second chrominance component reconstruction value.

Description

Video processing method, device and storage medium Technical Field

[0001] The present application relates to the field of video processing technology, and in particular to a video processing method, device and storage medium. Background Art

[0002] With the further development of video coding technology based on a hybrid coding framework, the processing flow of the adaptive loop filter (ALF) module has become increasingly rich, especially the filtering process flow for the luma component. To enhance the reconstruction effect of the adaptive loop filter module, one or more fixed filters can be added to the ALF module, whose output is used to supplement the input signal of the ALF module. After Wiener filtering, the filtering effect of the ALF module can be further improved. However, the cross-component adaptive loop filter (CC-ALF) module still uses the output value of the luma component after processing by the sample adaptive offset (SAO) module as the input signal, which does not fully utilize the rich luma information of the adaptive loop filter module. As a result, the CC-ALF input signal is relatively simple, and the deviation between the reconstructed chroma component values ​​corrected by CC-ALF processing and the original values ​​is large, and the image reconstruction quality needs to be further improved. Summary of the Invention

[0003] In view of this, embodiments of the present application provide a video processing method, device, and storage medium, which effectively improve the reconstruction quality of the chrominance component in the video image.

[0004] The present invention provides a video processing method, which is applied to a decoding end and includes:

[0005] Filtering the brightness component of the reconstructed image to obtain a corresponding brightness component reconstruction value;

[0006] Determine the luminance component filtering mode and luminance component filtering parameters according to the video code stream parameter information;

[0007] Filtering the luminance component reconstruction value using the luminance component filtering method and the luminance component filtering parameters to obtain corresponding first chrominance component sample correction values ​​and second chrominance component sample correction values;

[0008] The first chroma component sample correction value is superimposed on the first chroma component reconstruction value to obtain a corrected first chroma component reconstruction value, and the second chroma component sample correction value is superimposed on the second chroma component reconstruction value to obtain a corrected second chroma component reconstruction value.

[0009] The present invention provides a video processing method, which is applied to an encoding end and includes:

[0010] Filtering the brightness component of the reconstructed image to obtain a corresponding brightness component reconstruction value;

[0011] Filtering the luminance component reconstruction value to obtain a corresponding first chrominance component sample correction value and a second chrominance component sample correction value;

[0012] Superimposing the first chroma component sample corrected value and the first chroma component reconstructed value to obtain a corrected first chroma component reconstructed value, and superimposing the second chroma component sample corrected value and the second chroma component reconstructed value to obtain a corrected second chroma component reconstructed value;

[0013] The CC-ALF filter parameters are determined based on the principle of minimum mean square error between the corrected chroma component reconstruction value and the original pixel value of the chroma component;

[0014] The CC-ALF filter parameters are written into the encoded video stream as video stream parameter information and sent to the decoding end.

[0015] An embodiment of the present application provides a communication device, comprising: a memory, and one or more processors;

[0016] The memory is configured to store one or more programs;

[0017] When the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any one of the above embodiments.

[0018] An embodiment of the present application provides a storage medium storing a computer program. When the computer program is executed by a processor, the method described in any one of the above embodiments is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] FIG1 is a schematic diagram of an implementation of a CC-ALF structure in an H.266 / VVC video coding framework provided by an embodiment of the present application;

[0020] FIG2 is a schematic diagram of a loop filtering process flow in an ECM provided by the related art;

[0021] FIG3 is a schematic structural diagram of a luminance component filtering module that introduces a fixed filter provided by the related art;

[0022] FIG4 is a schematic diagram of an implementation of an H.266 / VVC encoding framework provided by the related art;

[0023] FIG5 is a schematic diagram of an implementation of an H.266 / VVC decoding framework provided by the related art;

[0024] FIG6 is a flow chart of a video processing method provided in an embodiment of the present application;

[0025] FIG7 is a flowchart of another video processing method provided in an embodiment of the present application;

[0026] FIG8 is a flowchart of a video processing method applied to a decoding end provided by an embodiment of the present application;

[0027] FIG9 is a schematic diagram of a configuration of a CC-ALF filtering structure for a single input signal provided in an embodiment of the present application;

[0028] FIG10 is a schematic diagram of another configuration of a CC-ALF filtering structure for a single input signal provided in an embodiment of the present application;

[0029] FIG11 is a schematic diagram of a configuration of a CC-ALF filtering structure for multiple input signals provided in an embodiment of the present application;

[0030] FIG12 is a flowchart of a video processing method applied to an encoding end provided by an embodiment of the present application;

[0031] FIG13 is a structural block diagram of a video processing device provided in an embodiment of the present application;

[0032] FIG14 is a structural block diagram of another video processing device provided in an embodiment of the present application;

[0033] FIG15 is a schematic structural diagram of a communication device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0034] The following describes the embodiments of the present application in conjunction with the accompanying drawings. The following describes the present application in conjunction with the accompanying drawings. The examples are only used to explain the present application and are not used to limit the scope of the present application.

[0035] For block-based hybrid coding frameworks such as High Efficiency Video Coding (HEVC), Versatile Video Coding (VVC), and AVS, distortion effects such as blocking artifacts, ringing artifacts, color deviation, and image blur still exist in the compressed video. The transformed and quantized signal is reconstructed through inverse quantization, inverse transformation, and prediction compensation. Compared with the original image, the reconstructed image has some different information due to the influence of quantization, which means that the reconstructed image will produce distortion. To reduce the impact of this distortion on video quality, in-loop filtering technology is usually used in hybrid coding frameworks to effectively reduce the degree of distortion caused by quantization. Since these filtered reconstructed images will serve as a reference for subsequent coded images to predict future image signals, the above filtering operation is also called in-loop filtering, that is, filtering operation within the coding loop.

[0036] Taking H.266 / VVC video coding technology as an example, loop filtering technologies include Luma Mapping with Chroma Scaling (LMCS), Deblocking Filter (DBF), Sample Adaptive Offset (SAO), and Adaptive Loop Filter (ALF). LMCS improves compression efficiency by reallocating codewords across the dynamic range; DBF reduces blocking artifacts; SAO improves ringing artifacts; and ALF reduces decoding errors.

[0037] Among them, the ALF module includes a filter for the luma component and a filter for the two chroma components, as well as a cross-component adaptive loop filter (CC-ALF). Figure 1 is a schematic diagram of the implementation of the CC-ALF structure in an H.266 / VVC video coding framework provided by an embodiment of the present application. CC-ALF uses luma sample values ​​to refine each chroma component. The combined structure of CC-ALF and other filters is shown in Figure 1. It can be seen that after the luma component (i.e., Luma) and the chroma components (i.e., Cb and Cr) are respectively subjected to SAO filtering, the ALF filtering process continues to be executed. In conventional video coding systems, only the luma component ALF and the chroma component ALF are executed. In the embodiment of the present application, when CC-ALF is turned on, two additional ALF filters, namely CCALF Cb and CCALF Cr, continue to be executed to output corrected sample values, and then use adders to superimpose the corrected sample values ​​on the first chroma component Cb and the second chroma component Cr processed by ALF.

[0038] Based on VVC, further enhanced compression models (ECM) have begun to be explored and studied. In addition to continuing to use the existing loop filters in VVC, the loop filtering part of ECM also introduces a variety of additional loop filters, such as bilateral filtering (BIF). Figure 2 is a schematic diagram of the loop filtering processing flow in ECM provided by related technology. The loop filtering process of ECM is shown in Figure 2. BIF and SAO operate in parallel, and the generated correction value and the correction value generated by SAO are added to the reconstructed pixels after deblocking effect filtering. Therefore, the input of ALF in ECM is the reconstructed value after BIF and SAO processing, and the output is the enhanced pixel value.

[0039] To address the problem of single input of the ALF filtering module, several technical solutions were proposed to add fixed filters to the loop filtering process, and certain gains were achieved.

[0040] In one solution, the reconstructed image sample value before DBF filtering can be used as an additional input signal for ALF, and the final filtering result of ALF will be obtained by weighted processing of the traditional ALF filtering processing result and the reconstructed value before DBF filtering. In another solution, the number of filter taps corresponding to the output value of the fixed filter can be increased in the ALF filtering module design in the related technology, wherein the online trained filter tap coefficients include two types: spatial domain taps and fixed filter output value taps. In another solution, the residual of the image pixel can be used as an additional input signal for ALF, and the reconstructed image prediction value and residual value use different filtering templates and different filtering coefficients respectively. In another solution, an additional fixed filter is added to the two fixed filters in the original ALF filtering process in ECM, and is constructed in a cascade manner with the original fixed filter, and its output can be used as the input of the ALF filter.

[0041] Figure 3 is a structural diagram of a luminance component filtering module that introduces a fixed filter provided by the relevant technology. After the fixed filter is introduced in the ECM, the original ALF filtering module input is expanded to multiple, including not only the output value after SAO filtering (Wiener filtering using spatial neighborhood pixels), but also the image reconstruction value before the DBF filtering module, the image pixel value before DBF and after Gaussian filtering, the output value of the fixed filter, the image pixel residual, etc., as shown in Figure 3.

[0042] The above solutions solve the problem of a single input signal for the ALF filter module. However, for the CC-ALF filter module, the output result after SAO filtering is still used as the input signal to generate the corrected value of the chrominance component. The deviation between the reconstructed value of the chrominance component after CC-ALF processing and the original value is large, and the image reconstruction quality needs to be further improved. To address this problem, this application proposes a flexible cross-component loop filtering method that can fully utilize the luminance component information of each node of the luminance ALF module, especially utilizing the fixed filter to optimize the luminance component, perform detail compensation on the filtering result of the chrominance component, and effectively improve the reconstruction quality of the chrominance component.

[0043] The following is a further detailed description of the present application in conjunction with the accompanying drawings and embodiments. The specific embodiments described herein are only used to explain the embodiments of the present application and are not intended to limit the present application.

[0044] The embodiment of the present application is implemented based on a hybrid coding framework. Figure 4 is a schematic diagram of an implementation of an H.266 / VVC coding framework provided by related technology. As shown in Figure 4, the new generation video coding standard H.266 / VVC coding framework can include modules such as intra-frame prediction, inter-frame prediction, transformation, quantization, loop filtering, and entropy coding.

[0045] The overall framework process of the encoding end is as follows:

[0046] (1) The input video is first divided into frames and then block-divided;

[0047] (2) The divided blocks are sent to the intra-frame / inter-frame prediction module for predictive coding. The intra-frame prediction module is mainly used to remove the spatial correlation of the image; the inter-frame prediction module is mainly used to remove the temporal correlation of the image;

[0048] (3) The predicted value is then subtracted from the original block to obtain a residual value, which is then transformed and quantized to remove frequency domain correlation and perform lossy compression on the data.

[0049] (4) Finally, all the coding parameters and residuals are entropy-coded to form a binary stream for storage or transmission. The output data of the entropy coding module is the compressed code stream of the original video.

[0050] (5) The predicted value and the residual after inverse quantization and inverse transformation are added to obtain the block reconstruction value, and finally a reconstructed image is formed.

[0051] (6) The reconstructed image is filtered through a loop filter and stored in the image cache as a reference image in the future.

[0052] FIG5 is a schematic diagram of an implementation of an H.266 / VVC decoding framework provided by related art. As shown in FIG5 , the overall framework process of the decoding end is as follows:

[0053] (1) Analyze the code stream to obtain the prediction mode and obtain the prediction value;

[0054] (2) Perform inverse transformation and inverse quantization on the residual obtained from bitstream analysis;

[0055] (3) The predicted value and the residual after inverse quantization and inverse transformation are added to obtain the block reconstruction value, and finally a reconstructed image is formed.

[0056] (4) The reconstructed image is filtered through a loop filter and stored in the image cache as a reference image in the future.

[0057] The partitioning pattern prediction method provided by the present application is applied to the loop filtering module. Taking the H.266 / VVC video coding standard technology as an example, the loop filtering module includes processing processes such as DBF, SAO and ALF. The luminance ALF, chrominance ALF and inter-component ALF filtering methods in the ALF technology are all based on the Wiener filtering principle. The Wiener-Hough equation is established through the original image information and the reconstructed image information to solve a series of filter coefficients with minimum mean square error, thereby reducing the decoding error and effectively improving the PSNR. In order to further reduce the distortion between the reconstructed image and the original image, the present application provides a loop filtering method, which introduces the output value of a fixed filter as the input signal in the CC-ALF filtering module, better utilizes the detailed texture information of the luminance component, compensates for the details of the chrominance component, and improves the reconstruction quality of the chrominance component.

[0058] It should be noted that the technical solution provided in the embodiments of the present application can be applied to the H.266 / VVC standard, AVS (such as AVS3) or the next-generation video coding and decoding standard, and the embodiments of the present application are not limited to this.

[0059] In one embodiment, FIG6 is a flow chart of a video processing method provided by an embodiment of the present application. This embodiment is applied to the case of improving the chrominance component of a video image. This embodiment can be executed by a decoding end (also referred to as a decoder). As shown in FIG6, this embodiment includes: S110-S140.

[0060] S110 , filtering the brightness component of the reconstructed image to obtain a corresponding brightness component reconstruction value.

[0061] In an example, the process of filtering the luminance component of the reconstructed image may be a process of performing at least one filtering process of DBF processing, BIF processing, SAO processing, and at least one fixed filter on the luminance component of the reconstructed image.

[0062] S120: Determine a luminance component filtering mode and luminance component filtering parameters according to the video stream parameter information.

[0063] S130 , filtering the luminance component reconstruction value using a luminance component filtering method and luminance component filtering parameters to obtain corresponding first chrominance component sample correction values ​​and second chrominance component sample correction values.

[0064] The process of filtering the luminance component reconstruction value may be a process of performing CC-ALF filtering on the luminance component reconstruction value.

[0065] S140. Superimpose the first chroma component sample correction value and the first chroma component reconstruction value to obtain a corrected first chroma component reconstruction value, and superimpose the second chroma component sample correction value and the second chroma component reconstruction value to obtain a corrected second chroma component reconstruction value.

[0066] In one embodiment, before filtering the luminance component of the reconstructed image to obtain the corresponding luminance component reconstruction value, the method further includes: parsing the received encoded video stream to obtain corresponding video stream parameter information; and decoding the encoded video stream to obtain the corresponding reconstructed image.

[0067] In one embodiment, after filtering the luminance component of the reconstructed image to obtain the corresponding luminance component reconstruction value, it also includes: performing ALF filtering operations on the first chrominance component and the second chrominance component in the reconstructed image respectively to obtain the corresponding first chrominance component reconstruction value and the second chrominance component reconstruction value.

[0068] In one embodiment, before filtering the luminance component reconstructed value using the luminance component filtering method and the luminance component filtering parameters, the method further includes: classifying the luminance component reconstructed value using a preconfigured luminance component sample classification strategy to obtain classified luminance component reconstructed values.

[0069] In one embodiment, the luminance component reconstructed value is filtered using a luminance component filtering method and luminance component filtering parameters, including: filtering each category of the luminance component reconstructed value, wherein different categories of filtering processes use different luminance component filtering parameters and luminance component filtering methods.

[0070] In one embodiment, the luminance component sample classification strategy includes at least one of the following: a classification strategy of an adaptive loop filter (ALF) filter processing mode; a classification strategy of an improved ALF filter processing mode; a classification strategy of basic sample residuals; and a classification strategy based on region division.

[0071] In one embodiment, filtering the luminance component of the reconstructed image to obtain a corresponding luminance component reconstruction value includes: performing one or more filters on the luminance component of the reconstructed image according to a preset order to obtain the corresponding luminance component reconstruction value; wherein the filtering process includes at least one of the following:

[0072] Deblocking filtering;

[0073] Double-sideband filtering;

[0074] Pixel adaptive compensation processing;

[0075] Filtering using a fixed filter;

[0076] In one example, the luminance component of the reconstructed image may be subjected to at least one of DBF processing, BIF processing, SAO processing, and at least one fixed filter filtering process to obtain one or more corresponding luminance component reconstruction values.

[0077] In one embodiment, filtering the luminance component of the reconstructed image to obtain a corresponding luminance component reconstruction value includes filtering the luminance component of the reconstructed image to obtain one or more luminance component reconstruction values. Obtaining one luminance component reconstruction value can be understood as filtering a single input signal of a CC-ALF filter; obtaining multiple luminance component reconstruction values ​​can be understood as filtering multiple input signals of a CC-ALF filter.

[0078] In one embodiment, the video stream parameter information includes at least one of the following: a CC-ALF filter switch in a sequence parameter set (SPS); a CC-ALF filter switch in a picture parameter set (PPS); a CC-ALF filter switch and filter identifier in a picture header (PH); a CC-ALF filter switch and filter identifier in a slice header (SH); a filter identifier in a coding tree unit (CTU); and CC-ALF filter parameter information in an adaptation parameter set (APS).

[0079] The CC-ALF filter parameter information in the APS includes at least the following parameters: the number of CC-ALF filter coefficients; the absolute value of the CC-ALF filter coefficients; and the sign of the CC-ALF filter coefficients.

[0080] In one embodiment, the video stream parameter information further includes at least one of the following:

[0081] The input sample category identifier or index used by CC-ALF filtering is contained in the sequence parameter set, picture parameter set, picture header, slice header or coding tree unit;

[0082] The CC-ALF input sample category identifier or index of the chroma component is included in the adaptation parameter set.

[0083] In one embodiment, the CC-ALF filter parameter information in the adaptive parameter set corresponds to the first chroma component and the second chroma component.

[0084] In one embodiment, filtering the luminance component reconstruction value using a luminance component filtering method and luminance component filtering parameters includes:

[0085] Filtering the luminance component reconstruction value according to a preset luminance component filtering method and luminance component filtering parameters;

[0086] Alternatively, the luminance component reconstruction value is filtered according to the luminance component filtering mode and luminance component filtering parameters specified in the video stream parameter information.

[0087] In one embodiment, filtering the luminance component reconstructed value according to a preset luminance component filtering mode and luminance component filtering parameters includes: performing CC-ALF filtering on the luminance component of the current image according to a CC-ALF filtering switch; determining CC-ALF filter coefficients, and filtering the luminance component reconstructed value according to the preset luminance component filtering mode. The current image may be understood as the reconstructed image in the above embodiment.

[0088] In one embodiment, filtering the luminance component reconstructed values ​​according to the luminance component filtering mode and luminance component filtering parameters specified in the video stream parameter information includes: performing CC-ALF filtering on the luminance component of the current image according to a CC-ALF filtering switch; determining the number and type of luminance component reconstructed values ​​used in the CC-ALF filtering according to an input sample category identifier or index used in the CC-ALF filtering; and determining CC-ALF filter coefficients to filter the luminance component reconstructed values.

[0089] In one embodiment, FIG7 is a flow chart of another video processing method provided by an embodiment of the present application. This embodiment is applied to the case of improving the chrominance component of a video image. This embodiment can be performed by an encoding end (also referred to as an encoder). As shown in FIG7, this embodiment includes: S210-S250.

[0090] S210 : Filter the brightness component of the reconstructed image to obtain a corresponding brightness component reconstruction value.

[0091] S220 , filtering the luminance component reconstruction value to obtain a corresponding first chrominance component sample correction value and a corresponding second chrominance component sample correction value.

[0092] S230: Superimpose the first chroma component sample correction value and the first chroma component reconstruction value to obtain a corrected first chroma component reconstruction value, and superimpose the second chroma component sample correction value and the second chroma component reconstruction value to obtain a corrected second chroma component reconstruction value.

[0093] S240 , determining CC-ALF filter parameters based on the minimum mean square error principle between the corrected chroma component reconstruction value and the chroma component original pixel value.

[0094] S250: Write the CC-ALF filter parameters into the encoded video stream as video stream parameter information, and send it to the decoding end.

[0095] In one embodiment, after filtering the luminance component of the reconstructed image to obtain a corresponding luminance component reconstruction value, the method further includes:

[0096] The luminance component reconstruction value is classified using a pre-configured luminance component sample classification strategy to obtain a classified luminance component reconstruction value.

[0097] In one embodiment, filtering the luminance component of the reconstructed image to obtain a corresponding luminance component reconstruction value includes:

[0098] Perform one or more filters on the luminance component of the reconstructed image according to a preset order to obtain corresponding luminance component reconstruction values; wherein the filtering process includes at least one of the following:

[0099] Deblocking filtering;

[0100] Double-sideband filtering;

[0101] Pixel adaptive compensation processing;

[0102] Filtering using a fixed filter;

[0103] A filtering process using at least two cascaded fixed filters.

[0104] In one embodiment, the luminance component sample classification strategy includes at least one of the following: a classification strategy of an adaptive loop filter (ALF) filter processing mode; a classification strategy of an improved ALF filter processing mode; a classification strategy of basic sample residuals; and a classification strategy based on region division.

[0105] In one embodiment, after filtering the luminance component of the reconstructed image to obtain a corresponding luminance component reconstruction value, the method further includes:

[0106] An ALF filtering operation is performed on the first chroma component and the second chroma component in the reconstructed image respectively to obtain a corresponding first chroma component reconstruction value and a corresponding second chroma component reconstruction value.

[0107] In one embodiment, the video stream parameter information includes at least one of the following: a CC-ALF filter switch in a sequence parameter set SPS; a CC-ALF filter switch in a picture parameter set PPS; a CC-ALF filter switch and filter identifier in a picture header PH; a CC-ALF filter switch and filter identifier in a slice header SH; a filter identifier in a coding tree unit CTU; and CC-ALF filter parameter information in an adaptation parameter set APS.

[0108] The CC-ALF filter parameter information in the APS includes at least the following parameters: the number of CC-ALF filter coefficients; the absolute value of the CC-ALF filter coefficients; and the sign of the CC-ALF filter coefficients.

[0109] In one embodiment, the video stream parameter information further includes at least one of the following:

[0110] The input sample category identifier or index used by CC-ALF filtering is contained in the sequence parameter set, picture parameter set, picture header, slice header or coding tree unit;

[0111] The CC-ALF input sample category identifier or index of the chroma component is included in the adaptation parameter set.

[0112] In one embodiment, the CC-ALF filter parameter information in the adaptive parameter set corresponds to the first chroma component and the second chroma component.

[0113] In the first embodiment, FIG8 is a flowchart of a video processing method applied to a decoding end provided by an embodiment of the present application. This embodiment describes a cross-component loop filtering method based on a fixed filter, which is applied to the loop filtering module in video decoding to filter the reconstructed frames in the video. Among them, the input of the cross-component loop filtering is based on the output result of the fixed filter, including a single output value of a single fixed filter or a cascade of multiple fixed filters, or the superposition of the output signals of multiple fixed filters, which correspond to different filter templates and filter coefficients respectively. As shown in FIG8, this embodiment includes the following steps:

[0114] S310: The decoder parses the coded video stream to obtain video stream parameter information, and decodes the coded video stream to obtain a corresponding reconstructed image.

[0115] The decoder parses the encoded video stream to obtain video stream parameter information, including information identifying the APS parameter set. The ALF filter coefficient set includes a fixed subset and an APS subset. The fixed subset is a pre-trained filter coefficient subset, specified by the standard and not required for transmission. The APS subset is a filter coefficient subset generated using the Wiener filter principle based on the reconstructed image in the current video stream.

[0116] After decoding the encoded video stream, the decoded image needs to undergo Luma Mapping and Chroma Scaling (LMCS) to obtain a reconstructed image. LMCS is a new coding tool introduced in VVC that aims to improve video coding efficiency by fully utilizing the range of luminance values ​​and photoelectric conversion characteristics.

[0117] S320 , performing filtering processing on the brightness component of the reconstructed image according to a preset order to obtain a corresponding brightness component reconstruction value.

[0118] The filtering process may include DBF and SAO, and then a fixed filter is used to filter the filtering result to obtain a filtered brightness component reconstruction value.

[0119] In the actual filtering process, the order of filtering the brightness component of the reconstructed image can include various orders, for example:

[0120] 1) After performing DBF, BIF, and SAO processing on the luminance component of the reconstructed image, the filtering result is filtered using a single fixed filter or multiple cascaded fixed filters to obtain a reconstructed value of the luminance component. For example, FIG9 is a schematic diagram of the configuration of a CC-ALF filtering structure for a single input signal provided in an embodiment of the present application, as shown in FIG9;

[0121] 2) After performing DBF, BIF, and SAO processing on the luminance component of the reconstructed image, the filtering results are filtered using two or more fixed filters to obtain multiple luminance component reconstruction values;

[0122] 3) performing no DBF, BIF, and SAO processing on the luminance component of the reconstructed image, or performing only DBF filtering processing, or performing only SAO processing, and then filtering the filtering result using a single fixed filter or multiple cascaded fixed filters to obtain a luminance component reconstructed value, wherein the multiple cascaded fixed filters are constructed according to a pre-set cascade order;

[0123] 4) The luminance component of the reconstructed image is not subjected to DBF and SAO processing, or is subjected to DBF filtering processing only, or is subjected to BIF and SAO processing only, and the filtering results are filtered using multiple fixed filters to obtain multiple luminance component reconstruction values;

[0124] It should be noted that the above processing sequence is only one of the implementation methods and is not limited to this in the embodiments of the present application.

[0125] S330 , classifying the reconstructed values ​​of the brightness components of the reconstructed image in units of pixel blocks of a specified size.

[0126] The embodiments of the present application support classification strategies for luminance component reconstruction values ​​in multiple dimensions, including classification strategies based on traditional ALF filtering processing, classification strategies based on improved ALF filtering processing, classification strategies based on sample residuals, classification strategies based on region division, etc. It should be noted that the following classification strategy is only one implementation method and is not limited to this embodiment of the present application.

[0127] 1) Classification strategy of traditional ALF filtering processing method:

[0128] a. Calculate the Laplace gradient: For each 4x4 luminance block, calculate the one-dimensional Laplace operator gradient g in the horizontal 0°, vertical 90°, 135°, and 45° directions for each pixel in the 8x8 pixel block centered on the block h ,g v ,g d1 ,g d2 .

[0129] b. Calculate the directional factor D: First, calculate the ratio of the maximum and minimum values ​​of the horizontal and vertical gradients, and the ratio of the maximum and minimum values ​​of the diagonal gradients based on the Laplace gradient:

[0130] Among them, max(g h ,g v ) represents the maximum value of the gradient in the horizontal and vertical directions; min(g h ,g v ) represents the minimum value of the gradient in the horizontal and vertical directions; r h,v Indicates the ratio between the maximum value of the gradient in the horizontal and vertical directions and the minimum value of the gradient in the horizontal and vertical directions; max(g d1 ,g d2 ) represents the maximum gradient in the diagonal direction; min(g d1 ,g d2 ) represents the minimum gradient in the diagonal direction; r d1,d2 It represents the ratio between the maximum diagonal gradient and the minimum diagonal gradient.

[0131] Then compare it with the preset thresholds T1 and T2 to obtain the directionality factor.

[0132] c. Calculate the activity factor A: The activity factor A reflects the strength of the gradient and is obtained by looking up the Laplace gradient table.

[0133] d. Calculate the classification result: classIdx = 5*D + A

[0134] 2) Improved ALF filtering processing method classification strategy:

[0135] a. Calculate the Laplace gradient: For each 2x2 luminance block, calculate the one-dimensional Laplace operator gradient g in the horizontal 0°, vertical 90°, 135°, and 45° directions for each pixel in the 4x4 pixel block centered on the block h ,g v ,g d1 ,g d2 .

[0136] b. Calculate the directivity factor Calculate the ratio of the maximum and minimum values ​​of the gradient in the horizontal and vertical directions r1, and the ratio of the maximum and minimum values ​​of the gradient in the diagonal direction r h,v ,r d1,d2 , and then use the two ratios to compare with a set of pre-set thresholds Th = [1.25, 1.5, 2, 3, 4.5, 8] to calculate the horizontal / vertical edge strength E HV and the diagonal edge strength E D , and finally obtain the directional factor by looking up the table The value of .

[0137] c. Calculate activity factor Obtained by looking up the Laplace gradient table.

[0138] d. Calculate the classification results:

[0139] Among them, M D Directionality factor Total quantity

[0140] 3) Classification strategy based on sample residuals:

[0141] For each 2x2 luminance block, calculate the sum of the absolute values ​​of the residual samples in the 8x8 window centered on the block, then the classification result is: classIdx = sum>>(bit_depth-4)

[0142] Where bit_depth is the sample bit depth.

[0143] 4) Region Division and Classification Strategy: Divide the entire image or slice into multiple regions, each containing a consecutive integer number of CTUs, with the number of CTUs in each region being consistent. Classify the regions based on the brightness component of the reconstructed image, for example into 8 categories, and try to ensure that the number of CTUs in each category is equal.

[0144] S340: The decoder determines the CC-ALF filtering mode and filtering parameters of the luminance component according to the video stream parameter information.

[0145] S350 , filter the luminance component reconstruction value respectively to obtain a first chrominance component sample correction value and a second chrominance component sample correction value.

[0146] Among them, the first chroma component sample correction value can be recorded as The corrected value of the second chrominance component sample is recorded as In the video encoding stream, high-level syntax is used to represent information related to the input signal adaptive cross-component loop filtering method, including information such as the input signal adaptive cross-component loop filter switch, the cross-component loop filter category indicator, and the cross-component loop filter coefficients. The encoder writes the above information into the encoded video data at the encoding end for the decoder to decode the header information and perform cross-component filtering operations based on the obtained filter information. The video stream parameter information in the embodiment of the present application includes at least one of the following:

[0147] 1) CC-ALF filter switch in the sequence parameter set (SPS): Determine whether CC-ALF filtering is enabled in the current video sequence based on the sequence-level CC-ALF filter switch identifier in the encoded video bitstream.

[0148] 2) CC-ALF filter switch in the picture parameter set (PPS): The CC-ALF filter operation level, i.e., the video unit to which the filter information is applied, is determined based on the CC-ALF filter switch picture level identifier. The CC-ALF filter can be applied to the reconstructed picture or to one or more slices of the reconstructed picture.

[0149] 3) CC-ALF filter switch and filter identifier (ID) in the picture header (PH): Determine whether the chrominance components of the current image use CC-ALF filtering based on the CC-ALF filter switch in the picture header of the current image, including the first chrominance component Cb and the second chrominance component Cr, and determine the corresponding number of the filter parameters used by the current image in the APS based on the CC-ALF filter identifier (ID).

[0150] 4) CC-ALF filter switch and filter ID in the slice header (SH): Determine whether CC-ALF filtering is used for the chrominance components of the current slice, including the first chrominance component Cb and the second chrominance component Cr, based on the CC-ALF filter switch in the current image slice header, and determine the corresponding number of the filter parameters used in the current slice in the APS based on the CC-ALF filter identifier (ID).

[0151] 5) Filter ID in the slice header (SH): Determine the corresponding number of the filter parameters used by the current CTU in the APS according to the CC-ALF filter identifier (ID).

[0152] 6) The CC-ALF filter parameter information in the adaptive parameter set (APS) corresponds to the first chrominance component Cb and the second chrominance component Cr.

[0153] The CC-ALF filter parameter information in the APS includes at least the following parameters: the number of CC-ALF filter coefficients; the absolute value of the CC-ALF filter coefficients; and the sign of the CC-ALF filter coefficients.

[0154] In the process of filtering various samples of the luminance component in this embodiment, the input signal of the luminance component is the luminance component reconstruction value obtained in S320, that is, the sample reconstruction value after filtering by the fixed filter. Depending on the different settings of the fixed filter, the CC-ALF filtering process includes one of the following methods:

[0155] 1) Single input signal CC-ALF filtering: The input signal of the luminance component can select the luminance reconstruction value (i.e., Reconstructed Luma sample) of different nodes. In CC-ALF structure example 1 shown in FIG9 , the reconstructed value after filtering by DBF, BIF, SAO, and a fixed filter (i.e., Fixed filter F0) is selected as the input signal of the CC-ALF filter. FIG10 is a configuration diagram of another CC-ALF filtering structure for a single input signal provided by an embodiment of the present application. In CC-ALF structure example 2 shown in FIG10 , the reconstructed value of the luminance component after filtering by DBF and a fixed filter (i.e., Fixed filter F0) is selected as the input signal of the CC-ALF filter:

[0156] The filtering process is shown in Formula 1:

[0157] in, Represents the filtered pixel value (for example, the first chroma component sample correction value Alternatively, the second chroma component sample correction value ), R(x,y) represents the current pixel value to be filtered (for example, it can be the reconstruction value of the brightness component), f i,0 、f i,1 Indicates the limit value of the difference between the surrounding pixels covered by the CC-ALF filter template used by the decoder and the current pixel; c i, i = 0, ... K represents the filter coefficients at the corresponding positions in the filter template, which need to be parsed from the encoded video bitstream. The CC-ALF filter template can support a variety of shapes and sizes. The CC-ALF filter shape currently used by VVC is a 3×4 diamond filter. In the enhanced coding ECM reference software, the CC-ALF filter template is expanded to a 9*9 diamond with a total of 25 tap coefficients. This is not limited in this embodiment.

[0158] 2) CC-ALF filtering of multiple input signals, wherein the input signal may include, in addition to the luminance component reconstructed samples, luminance component sample residuals or pixel values ​​of the luminance component sample residuals after filtering with a fixed filter, which is not limited in this embodiment. For example, FIG11 is a configuration diagram of a CC-ALF filtering structure for multiple input signals provided in an embodiment of the present application. When the input signal of the CC-ALF filter includes: a luminance component reconstructed value after filtering with DBF, SAO, and BIF, a luminance component reconstructed value after filtering with DBF, SAO, BIF, and a fixed filter (i.e., Fixed filter F0), and a luminance component reconstructed value without filtering with DBF or SAO, the CC-ALF filtering structure is shown in FIG11.

[0159] The filtering process is shown in Formula 2:

[0160] in, Represents the filtered pixel value (for example, the first chroma component sample correction value Alternatively, the second chroma component sample correction value ), R(x,y) represents the current pixel value to be filtered (for example, it can be the reconstruction value of the brightness component), f i,0 、f i,1 Indicates the limit value of the difference between the surrounding pixels covered by the CC-ALF filter template used by the decoder and the current pixel; g i Indicates the limit value of the difference between the output value generated by the fixed filter and the current pixel value to be filtered; c i Indicates the CC-ALF filter coefficient corresponding to the fixed filter output value, which needs to be parsed in the encoded video stream, where i = K + 1, ... M; h i,0 、h i,1 Indicates the limit value of the difference between the luminance component sample value before DBF filtering and the current pixel in the area covered by the filter template.

[0161] S360 , perform ALF filtering on the first chroma component and the second chroma component respectively to obtain corresponding first chroma component reconstructed values ​​and second chroma component reconstructed values.

[0162] S370. Superimpose the first chroma component sample correction value and the first chroma component reconstruction value to obtain a corrected first chroma component reconstruction value, and superimpose the second chroma component correction value and the second chroma component reconstruction value to obtain a corrected second chroma component reconstruction value.

[0163] In the second embodiment, FIG12 is a flowchart of a video processing method applied to the encoding end provided by an embodiment of the present application. This embodiment describes a cross-component loop filtering method based on a fixed filter, which is applied to the loop filtering module in video encoding to filter the reconstructed frames in the video. Among them, the input of the cross-component loop filtering is based on the output result of the fixed filter, including a single output value of a single fixed filter or a cascade of multiple fixed filters, or the superposition of the output signals of multiple fixed filters, which correspond to different filter templates and filter coefficients respectively. As shown in FIG12, this embodiment includes the following steps:

[0164] S410: The encoder obtains a reconstructed image corresponding to the current image according to the existing coding information.

[0165] S420 , performing filtering processing on the brightness component of the reconstructed image according to a preset sequence to obtain a corresponding brightness component reconstruction value.

[0166] The filtering process may include DBF and SAO, and then a fixed filter is used to filter the filtering result to obtain a filtered brightness component reconstruction value.

[0167] In the actual filtering process, there may be multiple orders for filtering the brightness component of the reconstructed image. Please refer to the description of S320 in the above embodiment, which is not limited in this embodiment.

[0168] S430 , performing ALF filtering on the first chroma component and the second chroma component in the reconstructed image respectively to obtain a first chroma component reconstructed value and a second chroma component reconstructed value.

[0169] S440 , classifying the reconstructed values ​​of the brightness components of the reconstructed image in units of pixel blocks of a specified size.

[0170] This embodiment supports multiple dimensional luminance component sample classification strategies, including classification strategies based on traditional ALF filtering processing methods, improved ALF classification strategies, classification strategies based on sample residuals, and classification strategies based on region division. It should be noted that the above classification method is only one implementation method and is not limited to this embodiment of the present application.

[0171] S450: Filter the luminance component reconstruction value to obtain a corresponding first chrominance component sample correction value and a corresponding second chrominance component sample correction value.

[0172] The luminance component reconstruction values ​​of each category are filtered to obtain corresponding first chrominance component sample correction values ​​and second chrominance component sample correction values.

[0173] S460: Superimpose the first chroma component sample correction value and the first chroma component reconstruction value to obtain a corrected first chroma component reconstruction value, and superimpose the second chroma component sample correction value and the second chroma component reconstruction value to obtain a corrected second chroma component reconstruction value.

[0174] In the process of filtering the luminance component reconstruction value in this embodiment, the input signal of the luminance component is the luminance component reconstruction value obtained in step S420, that is, the luminance component reconstruction value after filtering by the fixed filter. Depending on the different settings of the fixed filter, the CC-ALF filtering process includes one of the following methods:

[0175] 1) CC-ALF filtering of a single input signal. The filtering process is as shown in formula (1) in the first embodiment above. There is no limitation on the shape and size of the CC-ALF filter template.

[0176] 2) CC-ALF filtering of multiple input signals, where the input signals may include, in addition to the reconstructed luminance component samples, luminance component sample residuals or pixel values ​​of the luminance component sample residuals filtered by a fixed filter. This is not limited in this embodiment, and the template shape and size of the CC-ALF filter are also not limited.

[0177] S470 , determining CC-ALF filter parameters based on the minimum mean square error principle between the corrected chroma component reconstruction value and the chroma component original pixel value.

[0178] For each filter class, all pixel blocks of a specified size that use this type of filter are taken as a whole, and the Wiener-Hough equation is used to calculate the CC-ALF filter parameters so that the minimum mean square error (MSE) between the output value after CC-ALF filtering and the result of superimposing the chrominance component and the original pixel value of the chrominance component is minimized.

[0179] S480: Write the CC-ALF filter parameters into the encoded video stream as video stream parameter information, and send it to the decoding end.

[0180] In this embodiment, the video stream parameter information includes at least one of the following:

[0181] 1) CC-ALF filter switch in the sequence parameter set (SPS);

[0182] 2) CC-ALF filter switch in the picture parameter set (PPS);

[0183] 3) CC-ALF filter switch and filter ID in the picture header (PH), including the filter switch and filter ID of the first chrominance component Cb and the second chrominance component Cr.

[0184] 4) CC-ALF filter switch and filter ID in the slice header (SH), including the filter switch and filter ID of the first chroma component Cb and the second chroma component Cr.

[0185] 5) Filter ID in the slice header (SH).

[0186] 6) The CC-ALF filter parameter information in the adaptive parameter set (APS) corresponds to the first chrominance component Cb and the second chrominance component Cr.

[0187] The CC-ALF filter parameter information in the APS includes at least the following parameters: the number of CC-ALF filter coefficients; the absolute value of the CC-ALF filter coefficients; and the sign of the CC-ALF filter coefficients.

[0188] In the third embodiment, this embodiment describes an input signal adaptive cross-component loop filtering method, which is applied to the loop filtering module in video decoding to filter the reconstructed frames in the video. Among them, the input signal of the cross-component loop filtering provides a variety of schemes, including a single fixed filter or a single output value of multiple fixed filters cascaded, or the superposition of the output signals of multiple fixed filters, corresponding to different filter templates and filter coefficients respectively. The decoder determines the cross-component loop filtering mode and filter coefficients based on the parameter information in the bitstream to complete the filtering process. The steps included in the cross-component loop filtering process in this embodiment are the same as the steps included in the cross-component loop filtering process in the first embodiment above. The difference between the two is that the parameters included in the video bitstream parameter information are different.

[0189] Step 1: The decoding end parses the encoded video stream to obtain video stream parameter information, and decodes the encoded video stream to obtain the corresponding reconstructed image.

[0190] Same as S310 in the first embodiment.

[0191] Step 2: Filter the brightness component of the reconstructed image according to a preset order to obtain a corresponding brightness component reconstruction value.

[0192] Same as S320 in the above first embodiment.

[0193] Step 3: Classify the reconstructed values ​​of the brightness components of the reconstructed image in units of pixel blocks of a specified size.

[0194] Same as S330 in the above first embodiment.

[0195] Step 4: The decoder determines the filtering input sample category, filtering mode and filtering parameters of the luminance component CC-ALF according to the video stream parameter information.

[0196] Step 5: Filter the reconstructed values ​​of the luminance component to obtain the corrected sample values ​​of the first chrominance component. and the second chroma component sample correction value

[0197] In this embodiment, the video stream parameter information includes at least one of the following:

[0198] 1) CC-ALF filter switch in the sequence parameter set (SPS): Determine whether CC-ALF filtering is enabled in the current video sequence based on the sequence-level CC-ALF filter switch identifier in the encoded video bitstream.

[0199] 2) CC-ALF filter switch in the picture parameter set (PPS): The CC-ALF filter operation level, i.e., the video unit to which the filter information is applied, is determined based on the CC-ALF filter switch picture level identifier. The CC-ALF filter can be applied to the reconstructed picture or to one or more slices of the reconstructed picture.

[0200] 3) CC-ALF filter switch, filter ID, and input sample category identifier or index used for CC-ALF filtering in the picture header (PH): Determine whether CC-ALF filtering is used for the chrominance components of the current image, including the first chrominance component Cb and the second chrominance component Cr, based on the CC-ALF filter switch in the picture header of the current image, and determine the corresponding number of the filter parameters used in the current image in the APS based on the CC-ALF filter number (ID); Determine the source of the input samples of the CC-ALF filter of the current image based on the CC-ALF input sample category identifier or index.

[0201] 4) CC-ALF filter switch, filter ID, and input sample category identifier or index used for CC-ALF filtering in the slice header (SH): Determine whether CC-ALF filtering is used for the chrominance components of the current slice, including the first chrominance component Cb and the second chrominance component Cr, based on the CC-ALF filter switch in the current image slice header, and determine the corresponding number of the filter parameters used in the current slice in the APS based on the CC-ALF filter number (ID); Determine the source of the input samples of the CC-ALF filter of the current image based on the CC-ALF input sample category identifier or index.

[0202] 5) The filter ID in the coding tree unit (CTU) and the input sample category identifier or index used for CC-ALF filtering: Determine the corresponding number of the filter parameter used in the current CTU in the APS based on the CC-ALF filter number (ID); Determine the input sample source of the CC-ALF filter of the current image based on the CC-ALF input sample category identifier or index.

[0203] 6) The CC-ALF filter parameter information in the adaptive parameter set (APS) corresponds to the first chrominance component Cb and the second chrominance component Cr.

[0204] The CC-ALF input sample category identifier or index of the chroma component, where different identifiers or indices represent different input samples or input sample combinations of the filter, are pre-specified by the encoder and decoder.

[0205] The CC-ALF filter parameter information in the APS includes at least the following parameters: the number of CC-ALF filter coefficients; the absolute value of the CC-ALF filter coefficients; and the sign of the CC-ALF filter coefficients.

[0206] The filtering process for various samples of the luminance component in this embodiment is consistent with step S350 in the first embodiment.

[0207] Step 6: Perform ALF filtering on the chroma component and correct the first chroma component sample value The first chroma component reconstruction value is superimposed to obtain the corrected first chroma component reconstruction value, and the first chroma component sample correction value is superimposed to obtain the corrected first chroma component reconstruction value. The modified second chrominance component reconstructed value is superimposed on the modified second chrominance component reconstructed value to obtain the modified second chrominance component reconstructed value.

[0208] In a fourth embodiment, this embodiment describes an input signal adaptive cross-component loop filtering method, which is applied to a loop filtering module in video encoding to filter reconstructed frames in the video. The input signal of the cross-component loop filtering supports multiple schemes, including a single fixed filter or a single output value of a cascade of multiple fixed filters, or the superposition of the output signals of multiple fixed filters. The encoder uses different filtering methods to perform filtering and cost calculation (distortion between the reconstructed frame and the original frame) based on the reconstructed pixel values ​​and the original pixel values ​​of the image. The optimal method is selected based on the RDcost of different filtering methods to complete the filtering, and the corresponding filtering method parameter information such as the filtering method indicator and filtering coefficient is written into the video encoding bitstream.

[0209] Step 1: The encoder obtains the reconstruction value of the brightness component of the current image based on the existing encoding information.

[0210] Step 2: Filter the brightness component of the reconstructed image according to a preset order to obtain a corresponding brightness component reconstruction value.

[0211] The filtering process may include DBF and SAO, and then a fixed filter is used to filter the filtering result to obtain a filtered brightness reconstruction value.

[0212] In the actual filtering process, there may be multiple orders for filtering the brightness component of the reconstructed image. Please refer to the description of S320 in the first embodiment, which is not limited in this application.

[0213] Step 3: Perform ALF filtering on the first chrominance component Cb and the second chrominance component Cr in the reconstructed image respectively to obtain a reconstructed value of the first chrominance component Cb and a reconstructed value of the second chrominance component Cr.

[0214] Step 4: Classify the reconstructed values ​​of the brightness components of the reconstructed image in units of pixel blocks of a specified size.

[0215] This embodiment supports multiple dimensional luminance component sample classification strategies, including classification strategies based on traditional ALF filtering processing methods, improved ALF classification strategies, classification strategies based on sample residuals, classification strategies based on region division, etc. It should be noted that the above classification method is only one implementation method and is not limited in this application.

[0216] Step 5: Filter the luminance component reconstruction value to obtain the corresponding first chrominance component sample correction value and second chrominance component sample correction value.

[0217] The luminance component reconstruction values ​​of each category are filtered to obtain corresponding first chrominance component sample correction values ​​and second chrominance component sample correction values.

[0218] For each filtering scheme, repeat step 5, calculate the cost of each filtering scheme respectively, select the scheme with the minimum cost as the final filtering scheme, complete the filtering process according to the relevant filter coefficients, and correct the first chrominance component of the filtered output. The reconstructed value of the first chroma component obtained by ALF filtering is superimposed to obtain the corrected reconstructed value of the first chroma component and the corrected value of the second chroma component output by filtering. The modified second chrominance component reconstructed values ​​are superimposed with the second chrominance component reconstructed values ​​after ALF filtering to obtain corrected second chrominance component reconstructed values.

[0219] The CC-ALF filtering scheme in this embodiment supports two types of settings, and you can choose either one during implementation:

[0220] 1) Filtering scheme based on a single input signal: The filtering process for a single input signal based on a fixed filter is as shown in formula (1) in the first embodiment, with no restrictions on the shape and size of the CC-ALF filter template. A candidate range of input signals is pre-set at both the encoding and decoding ends, and an index value cc_idx corresponding to each input signal is preset, for example:

[0221] Luminance component after SAO filtering and fixed filter F0 filtering, cc_idx = 0;

[0222] Luminance component after SAO filtering and cascade filtering of fixed filter F0 and fixed filter F1, cc_idx = 1;

[0223] The luminance component after DBF filtering and fixed filter F0 filtering, cc_idx = 2;

[0224] …

[0225] 2) Filtering scheme based on multiple input signals: This scheme supports using the brightness reconstruction values ​​of multiple nodes in the loop filter as CC-ALF filter input signals. The filtering process is as shown in formula (2) in the first embodiment. There is no restriction on the shape and size of the CC-ALF filter template. The candidate range of each group of input signals is pre-set at both the encoding and decoding ends, and the index value cc_idx corresponding to each group of input signals is preset, for example:

[0226] Luminance reconstruction value after SAO filtering, reconstruction value after SAO output and then processed by fixed filter F0, reconstruction value after SAO output and then processed by fixed filter F1, cc_idx = 0;

[0227] Luminance reconstruction value after SAO filtering, reconstruction value after SAO output and then cascade filtering by fixed filter F0 and fixed filter F1, reconstruction value without DBF filtering, cc_idx = 1;

[0228] Luminance reconstruction value without DBF filtering, reconstruction value without DBF filtering and processed only by fixed filter F0, reconstruction value without DBF filtering and processed only by fixed filter F1, cc_idx=2;

[0229] …

[0230] It should be noted that the above settings of the input signals and indexes are only for explanation and are not limited in this embodiment.

[0231] Step 6: Superimpose the first chroma component sample correction value and the first chroma component reconstruction value to obtain a corrected first chroma component reconstruction value, and superimpose the second chroma component sample correction value and the second chroma component reconstruction value to obtain a corrected second chroma component reconstruction value.

[0232] Step 7: Determine the CC-ALF filter parameters based on the minimum mean square error principle between the corrected chrominance component reconstruction value and the chrominance component original pixel value.

[0233] For each filter class, all pixel blocks of a specified size that use this type of filter are taken as a whole, and the Wiener-Hough equation is used to calculate the CC-ALF filter parameters so that the minimum mean square error (MSE) between the output value after CC-ALF filtering and the result of superimposing the chrominance component and the original pixel value of the chrominance component is minimized.

[0234] Step 8: Write the CC-ALF filter parameter information into the encoded video stream as video stream parameter information, and send it to the decoding end.

[0235] In this embodiment, the video stream parameter information includes at least one of the following:

[0236] 1) CC-ALF filter switch in the sequence parameter set (SPS).

[0237] 2) CC-ALF filter switch in the picture parameter set (PPS).

[0238] 3) CC-ALF filter switch, filter ID, and input sample category identifier or index used by CC-ALF filtering in the picture header (PH).

[0239] 4) CC-ALF filter switch, filter ID, and input sample category identifier or index used by CC-ALF filtering in the slice header (SH).

[0240] 5) The filter ID in the coding tree unit (CTU), and the input sample class identifier or index used by CC-ALF filtering.

[0241] 6) The CC-ALF filter parameter information in the adaptive parameter set (APS) corresponds to the first chrominance component Cb and the second chrominance component Cr.

[0242] The CC-ALF filter parameter information in the APS includes at least the following parameters: CC-ALF input sample category identifier or index; number of CC-ALF filter coefficients; absolute value of CC-ALF filter coefficients; and sign of CC-ALF filter coefficients.

[0243] In one embodiment, FIG13 is a block diagram of a video processing device provided by an embodiment of the present application. This embodiment is applied to a decoding end. As shown in FIG13 , the video processing device in this embodiment includes: a first filter 510, a first determination module 520, a second filter 530, and a second determination module 540.

[0244] The first filter 510 is configured to filter the luminance component of the reconstructed image to obtain a corresponding luminance component reconstruction value.

[0245] The first determining module 520 is configured to determine a luminance component filtering mode and luminance component filtering parameters according to the video stream parameter information.

[0246] The second filter 530 is configured to filter the luminance component reconstruction value using a luminance component filtering method and luminance component filtering parameters to obtain a corresponding first chrominance component sample correction value and a corresponding second chrominance component sample correction value.

[0247] The second determination module 540 is configured to superimpose the first chroma component sample correction value and the first chroma component reconstruction value to obtain a corrected first chroma component reconstruction value, and to superimpose the second chroma component sample correction value and the second chroma component reconstruction value to obtain a corrected second chroma component reconstruction value.

[0248] In one embodiment, before filtering the luminance component of the reconstructed image to obtain the corresponding luminance component reconstruction value, the video processing device applied to the decoding end further includes:

[0249] The parsing module is configured to parse the received coded video stream to obtain corresponding video stream parameter information;

[0250] The decoding module is configured to decode the encoded video stream to obtain a corresponding reconstructed image.

[0251] In one embodiment, after filtering the luminance component of the reconstructed image to obtain the corresponding luminance component reconstruction value, the video processing device applied to the decoding end further includes:

[0252] The third filter is configured to perform ALF filtering operations on the first chroma component and the second chroma component in the reconstructed image respectively to obtain corresponding first chroma component reconstruction values ​​and second chroma component reconstruction values.

[0253] In one embodiment, before filtering the luminance component reconstruction value using the luminance component filtering method and the luminance component filtering parameters, the video processing device applied to the decoding end further includes:

[0254] The classification module is configured to classify the brightness component reconstruction value using a pre-configured brightness component sample classification strategy to obtain a classified brightness component reconstruction value.

[0255] In one embodiment, filtering the luminance component reconstruction value using a luminance component filtering method and luminance component filtering parameters includes:

[0256] Each category of the luminance component reconstruction value is filtered, wherein the filtering processes of different categories use different luminance component filtering parameters and luminance component filtering methods.

[0257] In one embodiment, the luminance component sample classification strategy includes at least one of the following: a classification strategy of an adaptive loop filter (ALF) filter processing mode; a classification strategy of an improved ALF filter processing mode; a classification strategy of basic sample residuals; and a classification strategy based on region division.

[0258] In one embodiment, filtering the luminance component of the reconstructed image to obtain a corresponding luminance component reconstruction value includes:

[0259] Perform one or more filters on the luminance component of the reconstructed image according to a preset order to obtain corresponding luminance component reconstruction values; wherein the filtering process includes at least one of the following:

[0260] Deblocking filtering;

[0261] Double-sideband filtering B processing;

[0262] Pixel adaptive compensation processing;

[0263] Filtering using a fixed filter;

[0264] A filtering process using at least two cascaded fixed filters.

[0265] In one embodiment, filtering the luminance component of the reconstructed image to obtain a corresponding luminance component reconstruction value includes:

[0266] The luminance component of the reconstructed image is filtered to obtain one or more luminance component reconstruction values.

[0267] In one embodiment, the video stream parameter information includes at least one of the following: a CC-ALF filter switch in a sequence parameter set SPS; a CC-ALF filter switch in a picture parameter set PPS; a CC-ALF filter switch and filter identifier in a picture header PH; a CC-ALF filter switch and filter identifier in a slice header SH; a filter identifier in a coding tree unit CTU; and CC-ALF filter parameter information in an adaptation parameter set APS.

[0268] The CC-ALF filter parameter information in the APS includes at least the following parameters: the number of CC-ALF filter coefficients; the absolute value of the CC-ALF filter coefficients; and the sign of the CC-ALF filter coefficients.

[0269] In one embodiment, the video stream parameter information further includes at least one of the following:

[0270] The input sample category identifier or index used by CC-ALF filtering is contained in the sequence parameter set, picture parameter set, picture header, slice header or coding tree unit;

[0271] The CC-ALF input sample category identifier or index of the chroma component is included in the adaptation parameter set.

[0272] In one embodiment, the CC-ALF filter parameter information in the adaptive parameter set corresponds to the first chroma component and the second chroma component.

[0273] In one embodiment, filtering the luminance component reconstruction value using a luminance component filtering method and luminance component filtering parameters includes:

[0274] Filtering the luminance component reconstruction value according to a preset luminance component filtering method and luminance component filtering parameters;

[0275] Alternatively, the luminance component reconstruction value is filtered according to the luminance component filtering mode and luminance component filtering parameters specified in the video stream parameter information.

[0276] In one embodiment, filtering the luminance component reconstructed value according to a preset luminance component filtering mode and luminance component filtering parameters includes:

[0277] Perform CC-ALF filtering on the brightness component of the current image according to the CC-ALF filter switch;

[0278] Determine the CC-ALF filter coefficients and filter the luminance component reconstruction value according to the preset luminance component filtering method.

[0279] In one embodiment, filtering the reconstructed luminance component value according to the luminance component filtering mode and luminance component filtering parameters specified in the video stream parameter information includes:

[0280] Perform CC-ALF filtering on the brightness component of the current image according to the CC-ALF filter switch;

[0281] Determining the number and type of luminance component reconstruction values ​​used in CC-ALF filtering based on an input sample category identifier or index used in CC-ALF filtering;

[0282] Determine the CC-ALF filter coefficients and filter the luminance component reconstruction value.

[0283] The video processing device provided in this embodiment is configured to implement the video processing method applied to the decoding end in the embodiment shown in FIG6 . The implementation principle and technical effects of the video processing device provided in this embodiment are similar and will not be described in detail here.

[0284] In one embodiment, FIG14 is a block diagram of another video processing device provided by an embodiment of the present application. This embodiment is applied to an encoding end. As shown in FIG14 , the video processing device in this embodiment includes: a first filter 610, a second filter 620, a first determination module 630, a second determination module 640, and a sending module 650.

[0285] The first filter 610 is configured to filter the luminance component of the reconstructed image to obtain a corresponding luminance component reconstruction value.

[0286] The second filter 620 is configured to filter the luminance component reconstruction value to obtain the corresponding first chrominance component sample correction value and second chrominance component sample correction value.

[0287] The first determination module 630 is configured to superimpose the first chroma component sample correction value and the first chroma component reconstruction value to obtain a corrected first chroma component reconstruction value, and to superimpose the second chroma component sample correction value and the second chroma component reconstruction value to obtain a corrected second chroma component reconstruction value.

[0288] The second determination module 640 is configured to determine the CC-ALF filter parameters based on the minimum mean square error principle between the corrected chroma component reconstruction value and the chroma component original pixel value.

[0289] The sending module 650 is configured to write the CC-ALF filter parameters as video stream parameter information into the encoded video stream and send it to the decoding end.

[0290] In one embodiment, after filtering the luminance component of the reconstructed image to obtain the corresponding luminance component reconstruction value, the video processing device applied to the encoding end further includes:

[0291] The classification module is configured to classify the brightness component reconstruction value using a pre-configured brightness component sample classification strategy to obtain a classified brightness component reconstruction value.

[0292] In one embodiment, filtering the luminance component of the reconstructed image to obtain a corresponding luminance component reconstruction value includes:

[0293] Perform one or more filters on the luminance component of the reconstructed image according to a preset order to obtain corresponding luminance component reconstruction values; wherein the filtering process includes at least one of the following:

[0294] Deblocking filtering;

[0295] Double-sideband filtering;

[0296] Pixel adaptive compensation processing;

[0297] Filtering using a fixed filter;

[0298] A filtering process using at least two cascaded fixed filters.

[0299] In one embodiment, the luminance component sample classification strategy includes at least one of the following: a classification strategy of an adaptive loop filter (ALF) filter processing mode; a classification strategy of an improved ALF filter processing mode; a classification strategy of basic sample residuals; and a classification strategy based on region division.

[0300] In one embodiment, after filtering the luminance component of the reconstructed image to obtain the corresponding luminance component reconstruction value, the video processing device applied to the encoding end further includes:

[0301] The third filtering module is configured to perform ALF filtering operations on the first chroma component and the second chroma component in the reconstructed image respectively to obtain corresponding first chroma component reconstruction values ​​and second chroma component reconstruction values.

[0302] In one embodiment, the video stream parameter information includes at least one of the following: a CC-ALF filter switch in a sequence parameter set SPS; a CC-ALF filter switch in a picture parameter set PPS; a CC-ALF filter switch and filter identifier in a picture header PH; a CC-ALF filter switch and filter identifier in a slice header SH; a filter identifier in a coding tree unit CTU; and CC-ALF filter parameter information in an adaptation parameter set APS.

[0303] The CC-ALF filter parameter information in the APS includes at least the following parameters: the number of CC-ALF filter coefficients; the absolute value of the CC-ALF filter coefficients; and the sign of the CC-ALF filter coefficients.

[0304] In one embodiment, the video stream parameter information further includes at least one of the following:

[0305] The input sample category identifier or index used by CC-ALF filtering is contained in the sequence parameter set, picture parameter set, picture header, slice header or coding tree unit;

[0306] The CC-ALF input sample category identifier or index of the chroma component is included in the adaptation parameter set.

[0307] In one embodiment, the CC-ALF filter parameter information in the adaptive parameter set corresponds to the first chroma component and the second chroma component.

[0308] The video processing device provided in this embodiment is configured to implement the video processing method applied to the encoding end in the embodiment shown in FIG7 . The implementation principle and technical effects of the video processing device provided in this embodiment are similar and will not be described in detail here.

[0309] In one embodiment, Figure 15 is a schematic diagram of the structure of a communication device provided by an embodiment of the present application. As shown in Figure 15, the device provided by the present application includes: a processor 710, a memory 720, and a communication module 730. The number of processors 710 in the device can be one or more, and Figure 15 uses one processor 710 as an example. The number of memories 720 in the device can be one or more, and Figure 15 uses one memory 720 as an example. The processor 710, memory 720, and communication module 730 of the device can be connected via a bus or other means, and Figure 15 uses a bus connection as an example. In this embodiment, the device can be a decoder or an encoder.

[0310] The memory 720, as a computer-readable storage medium, can be configured to store software programs, computer executable programs, and modules, such as program instructions / modules corresponding to the device of any embodiment of the present application (for example, the first filter 510, the first determination module 520, the second filter 530, and the second determination module 540 in the video processing device applied to the decoding end). The memory 720 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and applications required for at least one function; the data storage area may store data created according to the use of the device, etc. In addition, the memory 720 may include a high-speed random access memory and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 720 may further include a memory remotely located relative to the processor 710, and these remote memories may be connected to the device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0311] In the case where the communication device serves as a decoding end, the above-provided device can be configured to execute the video processing method applied to the decoding end provided in any of the above-mentioned embodiments, and have corresponding functions and effects.

[0312] In the case where the communication device serves as the encoding end, the above-mentioned device can be configured to execute the video processing method applied to the encoding end provided in any of the above-mentioned embodiments, and have corresponding functions and effects.

[0313] An embodiment of the present application also provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to execute a video processing method applied to a decoding end, the method comprising: filtering the luminance component of the reconstructed image to obtain a corresponding luminance component reconstruction value; determining a luminance component filtering method and luminance component filtering parameters based on video code stream parameter information; filtering the luminance component reconstruction value using the luminance component filtering method and the luminance component filtering parameters to obtain a corresponding first chroma component sample correction value and a second chroma component sample correction value; superimposing the first chroma component sample correction value with the first chroma component reconstruction value to obtain a corrected first chroma component reconstruction value, and superimposing the second chroma component sample correction value with the second chroma component reconstruction value to obtain a corrected second chroma component reconstruction value.

[0314] An embodiment of the present application also provides a storage medium containing computer-executable instructions. When executed by a computer processor, the computer-executable instructions are used to perform a video processing method applied to an encoding end. The method includes: filtering the luminance component of a reconstructed image to obtain a corresponding luminance component reconstruction value; filtering the luminance component reconstruction value to obtain a corresponding first chroma component sample correction value and a second chroma component sample correction value; superimposing the first chroma component sample correction value with the first chroma component reconstruction value to obtain a corrected first chroma component reconstruction value, and superimposing the second chroma component sample correction value with the second chroma component reconstruction value to obtain a corrected second chroma component reconstruction value; determining CC-ALF filter parameters based on the principle of minimum mean square error between the corrected chroma component reconstruction value and the original pixel value of the chroma component; and writing the CC-ALF filter parameters as video stream parameter information into the encoded video stream and sending it to the decoding end.

[0315] It will be appreciated by those skilled in the art that the term user equipment encompasses any suitable type of wireless user equipment, such as a mobile phone, a portable data processing device, a portable web browser or a car-mounted mobile station.

[0316] In general, various embodiments of the present application may be implemented in hardware or dedicated circuits, software, logic, or any combination thereof. For example, some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software that can be executed by a controller, microprocessor, or other computing device, although the present application is not limited thereto.

[0317] Embodiments of the present application may be implemented by executing computer program instructions by a data processor of a mobile device, for example, in a processor entity, or by hardware, or by a combination of software and hardware. The computer program instructions may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages.

[0318] The block diagram of any logic flow in the drawings of the present application may represent program steps, or may represent interconnected logic circuits, modules and functions, or may represent a combination of program steps and logic circuits, modules and functions. A computer program may be stored on a memory. The memory may be of any type suitable for the local technical environment and may be implemented using any suitable data storage technology, such as, but not limited to, read-only memory (ROM), random access memory (RAM), optical memory devices and systems (digital versatile discs (DVD) or compact disks (CD)), etc. Computer-readable media may include non-transient storage media. A data processor may be of any type suitable for the local technical environment, such as, but not limited to, a general-purpose computer, a special-purpose computer, a microprocessor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), and a processor based on a multi-core processor architecture.

[0319] An embodiment of the present application further provides a computer program product, including a computer program, which, when executed by a processor, can implement the video processing method provided in any embodiment of the present application.

[0320] The computer program product, during implementation, may be written in one or more programming languages ​​or a combination thereof, for performing the operations of the present application, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0321] The above are merely preferred embodiments of the present application and are not intended to limit the present application. Those skilled in the art will readily appreciate that various modifications and variations are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A video processing method, applied to a decoding end, comprising: Filtering the brightness component of the reconstructed image to obtain a corresponding brightness component reconstruction value; Determine the luminance component filtering mode and luminance component filtering parameters according to the video code stream parameter information; Filtering the luminance component reconstruction value using the luminance component filtering method and the luminance component filtering parameters to obtain corresponding first chrominance component sample correction values and second chrominance component sample correction values; The first chroma component sample correction value is superimposed on the first chroma component reconstruction value to obtain a corrected first chroma component reconstruction value, and the second chroma component sample correction value is superimposed on the second chroma component reconstruction value to obtain a corrected second chroma component reconstruction value.

2. The method according to claim 1, before filtering the luminance component of the reconstructed image to obtain the corresponding luminance component reconstruction value, further comprising: Parse the received encoded video stream to obtain the corresponding video stream parameter information; Decode the encoded video stream to obtain the corresponding reconstructed image.

3. The method according to claim 1, after filtering the luminance component of the reconstructed image to obtain the corresponding luminance component reconstruction value, further comprising: An adaptive loop filtering (ALF) filtering operation is performed on the first chroma component and the second chroma component in the reconstructed image respectively to obtain a corresponding first chroma component reconstruction value and a corresponding second chroma component reconstruction value.

4. The method according to claim 1, before filtering the luminance component reconstruction value using the luminance component filtering mode and the luminance component filtering parameters, further comprising: The luminance component reconstruction value is classified using a pre-configured luminance component sample classification strategy to obtain a classified luminance component reconstruction value.

5. The method according to claim 1, wherein The filtering of the luminance component reconstruction value by using the luminance component filtering mode and the luminance component filtering parameters includes: Each category of the luminance component reconstruction value is filtered, wherein the filtering process of the luminance component reconstruction values of different categories uses different luminance component filtering parameters and luminance component filtering methods.

6. The method according to claim 4, wherein: The luminance component sample classification strategy includes at least one of the following: a classification strategy of an adaptive loop filtering (ALF) filtering processing mode; a classification strategy of an improved ALF filtering processing mode; a classification strategy of basic sample residuals; and a classification strategy based on region division.

7. The method according to any one of claims 1 to 6, wherein: The filtering of the brightness component of the reconstructed image to obtain a corresponding brightness component reconstruction value includes: Perform at least one filtering on the luminance component of the reconstructed image according to a preset order to obtain a corresponding luminance component reconstruction value; wherein the filtering process includes at least one of the following: Deblocking filtering; Double-sideband filtering; Pixel adaptive compensation processing; Filtering using a fixed filter; A filtering process using at least two cascaded fixed filters.

8. The method according to any one of claims 1 to 6, wherein: The filtering of the brightness component of the reconstructed image to obtain a corresponding brightness component reconstruction value includes: The luminance component of the reconstructed image is filtered to obtain at least one luminance component reconstruction value.

9. The method according to any one of claims 1 to 6, wherein: The video stream parameter information includes at least one of the following: a cross-component adaptive loop filter CC-ALF filter switch in a sequence parameter set SPS; a CC-ALF filter switch in a picture parameter set PPS; a CC-ALF filter switch and filter identifier in a picture header PH; a CC-ALF filter switch and filter identifier in a slice header SH; a filter identifier in a coding tree unit CTU; and CC-ALF filter parameter information in an adaptive parameter set APS. The CC-ALF filter parameter information in the APS includes at least the following parameters: the number of CC-ALF filter coefficients; the absolute value of CC-ALF filter coefficients; and the sign of CC-ALF filter coefficients.

10. The method according to claim 9, wherein: The video stream parameter information also includes at least one of the following: The input sample category identifier or index used by CC-ALF filtering is contained in the sequence parameter set, picture parameter set, picture header, slice header or coding tree unit; The CC-ALF input sample category identifier or index of the chroma component is included in the adaptation parameter set.

11. The method according to claim 9, wherein The CC-ALF filter parameter information in the adaptive parameter set corresponds to the first chroma component and the second chroma component.

12. The method according to claim 1, wherein Filtering the luminance component reconstruction value using the luminance component filtering method and the luminance component filtering parameters includes: Filtering the luminance component reconstruction value according to a preset luminance component filtering mode and the luminance component filtering parameters; Alternatively, the luminance component reconstruction value is filtered according to the luminance component filtering mode and the luminance component filtering parameters specified in the video stream parameter information.

13. The method according to claim 12, wherein: The filtering of the luminance component reconstruction value according to the preset luminance component filtering mode and the luminance component filtering parameter includes: Determine, according to the CC-ALF filter switch, whether to perform CC-ALF filtering on the luminance component of the current image; Determine the CC-ALF filter coefficients and filter the luminance component reconstruction value according to the preset luminance component filtering method.

14. The method according to claim 12, wherein: The filtering of the luminance component reconstruction value according to the luminance component filtering mode and the luminance component filtering parameters specified in the video stream parameter information includes: Determine, according to the CC-ALF filter switch, whether to perform CC-ALF filtering on the luminance component of the current image; Determining the number and type of luminance component reconstruction values used in CC-ALF filtering based on an input sample category identifier or index used in CC-ALF filtering; Determine the CC-ALF filter coefficients and filter the luminance component reconstruction value.

15. A video processing method, applied to an encoding end, comprising: Filtering the brightness component of the reconstructed image to obtain a corresponding brightness component reconstruction value; Filtering the luminance component reconstruction value to obtain a corresponding first chrominance component sample correction value and a second chrominance component sample correction value; Superimposing the first chroma component sample corrected value and the first chroma component reconstructed value to obtain a corrected first chroma component reconstructed value, and superimposing the second chroma component sample corrected value and the second chroma component reconstructed value to obtain a corrected second chroma component reconstructed value; The CC-ALF filter parameters are determined based on the principle of minimum mean square error between the corrected chroma component reconstruction value and the original pixel value of the chroma component; The CC-ALF filter parameters are written into the encoded video stream as video stream parameter information and sent to the decoding end.

16. The method according to claim 15, after filtering the luminance component of the reconstructed image to obtain a corresponding luminance component reconstruction value, further comprising: The luminance component reconstruction values are classified using a pre-configured luminance component sample classification strategy to obtain classified luminance component reconstruction values.

17. The method according to any one of claims 15 to 16, wherein: The filtering of the brightness component of the reconstructed image to obtain a corresponding brightness component reconstruction value includes: Perform at least one filtering on the luminance component of the reconstructed image according to a preset order to obtain a corresponding luminance component reconstruction value; wherein the filtering process includes at least one of the following: Deblocking filtering; Double-sideband filtering; Pixel adaptive compensation processing; Filtering using a fixed filter; A filtering process using at least two cascaded fixed filters.

18. The method according to claim 16, wherein The luminance component sample classification strategy includes at least one of the following: a classification strategy of an adaptive loop filtering (ALF) filtering processing mode; a classification strategy of an improved ALF filtering processing mode; a classification strategy of basic sample residuals; and a classification strategy based on region division.

19. The method according to claim 15, further comprising, after filtering the luminance component of the reconstructed image to obtain a corresponding luminance component reconstruction value: An ALF filtering operation is performed on the first chroma component and the second chroma component in the reconstructed image respectively to obtain a corresponding first chroma component reconstruction value and a corresponding second chroma component reconstruction value.

20. The method according to claim 15, wherein The video stream parameter information includes at least one of the following: a CC-ALF filter switch in a sequence parameter set SPS; a CC-ALF filter switch in a picture parameter set PPS; a CC-ALF filter switch and filter identifier in a picture header PH; a CC-ALF filter switch and filter identifier in a slice header SH; a filter identifier in a coding tree unit CTU; and CC-ALF filter parameter information in an adaptive parameter set APS. The CC-ALF filter parameter information in the APS includes at least the following parameters: the number of CC-ALF filter coefficients; the absolute value of CC-ALF filter coefficients; and the sign of CC-ALF filter coefficients.

21. The method according to claim 20, wherein The video stream parameter information also includes at least one of the following: The input sample category identifier or index used by CC-ALF filtering is contained in the sequence parameter set, picture parameter set, picture header, slice header or coding tree unit; The CC-ALF input sample category identifier or index of the chroma component is included in the adaptation parameter set.

22. The method according to claim 20, wherein The CC-ALF filter parameter information in the adaptive parameter set corresponds to the first chroma component and the second chroma component.

23. A communication device comprising: memory, and at least one processor; The memory is configured to store at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1 to 22.

24. A storage medium storing a computer program, wherein the computer program implements the method according to any one of claims 1 to 22 when executed by a processor.

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