Image component prediction method, encoder, decoder and computer storage medium

Abstract

The embodiment of the invention discloses an image component prediction method, an encoder and a computer storage medium, and the method comprises the steps: carrying out the encoding of a chrominance component in the encoding of the image component, and obtaining a prediction value of a brightness component according to the encoded chrominance component.

Description

[0001] This application is a divisional application of PCT international patent application PCT / CN2019 / 124114 with an application date of December 9, 2019, which entered the Chinese national phase with Chinese patent application number 201980091480.8 and the invention name being “Prediction method, encoder, decoder and computer storage medium for image components”. Technical Field

[0002] The embodiments of the present application relate to intra-frame prediction technology in the field of video coding, and more particularly to a prediction method, encoder, decoder, and computer storage medium for image components. Background Art

[0003] In the next generation video coding standard H.266 or Versatile Video Coding (VVC), cross-component prediction can be achieved through the cross-component linear model prediction method (CCLM). Through cross-component prediction, the chrominance component can be predicted by the luminance component based on the dependency between the components.

[0004] Currently, the luminance component used for prediction needs to be downsampled to the same resolution as the chrominance component to be predicted, and then prediction is performed between luminance and chrominance at the same resolution to achieve prediction of the luminance component to one of the chrominance components.

[0005] However, since the luminance component has rich texture and the chrominance component is relatively flat, using the luminance component to predict the chrominance component results in a large deviation between the predicted chrominance component and the true chrominance value, resulting in low accuracy of the predicted value, which affects the efficiency of encoding and decoding. Summary of the Invention

[0006] The embodiments of the present application provide a prediction method, encoder, decoder and computer storage medium for image components, which can realize predictive coding of chrominance components to luminance components, improve the accuracy of luminance component prediction, and make the predicted value of the luminance component closer to the actual pixel value of the luminance component.

[0007] The technical solution of the embodiment of the present application can be implemented as follows:

[0008] In a first aspect, an embodiment of the present application provides a method for predicting image components, the method comprising:

[0009] In the encoding of image components, the chrominance components are encoded;

[0010] Get the predicted value of the luma component based on the encoded chroma component.

[0011] In a second aspect, an embodiment of the present application provides a method for predicting image components, the method comprising:

[0012] In decoding of image components, chrominance components are decoded;

[0013] Get the predicted value of the luma component based on the decoded chroma component.

[0014] In a third aspect, an embodiment of the present application provides an encoder, comprising:

[0015] An encoding module configured to encode a chrominance component in encoding of an image component;

[0016] The first acquisition module is configured to acquire a predicted value of a luminance component according to the encoded chrominance component.

[0017] In a fourth aspect, an embodiment of the present application provides a decoder, comprising:

[0018] A decoding module configured to decode a chrominance component during decoding of an image component;

[0019] The second acquisition module is configured to acquire a predicted value of the luminance component according to the decoded chrominance component.

[0020] In a fifth aspect, an embodiment of the present application provides an encoder, comprising:

[0021] A processor and a storage medium storing instructions executable by the processor, wherein the storage medium relies on the processor to perform operations through a communication bus, and when the instructions are executed by the processor, the image component prediction method described in one or more of the above embodiments is executed.

[0022] In a sixth aspect, an embodiment of the present application provides a decoder, comprising:

[0023] A processor and a storage medium storing instructions executable by the processor, wherein the storage medium relies on the processor to perform operations through a communication bus, and when the instructions are executed by the processor, the image component prediction method described in one or more of the above embodiments is executed.

[0024] In a seventh aspect, an embodiment of the present application provides a computer-readable storage medium, which stores executable instructions. When the executable instructions are executed by one or more processors, the processor executes the method for predicting image components described in one or more of the above embodiments.

[0025] An embodiment of the present application provides a method for predicting an image component, an encoder, a decoder, and a computer storage medium. The method includes: in encoding the image component, encoding the chrominance component, and obtaining a predicted value of the luminance component based on the encoded chrominance component; that is, in an embodiment of the present application, by first encoding and decoding the chrominance component, and then predicting the luminance component based on the encoded and decoded chrominance component, in this way, the luminance component is predicted by the chrominance component obtained by encoding and decoding, that is, the relatively flat chrominance component is first encoded and decoded, and then the luminance component with rich texture is predicted based on the chrominance component obtained by encoding and decoding, which can improve the accuracy of the luminance component prediction, so that the predicted value of the luminance component is closer to the actual pixel value of the luminance component. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A schematic flow chart of an optional method for predicting image components provided in an embodiment of the present application;

[0027] Figure 2 It is a structural diagram of a video coding system;

[0028] Figure 3 It is a structural diagram of a video decoding system;

[0029] Figure 4 A schematic flow chart of another optional method for predicting image components provided in an embodiment of the present application;

[0030] Figure 5 A schematic diagram of the structure of an optional encoder proposed in an embodiment of the present application;

[0031] Figure 6 A schematic diagram of the structure of an optional decoder proposed in an embodiment of the present application;

[0032] Figure 7 A schematic diagram of the structure of another optional encoder proposed in an embodiment of the present application;

[0033] Figure 8 A schematic structural diagram of another optional decoder proposed in an embodiment of the present application. DETAILED DESCRIPTION

[0034] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. It should be understood that the specific embodiments described herein are only used to explain the related applications and are not intended to limit the applications. It should also be noted that for ease of description, only the parts relevant to the related applications are shown in the drawings.

[0035] Example 1

[0036] In video images, image blocks are generally represented by first, second, and third image components. These components may include a luminance component and two chrominance components. Specifically, the luminance component is typically represented by the symbol Y, and the chrominance components are typically represented by the symbols Cb and Cr, with Cb representing the blue chrominance component and Cr representing the red chrominance component.

[0037] It should be noted that, in an embodiment of the present application, the first image component, the second image component and the third image component may be the luminance component Y, the blue chrominance component Cb and the red chrominance component Cr, respectively. For example, the first image component may be the luminance component Y, the second image component may be the red chrominance component Cr, and the third image component may be the blue chrominance component Cb. The embodiment of the present application does not specifically limit this.

[0038] Furthermore, in an embodiment of the present application, a commonly used sampling format in which luminance components and chrominance components are represented separately is also referred to as a YCbCr format, wherein the YCbCr format may include a 4:4:4 format, a 4:2:2 format, and a 4:2:0 format.

[0039] When a video image uses a YCbCr 4:2:0 format, if the luminance component of the video image is a current image block of 2N×2N size, the corresponding chrominance component is a current image block of N×N size, where N is the side length of the current image block. In the embodiments of the present application, the 4:2:0 format will be used as an example for description, but the technical solutions of the embodiments of the present application are also applicable to other sampling formats.

[0040] To further improve coding performance and efficiency, H.266 extends and improves Cross-component Prediction (CCP) and proposes Cross-component Linear Model Prediction (CCLM). In H.266, CCLM enables predictions from a first image component to a second image component, from a first image component to a third image component, and between a second image component and a third image component.

[0041] However, for CCLM, the luminance component of the current image block is first predicted, and then the chrominance component is predicted through the luminance component. However, since the luminance component has rich texture and the chrominance component is relatively flat, using the luminance component to predict the chrominance component results in a large deviation between the predicted chrominance component and the true chrominance value, resulting in low accuracy of the predicted value, which affects the efficiency of encoding and decoding.

[0042] The embodiment of the present application provides a method for predicting image components. Figure 1 A flowchart of an optional image component prediction method provided in an embodiment of the present application is shown as follows: Figure 1 As shown, the method may include:

[0043] S101: In encoding of image components, encoding chrominance components;

[0044] S102: Obtain a predicted value of the luminance component according to the encoded chrominance component.

[0045] The image component prediction method provided in the embodiment of the present application can be applied to an encoder or a decoder. Figure 2 It is a structural diagram of the video coding system. Figure 2As shown, the video coding system 200 includes a transform and quantization unit 201, an intra-frame estimation unit 202, an intra-frame prediction unit 203, a motion compensation unit 204, a motion estimation unit 205, an inverse transform and inverse quantization unit 206, a filter control analysis unit 207, a filtering unit 208, a coding unit 209 and a decoded image cache unit 210, etc., wherein the filtering unit 208 can implement deblocking filtering and sample adaptive offset (Sample Adaptive Offset, SAO) filtering, and the coding unit 209 can implement header information encoding and context-based adaptive binary arithmetic coding (Context-based Adaptive Binary Arithmatic Coding, CABAC). For the input original video signal, the coding tree block (Coding Tree A video coding block can be obtained by dividing the video coding block into a plurality of frames (CTUs) and then the residual pixel information obtained after intra-frame or inter-frame prediction is transformed by the transform and quantization unit 201, including transforming the residual information from the pixel domain to the transform domain and quantizing the obtained transform coefficients to further reduce the bit rate; the intra-frame estimation unit 202 and the intra-frame prediction unit 203 are used to perform intra-frame prediction on the video coding block; specifically, the intra-frame estimation unit 202 and the intra-frame prediction unit 203 are used to determine the intra-frame prediction mode to be used to encode the video coding block; the motion compensation unit 204 and the motion estimation unit 205 are used to perform inter-frame prediction coding of the received video coding block relative to one or more blocks in one or more reference frames to provide temporal prediction information; the motion estimation performed by the motion estimation unit 205 is a process of generating a motion vector, which can estimate the motion of the video coding block, and then the motion compensation unit 204 calculates the motion vector based on the motion vector determined by the motion estimation unit 205. After determining the intra-frame prediction mode, the intra-frame prediction unit 203 is further configured to provide the selected intra-frame prediction data to the encoding unit 209, and the motion estimation unit 205 also sends the calculated motion vector data to the encoding unit 209. In addition, the inverse transform and inverse quantization unit 206 is configured to reconstruct the video coding block and reconstruct a residual block in the pixel domain. The reconstructed residual block is subjected to the filter control analysis unit 207 and the filtering unit 208 to remove the block effect artifacts. The reconstructed residual block is then added to a predictive block in the frame of the decoded image buffer unit 210 to generate a reconstructed video coding block. The encoding unit 209 is configured to encode various coding parameters and quantized transform coefficients. In the CABAC-based coding algorithm, the context content can be based on adjacent coding blocks and can be used to encode information indicating the determined intra-frame prediction mode, thereby outputting the code stream of the video signal. The decoded image buffer unit 210 is configured to store the reconstructed video coding block for prediction reference.As the video image encoding proceeds, new reconstructed video encoding blocks are continuously generated, and these reconstructed video encoding blocks are stored in the decoded image buffer unit 210 .

[0046] Figure 3 It is a structural diagram of the video decoding system, such as Figure 3 As shown, the video decoding system 300 includes a decoding unit 301, an inverse transform and inverse quantization unit 302, an intra-frame prediction unit 303, a motion compensation unit 304, a filtering unit 305 and a decoded image buffer unit 306, etc., wherein the decoding unit 301 can implement header information decoding and CABAC decoding, and the filtering unit 305 can implement deblocking filtering and SAO filtering. The input video signal is processed by Figure 2 After the encoding process, the code stream of the video signal is output; the code stream is input into the video decoding system 300, and first passes through the decoding unit 301 to obtain the decoded transform coefficients; the transform coefficients are processed by the inverse transform and inverse quantization unit 302 to generate a residual block in the pixel domain; the intra-frame prediction unit 303 can be used to generate prediction data for the current video decoding block based on the determined intra-frame prediction mode and the data of the previously decoded block from the current frame or picture; the motion compensation unit 304 determines the prediction information for the video decoding block by analyzing the motion vector and other associated syntax elements, and uses the prediction information to generate the prediction data for the current video decoding block. The decoded video block is formed by summing the residual block from the inverse transform and inverse quantization unit 302 with the corresponding predictive block generated by the intra-frame prediction unit 303 or the motion compensation unit 304; the decoded video signal passes through the filtering unit 305 to remove blocking artifacts, thereby improving the video quality; the decoded video block is then stored in the decoded image buffer unit 306, which stores reference images for subsequent intra-frame prediction or motion compensation and is also used for outputting the video signal, that is, the restored original video signal is obtained.

[0047] It should be noted that S101 and S102 in the embodiment of the present application are mainly used in the following situations: Figure 2 The intra-frame prediction unit 203 shown is partly Figure 3 The intra-frame prediction unit 303 part is shown; that is, the embodiment of the present application can act on the encoder and the decoder at the same time, and the embodiment of the present application does not make any specific limitation on this.

[0048] In addition, in S101 and S102, in the encoding of the image components, one chroma component may be encoded and then the chroma component may be used to predict the luminance component, one chroma component may be encoded and then the chroma component may be used to predict another chroma component, two chroma components may be encoded first and then one chroma component may be used to predict the luminance component, or two chroma components may be used to predict the luminance component. Here, the embodiments of the present application do not make specific limitations on this.

[0049] In order to obtain a predicted value of the luminance component, in an optional embodiment, S102 may include:

[0050] Predicting a luminance component based on a first chroma component in the encoded chroma components and a second chroma component in the encoded chroma components to obtain a predicted value of the luminance component;

[0051] When the first chromaticity component is a blue chromaticity component, the second chromaticity component is a red chromaticity component; when the first chromaticity component is a red chromaticity component, the second chromaticity component is a blue chromaticity component.

[0052] Here, the first chroma component and the second chroma component in the encoded chroma components are used to predict the predicted value of the luminance component. For example, the first chroma component is Cb, the second chroma component is Cr, and the luminance component is Y, then Y can be predicted by Cb and Cr, or the first chroma component is Cr, the second chroma component is Cb, and the luminance component is Y, then Y can be predicted by Cb and Cr.

[0053] Furthermore, in order to predict the predicted value of the luminance component, in an optional embodiment, the prediction is performed based on the first chrominance component in the encoded chrominance components and the second chrominance component in the encoded chrominance components to obtain the predicted value of the luminance component, including:

[0054] For the current image block, obtain a reconstructed value of the first chroma component, a reconstructed value of the second chroma component, an adjacent reference value of the first chroma component, an adjacent reference value of the second chroma component, and an adjacent reference value of the luminance component;

[0055] Predicting according to the reconstructed value of the first chrominance component, the adjacent reference values ​​of the first chrominance component, and the adjacent reference values ​​of the luminance component to obtain a first predicted value of the luminance component;

[0056] Performing prediction based on the reconstructed value of the second chrominance component, the adjacent reference values ​​of the second chrominance component, and the adjacent reference values ​​of the luminance component to obtain a second predicted value of the luminance component;

[0057] A predicted value of the luminance component is determined based on the first predicted value and the second predicted value.

[0058] Among them, the current image block is the current image block to be encoded. Here, for the current image block, it is necessary to obtain the reconstruction value of the first chrominance component of the current image block and the reconstruction value of the second chrominance component of the current image block. The first chrominance component of the adjacent image block of the current image block is the adjacent reference value of the above-mentioned first chrominance component, the second chrominance component of the adjacent image block of the current image block is the adjacent reference value of the above-mentioned second chrominance component, and the luminance component of the adjacent image block of the current image block is the adjacent reference value of the luminance component. It should be noted that the adjacent image blocks of the above-mentioned current image block are the image blocks in the upper row and the image blocks in the left column of the current image block.

[0059] Then, after obtaining the above values, a first prediction value can be predicted based on the reconstructed value of the first chrominance component, the adjacent reference value of the first chrominance component and the adjacent reference value of the luminance component. A second prediction value can be predicted based on the reconstructed value of the second chrominance component, the adjacent reference value of the second chrominance component and the adjacent reference value of the luminance component. Then, the prediction value of the luminance component of the current image block is obtained based on the first prediction value and the second prediction value. In this way, a prediction value is predicted by each chrominance component, and finally the two predicted prediction values ​​are fused to obtain the prediction value of the luminance component of the current image block.

[0060] To obtain the first predicted value, in an optional embodiment, performing prediction based on the reconstructed value of the first chrominance component, the adjacent reference values ​​of the first chrominance component, and the adjacent reference values ​​of the luminance component to obtain the first predicted value of the luminance component includes:

[0061] Determining parameters of a prediction model according to adjacent reference values ​​of the first chrominance component and adjacent reference values ​​of the luminance component;

[0062] According to the reconstructed value of the first chrominance component, a prediction model is called to obtain a first prediction value.

[0063] After obtaining the reconstructed value of the first chrominance component and the adjacent reference value of the first chrominance component, the prediction model of the image component adopted above can be a linear model or a nonlinear model to predict the luminance component to obtain the first prediction value. Here, the embodiment of the present application does not make specific limitations.

[0064] Specifically, for the linear model, an inter-component linear model prediction mode is used in encoders of next-generation video coding standards, such as the H.266 / VVC early test model (Joint Exploration Model, JEM) or the VVC test model (VTM). For example, according to formula (1), the predicted value of the luminance component is constructed using the reconstructed chrominance value of the same coding block:

[0065] Pred L [i,j]=α·RecC [i,j]+β (1)

[0066] Among them, i, j represent the position coordinates of the sampling point in the current image block, i represents the horizontal direction, j represents the vertical direction, Pred L [i, j] represents the predicted value of the luminance component of the sampling point with coordinates i and j in the coding block, Rec C [i, j] represents the chrominance component reconstruction value of the sampling point with coordinates i and j in the current image block. α and β are the scaling factors of the linear model, which can be derived by minimizing the regression error of the adjacent reference values ​​of the chrominance component and the adjacent reference values ​​of the luminance component, as shown in the following formula (2):

[0067]

[0068] Wherein, L(n) represents the adjacent reference value of the luminance component (e.g., the left side and the top side), C(n) represents the adjacent reference value of the chrominance component (e.g., the left side and the top side), and N is the number of adjacent reference values ​​of the luminance component. α and β are also calculated in the decoder using formula (2).

[0069] Among them, using the adjacent reference value L(n) of the luminance component and the adjacent reference value C(n) of the chrominance component of the current image block, α and β can be calculated according to formula (2); then the chrominance component reconstruction value of the current image block is substituted into the linear model described in formula (2) to calculate the predicted value of the luminance component of the current image block.

[0070] In practical applications, the adjacent reference values ​​of the first chrominance component and the adjacent reference values ​​of the luminance component are substituted into formula (2) to obtain α and β, and then the reconstructed value of the first chrominance component is substituted into formula (1) to obtain the first predicted value; in this way, the first predicted value can be obtained using the linear model.

[0071] In addition to the above-mentioned linear model, the prediction model may also adopt a nonlinear model. On the basis of the above-mentioned linear model, the prediction model of the image component also proposes a nonlinear model calculation method.

[0072] Specifically, when calculating the parameters of the linear model, not only the adjacent reference values ​​of the chrominance component and the adjacent reference values ​​of the luminance component are considered, but also the correlation and similarity between the chrominance component reconstruction value of the current image block and the adjacent reference values ​​of the chrominance component are considered to obtain α and β in the existing linear model, so that the obtained linear model is more in line with the current chrominance component reconstruction value, and further obtains the luminance component prediction value of the current image block.

[0073] For example, in a nonlinear model, the adjacent reference values ​​of the chrominance component and the adjacent reference values ​​of the luminance component of the current image block are divided into two groups. Each group can be used as a separate training set for deriving linear model parameters, that is, each group can derive a set of parameters. Therefore, the problem of the linear model deviating from the expected model when there is a significant deviation between the adjacent reference values ​​of the chrominance component and the parameters corresponding to the current image block, or when there is a significant deviation between the adjacent reference values ​​of another chrominance component and the parameters corresponding to the current image block, can be overcome. As a result, when predicting the luminance component of the current image block based on this linear model, the prediction accuracy of the luminance component prediction value can be greatly improved.

[0074] For nonlinear models, adjacent reference values ​​and intermediate values ​​can be divided into two groups by setting a threshold, and a nonlinear model can be established based on the two groups of adjacent reference values ​​and reconstructed values.

[0075] The threshold value is used as a basis for classifying the adjacent reference values ​​of the chrominance components and the adjacent reference values ​​of the luminance components of the current image block, and is also used as a basis for classifying the chrominance component reconstruction value of the current image block. The threshold value is used to indicate the set value based on which multiple calculation models are established, and the size of the threshold value is related to the chrominance component reconstruction value of all sampling points of the current image block. Specifically, it can be obtained by calculating the mean value of the chrominance component reconstruction value of all sampling points of the current image block, or by calculating the median value of the chrominance component reconstruction value of all sampling points of the current image block. This embodiment of the present application does not specifically limit this.

[0076] In the embodiment of the present application, first, the mean value Mean can be calculated based on the reconstructed values ​​of the chrominance components of all sampling points of the current image block and formula (3):

[0077]

[0078] Among them, Mean represents the mean of the reconstructed values ​​of the chrominance components of all sampling points of the current image block, ∑Rec C [i, j] represents the sum of the reconstructed values ​​of the chrominance components of all sampling points of the current image block, and M represents the number of samples of the reconstructed values ​​of the chrominance components of all sampling points of the current image block.

[0079] Secondly, the calculated mean value Mean is directly used as a threshold, and two calculation models can be established using the threshold; however, the embodiment of the present application is not limited to establishing only two calculation models. For example, based on the sum of the reconstructed values ​​of the chrominance components of all sampling points of the current image block ∑Rec C[i, j] is averaged to obtain the mean. If two calculation models are established, the Mean can be used directly as a threshold. Based on this threshold, the adjacent reference values ​​of the chrominance component of the current image block can be divided into two parts, indicating that two calculation models can be established subsequently. If three calculation models are established, (minimum reconstruction value of the chrominance component + Mean + 1) >> 1 is used as the first threshold, and (maximum reconstruction value of the chrominance component + Mean + 1) >> 1 is used as the second threshold. Based on these two thresholds, the adjacent reference values ​​of the chrominance component of the current image block can be divided into three parts, indicating that three calculation models can be established subsequently. The following description will use the calculated mean Mean as a threshold to establish two calculation models as an example.

[0080] In some embodiments, if the adjacent reference value of the chrominance component of the current image block is not greater than at least one threshold, obtaining a first group of adjacent reference values ​​C(m) of the chrominance component and a first group of adjacent reference values ​​L(m) of the luminance component;

[0081] If the adjacent reference value of the chrominance component of the current image block is greater than at least one threshold, a second group of adjacent reference values ​​C(k) of the chrominance component and L(k) of the luminance component are obtained.

[0082] It should be noted that, using the mean value Mean calculated above as the threshold, the adjacent reference values ​​of the chrominance component of the current image block can be divided into two parts, namely C(m) and C(k); correspondingly, the adjacent reference values ​​of the luminance component of the current image block can also be divided into two parts, namely L(m) and L(k).

[0083] It can be understood that after obtaining the first group of adjacent reference values ​​C(m) of the chroma components and the adjacent reference values ​​L(m) of the luminance components, and the second group of adjacent reference values ​​C(k) of the chroma components and the adjacent reference values ​​L(k) of the luminance components, the adjacent reference values ​​of each group of chroma components and the adjacent reference values ​​of the luminance components can be used as a separate training set, that is, each group can be trained to obtain a set of model parameters; therefore, in the above implementation, specifically, at least two calculation models are established based on at least two groups of adjacent reference values ​​of the chroma components and the adjacent reference values ​​of the luminance components, including:

[0084] According to L(m), C(m) and formula (7), the first parameter α1 of the first calculation model and the second parameter β1 of the first calculation model are calculated:

[0085]

[0086] According to L(k), C(k) and formula (5), the first parameter α2 of the second calculation model and the second parameter β2 of the second calculation model are calculated:

[0087]

[0088] According to the first parameter α1 of the first calculation model and the second parameter β1 of the first calculation model, the first parameter α2 of the second calculation model and the second parameter β2 of the second calculation model and formula (6), the first calculation model Pred is established. 1L [i,j] and the second calculation model Pred 2L [i,j]:

[0089]

[0090] Wherein, M represents the number of adjacent reference values ​​C(m) of the chroma component or the adjacent reference values ​​L(m) of the luminance component of the first group, K represents the number of adjacent reference values ​​C(k) of the chroma component or the adjacent reference values ​​L(k) of the luminance component of the second group, [i, j] represents the position coordinates of the sampling point in the current image block, i represents the horizontal direction, and j represents the vertical direction; Threshold represents the preset threshold value, which is obtained according to the reconstructed values ​​of the chroma components of all sampling points in the current image block; Rec C [i, j] represents the reconstructed value of the chrominance component of the sampling point with the position coordinates [i, j] in the current image block; Pred 1L [i,j] and Pred 2L [i, j] represents the predicted value of the brightness component of the sampling point with position coordinates [i, j] in the current image block.

[0091] In practical applications, a threshold is first calculated based on the reconstructed value of the first chrominance component, and the adjacent reference values ​​of the first chrominance component and the adjacent reference values ​​of the luminance component are classified according to the threshold. Taking two calculation models as an example, α1 and β1 are obtained according to formula (4), and α2 and β2 are obtained according to formula (5). Then, the reconstructed value of the first chrominance component is substituted into the above formula (6) to obtain the first predicted value.

[0092] To obtain the second predicted value, in an optional embodiment, performing prediction based on the reconstructed value of the second chrominance component, the adjacent reference values ​​of the second chrominance component, and the adjacent reference values ​​of the luminance component to obtain the second predicted value of the luminance component includes:

[0093] Determining parameters of a prediction model according to adjacent reference values ​​of the second chrominance component and adjacent reference values ​​of the luminance component;

[0094] According to the reconstructed value of the second chrominance component, a prediction model is called to obtain a second prediction value.

[0095] Similarly, in the same way as calculating the first prediction value, for the linear model, in actual application, the adjacent reference value of the second chrominance component and the adjacent reference value of the luminance component are substituted into formula (2) to obtain α and β, and then the reconstructed value of the second chrominance component is substituted into formula (1) to obtain the second prediction value; in this way, the second prediction value can be obtained using the linear model.

[0096] For nonlinear models, in practical applications, a threshold is first calculated based on the reconstructed value of the second chrominance component, and the adjacent reference values ​​of the second chrominance component and the adjacent reference values ​​of the luminance component are classified according to the threshold. Taking two calculation models as an example, α1 and β1 are obtained according to formula (4), and α2 and β2 are obtained according to formula (5). Then, the reconstructed value of the second chrominance component is substituted into the above formula (6) to obtain the second predicted value.

[0097] In this way, the first predicted value and the second predicted value can be obtained.

[0098] In order to determine the predicted value of the luminance component, in an optional embodiment, determining the predicted value of the luminance component according to the first predicted value and the second predicted value includes:

[0099] Obtaining a weight value of the first prediction value and a weight value of the second prediction value;

[0100] According to the weight value of the first prediction value and the weight value of the second prediction value, the first prediction value and the second prediction value are weighted and summed to obtain the prediction value of the brightness component.

[0101] After the first predicted value and the second predicted value are determined, the first predicted value and the second predicted value may be fused, and the fused value may be determined as the predicted value of the luminance component.

[0102] Specifically, the weight value of the first prediction value and the weight value of the second prediction value may be obtained first, and then the first prediction value and the second prediction value may be weighted summed in a weighted summation manner to obtain the prediction value of the brightness component.

[0103] There are multiple ways to obtain the weight value of the first prediction value and the weight value of the second prediction value. In an optional embodiment, obtaining the weight value of the first prediction value and the weight value of the second prediction value may include:

[0104] A set of weight values ​​is selected from a preset weight value group, one of the values ​​in the set of weight values ​​is determined as the weight value of the first prediction value, and another value in the set of weight values ​​is determined as the weight value of the second prediction value.

[0105] That is to say, multiple groups of weight values ​​are pre-set in the encoder, such as (0.5, 0.5), (0.2, 0.8), (0.3, 0.7) and (0.1, 0.9), etc., and one group can be selected from the preset weight value group. If (0.5, 0.5) is selected, then the weight value of the first predicted value is 0.5, and the weight value of the second predicted value is 0.5. In this way, the weight value of the first predicted value and the weight value of the second predicted value can be determined.

[0106] Then, at the decoder end, the selected result can be identified from the bitstream with a corresponding syntax element to facilitate the decoder end to predict the predicted value of the luminance component.

[0107] In an optional embodiment, obtaining the weight value of the first prediction value and the weight value of the second prediction value may include:

[0108] receiving a first weight value and a second weight value;

[0109] The first weight value is determined as the weight value of the first prediction value, and the second weight value is determined as the weight value of the second prediction value.

[0110] Here, the weight value of the first prediction value and the weight value of the second prediction value can be determined in advance through user input, so that the encoder end receives the first weight value and the second weight value. Then, the first weight value can be determined as the weight value of the first prediction value, and the second weight value can be determined as the weight value of the second prediction value; at the same time, the selected result is marked with the corresponding syntax element in the code stream to facilitate the decoder end to receive the weight value and predict the predicted value of the luminance component.

[0111] In addition, in actual applications, the resolution of the chrominance component of the current image block is smaller than the resolution of the luminance component. You can choose to upsample the reconstructed value of the first chrominance component and the reconstructed value of the second chrominance component, or you can choose to upsample the first predicted value and the second predicted value. You can also obtain the predicted value of the luminance component and then upsample the predicted value of the luminance component. Here, the embodiments of the present application do not make specific limitations on this.

[0112] In upsampling the reconstructed value of the first chroma component and the reconstructed value of the second chroma component, in an optional embodiment, after obtaining, for the current image block, the reconstructed value of the first chroma component, the reconstructed value of the second chroma component, the adjacent reference value of the first chroma component, the adjacent reference value of the second chroma component, and the adjacent reference value of the luminance component, the method further includes:

[0113] When the resolution of the chroma component is smaller than the resolution of the luminance component, upsampling the reconstructed value of the first chroma component and the reconstructed value of the second chroma component is performed respectively to obtain a reconstructed value of the first chroma component and a reconstructed value of the second chroma component after processing;

[0114] Accordingly, performing prediction based on the reconstructed value of the first chrominance component, the adjacent reference values ​​of the first chrominance component, and the adjacent reference values ​​of the luminance component to obtain a first predicted value of the luminance component includes:

[0115] Predicting based on the reconstructed value of the first chrominance component, the adjacent reference values ​​of the first chrominance component, and the adjacent reference values ​​of the luminance component to obtain a first predicted value of the luminance component;

[0116] Accordingly, performing prediction based on the reconstructed value of the second chrominance component, the adjacent reference values ​​of the second chrominance component, and the adjacent reference values ​​of the luminance component to obtain a second predicted value of the luminance component includes:

[0117] Prediction is performed based on the reconstructed value of the second chrominance component after processing, the adjacent reference values ​​of the second chrominance component and the adjacent reference values ​​of the luminance component to obtain a second predicted value of the luminance component.

[0118] Specifically, since the resolution of the chrominance component of the current image block is smaller than the resolution of the luminance component, in order to improve the prediction accuracy, here, after obtaining the reconstructed value of the first chrominance component and the reconstructed value of the second chrominance component, it is necessary to upsample the reconstructed value of the first chrominance component and the reconstructed value of the second chrominance component respectively, so that the resolution of the processed reconstructed value of the first chrominance component and the resolution of the processed reconstructed value of the second chrominance component are respectively the same as the resolution of the luminance component, so as to improve the prediction accuracy.

[0119] Then, after obtaining the processed reconstructed value of the first chrominance component and the processed reconstructed value of the second chrominance component, a prediction can be made based on the processed reconstructed value of the first chrominance component, the adjacent reference values ​​of the first chrominance component and the adjacent reference values ​​of the luminance component to obtain a first predicted value of the luminance component, and a prediction can be made based on the processed reconstructed value of the second chrominance component, the adjacent reference values ​​of the second chrominance component and the adjacent reference values ​​of the luminance component to obtain a second predicted value of the luminance component, and the predicted value of the luminance component of the current image block can be determined based on the first predicted value and the second predicted value obtained in this way.

[0120] Here, in upsampling the first predicted value and the second predicted value, in an optional embodiment, before determining the predicted value of the luminance component according to the first predicted value and the second predicted value, the method further includes:

[0121] When the resolution of the chrominance component is smaller than the resolution of the luminance component, upsampling the first predicted value and the second predicted value is performed respectively to obtain a processed first predicted value and a processed second predicted value;

[0122] Accordingly, determining a predicted value of the luminance component according to the first predicted value and the second predicted value includes:

[0123] A predicted value of the luminance component is determined based on the processed first predicted value and the processed second predicted value.

[0124] Here, when the resolution of the chrominance component is smaller than that of the luminance component, in order to adapt to the resolution of the luminance component, after obtaining the first prediction value and the second prediction value, the first prediction value and the second prediction value are upsampled respectively to obtain the processed first prediction value and the processed second prediction value. Finally, the prediction value of the luminance component is determined based on the processed first prediction value and the processed second prediction value.

[0125] In up-sampling the predicted value of the luminance component, in an optional embodiment, after determining the predicted value of the luminance component according to the first predicted value and the second predicted value, the method further includes:

[0126] When the resolution of the chrominance component is smaller than the resolution of the luminance component, the predicted value of the luminance component is upsampled to obtain the processed predicted value of the luminance component.

[0127] That is, after obtaining the predicted value of the luminance component, up-sampling is performed on the predicted value of the luminance component so that the resolution of the processed predicted value of the luminance component is the same as the resolution of the luminance component.

[0128] The embodiment of the present application provides a method for predicting image components. Figure 4 A flowchart of an optional image component prediction method provided in an embodiment of the present application is shown as follows: Figure 4 As shown, the method may include:

[0129] S401: In decoding of image components, decoding chrominance components;

[0130] S402: Obtain a predicted value of the luminance component according to the decoded chrominance component.

[0131] It should be noted that S401 and S402 in the embodiment of the present application are mainly used in the following situations: Figure 2 The intra-frame prediction unit 203 shown is partly Figure 3 The intra-frame prediction unit 303 part is shown; that is, the embodiment of the present application can act on the encoder and the decoder at the same time, and the embodiment of the present application does not make any specific limitation on this.

[0132] In addition, in S401 and S402, in the decoding of the image components, one chroma component may be decoded and then the chroma component may be used to predict the luminance component, one chroma component may be decoded and then the chroma component may be used to predict another chroma component, two chroma components may be decoded first and then one chroma component may be used to predict the luminance component, or two chroma components may be used to predict the luminance component. Here, the embodiments of the present application do not make specific limitations on this.

[0133] In order to obtain a predicted value of the luminance component, in an optional embodiment, S102 may include:

[0134] Predicting a first chroma component in the decoded chroma components and a second chroma component in the decoded chroma components to obtain a predicted value of a luminance component;

[0135] When the first chromaticity component is a blue chromaticity component, the second chromaticity component is a red chromaticity component; when the first chromaticity component is a red chromaticity component, the second chromaticity component is a blue chromaticity component.

[0136] Here, the first chroma component and the decoded second chroma component in the decoded chroma component are used to predict the predicted value of the luminance component. For example, the first chroma component is Cb, the second chroma component is Cr, and the luminance component is Y, then Y can be predicted by Cb and Cr, or the first chroma component is Cr, the second chroma component is Cb, and the luminance component is Y, then Y can be predicted by Cb and Cr.

[0137] Furthermore, in order to predict a predicted value of the luminance component, in an optional embodiment, performing prediction based on a first chrominance component in the decoded chrominance components and a second chrominance component in the decoded chrominance components to obtain a predicted value of the luminance component includes:

[0138] For the current image block, obtain a reconstructed value of the first chroma component, a reconstructed value of the second chroma component, an adjacent reference value of the first chroma component, an adjacent reference value of the second chroma component, and an adjacent reference value of the luminance component;

[0139] Predicting according to the reconstructed value of the first chrominance component, the adjacent reference values ​​of the first chrominance component, and the adjacent reference values ​​of the luminance component to obtain a first predicted value of the luminance component;

[0140] Performing prediction based on the reconstructed value of the second chrominance component, the adjacent reference values ​​of the second chrominance component, and the adjacent reference values ​​of the luminance component to obtain a second predicted value of the luminance component;

[0141] A predicted value of the luminance component is determined based on the first predicted value and the second predicted value.

[0142] Among them, the current image block is the current image block to be decoded. Here, for the current image block, it is necessary to obtain the reconstruction value of the first chrominance component of the current image block and the reconstruction value of the second chrominance component of the current image block. The first chrominance component of the adjacent image block of the current image block is the adjacent reference value of the above-mentioned first chrominance component, the second chrominance component of the adjacent image block of the current image block is the adjacent reference value of the above-mentioned second chrominance component, and the luminance component of the adjacent image block of the current image block is the adjacent reference value of the luminance component. It should be noted that the adjacent image blocks of the above-mentioned current image block are the image blocks in the upper row and the image blocks in the left column of the current image block.

[0143] Then, after obtaining the above values, a first prediction value can be predicted based on the reconstructed value of the first chrominance component, the adjacent reference value of the first chrominance component and the adjacent reference value of the luminance component. A second prediction value can be predicted based on the reconstructed value of the second chrominance component, the adjacent reference value of the second chrominance component and the adjacent reference value of the luminance component. Then, the prediction value of the luminance component of the current image block is obtained based on the first prediction value and the second prediction value. In this way, a prediction value is predicted by each chrominance component, and finally the two predicted prediction values ​​are fused to obtain the prediction value of the luminance component of the current image block.

[0144] To obtain the first predicted value, in an optional embodiment, performing prediction based on the reconstructed value of the first chrominance component, the adjacent reference values ​​of the first chrominance component, and the adjacent reference values ​​of the luminance component to obtain the first predicted value of the luminance component includes:

[0145] Determining parameters of a prediction model according to adjacent reference values ​​of the first chrominance component and adjacent reference values ​​of the luminance component;

[0146] According to the reconstructed value of the first chrominance component, a prediction model is called to obtain a first prediction value.

[0147] After obtaining the reconstructed value of the first chrominance component and the adjacent reference value of the first chrominance component, the prediction model of the image component adopted above can be a linear model or a nonlinear model to predict the luminance component to obtain the first prediction value. Here, the embodiment of the present application does not make specific limitations.

[0148] In practical applications, the adjacent reference values ​​of the first chrominance component and the adjacent reference values ​​of the luminance component are substituted into formula (2) to obtain α and β, and then the reconstructed value of the first chrominance component is substituted into formula (1) to obtain the first predicted value; in this way, the first predicted value can be obtained using the linear model.

[0149] In addition to the above-mentioned linear model, the prediction model may also adopt a nonlinear model. On the basis of the above-mentioned linear model, the prediction model of the image component also proposes a nonlinear model calculation method.

[0150] In practical applications, a threshold is first calculated based on the reconstructed value of the first chrominance component, and the adjacent reference values ​​of the first chrominance component and the adjacent reference values ​​of the luminance component are classified according to the threshold. Taking two calculation models as an example, α1 and β1 are obtained according to formula (4), and α2 and β2 are obtained according to formula (5). Then, the reconstructed value of the first chrominance component is substituted into the above formula (6) to obtain the first predicted value.

[0151] To obtain the second predicted value, in an optional embodiment, performing prediction based on the reconstructed value of the second chrominance component, the adjacent reference values ​​of the second chrominance component, and the adjacent reference values ​​of the luminance component to obtain the second predicted value of the luminance component includes:

[0152] Determining parameters of a prediction model according to adjacent reference values ​​of the second chrominance component and adjacent reference values ​​of the luminance component;

[0153] According to the reconstructed value of the second chrominance component, a prediction model is called to obtain a second prediction value.

[0154] Similarly, in the same way as calculating the first prediction value, for the linear model, in actual application, the adjacent reference value of the second chrominance component and the adjacent reference value of the luminance component are substituted into formula (2) to obtain α and β, and then the reconstructed value of the second chrominance component is substituted into formula (1) to obtain the second prediction value; in this way, the second prediction value can be obtained using the linear model.

[0155] For nonlinear models, in practical applications, a threshold is first calculated based on the reconstructed value of the second chrominance component, and the adjacent reference values ​​of the second chrominance component and the adjacent reference values ​​of the luminance component are classified according to the threshold. Taking two calculation models as an example, α1 and β1 are obtained according to formula (4), and α2 and β2 are obtained according to formula (5). Then, the reconstructed value of the second chrominance component is substituted into the above formula (6) to obtain the second predicted value.

[0156] In this way, the first predicted value and the second predicted value can be obtained.

[0157] In order to determine the predicted value of the luminance component, in an optional embodiment, determining the predicted value of the luminance component according to the first predicted value and the second predicted value includes:

[0158] Obtaining a weight value of the first prediction value and a weight value of the second prediction value;

[0159] According to the weight value of the first prediction value and the weight value of the second prediction value, the first prediction value and the second prediction value are weighted and summed to obtain the prediction value of the brightness component.

[0160] After the first predicted value and the second predicted value are determined, the first predicted value and the second predicted value may be fused, and the fused value may be determined as the predicted value of the luminance component.

[0161] Specifically, the weight value of the first prediction value and the weight value of the second prediction value may be obtained first, and then the first prediction value and the second prediction value may be weighted summed in a weighted summation manner to obtain the prediction value of the brightness component.

[0162] There are multiple ways to obtain the weight value of the first prediction value and the weight value of the second prediction value. In an optional embodiment, obtaining the weight value of the first prediction value and the weight value of the second prediction value may include:

[0163] A set of weight values ​​is selected from a preset weight value group, one of the values ​​in the set of weight values ​​is determined as the weight value of the first prediction value, and another value in the set of weight values ​​is determined as the weight value of the second prediction value.

[0164] That is to say, multiple groups of weight values ​​are pre-set in the decoder, such as (0.5, 0.5), (0.2, 0.8), (0.3, 0.7) and (0.1, 0.9), etc., and one group can be selected from the preset weight value group. If (0.5, 0.5) is selected, then the weight value of the first prediction value is 0.5, and the weight value of the second prediction value is 0.5. In this way, the weight value of the first prediction value and the weight value of the second prediction value can be determined.

[0165] Then, at the decoder end, the selected result can be identified from the bitstream with a corresponding syntax element to facilitate the decoder end to predict the predicted value of the luminance component.

[0166] In an optional embodiment, obtaining the weight value of the first prediction value and the weight value of the second prediction value may include:

[0167] receiving a first weight value and a second weight value;

[0168] The first weight value is determined as the weight value of the first prediction value, and the second weight value is determined as the weight value of the second prediction value.

[0169] Here, the weight value of the first prediction value and the weight value of the second prediction value can be determined in advance through user input, so that the encoder end receives the first weight value and the second weight value. Then, the first weight value can be determined as the weight value of the first prediction value, and the second weight value can be determined as the weight value of the second prediction value; at the same time, the selected result is marked with the corresponding syntax element in the code stream to facilitate the decoder end to receive the weight value and predict the predicted value of the brightness component.

[0170] In addition, in actual applications, the resolution of the chrominance component of the current image block is smaller than the resolution of the luminance component. You can choose to upsample the reconstructed value of the first chrominance component and the reconstructed value of the second chrominance component, or you can choose to upsample the first predicted value and the second predicted value. You can also obtain the predicted value of the luminance component and then upsample the predicted value of the luminance component. Here, the embodiments of the present application do not make specific limitations on this.

[0171] In upsampling the reconstructed value of the first chroma component and the reconstructed value of the second chroma component, in an optional embodiment, after obtaining, for the current image block, the reconstructed value of the first chroma component, the reconstructed value of the second chroma component, the adjacent reference value of the first chroma component, the adjacent reference value of the second chroma component, and the adjacent reference value of the luminance component, the method further includes:

[0172] When the resolution of the chroma component is smaller than the resolution of the luminance component, upsampling the reconstructed value of the first chroma component and the reconstructed value of the second chroma component is performed respectively to obtain a reconstructed value of the first chroma component and a reconstructed value of the second chroma component after processing;

[0173] Accordingly, performing prediction based on the reconstructed value of the first chrominance component, the adjacent reference values ​​of the first chrominance component, and the adjacent reference values ​​of the luminance component to obtain a first predicted value of the luminance component includes:

[0174] Predicting based on the reconstructed value of the first chrominance component, the adjacent reference values ​​of the first chrominance component, and the adjacent reference values ​​of the luminance component to obtain a first predicted value of the luminance component;

[0175] Accordingly, performing prediction based on the reconstructed value of the second chrominance component, the adjacent reference values ​​of the second chrominance component, and the adjacent reference values ​​of the luminance component to obtain a second predicted value of the luminance component includes:

[0176] Prediction is performed based on the reconstructed value of the second chrominance component after processing, the adjacent reference values ​​of the second chrominance component and the adjacent reference values ​​of the luminance component to obtain a second predicted value of the luminance component.

[0177] Specifically, since the resolution of the chrominance component of the current image block is smaller than the resolution of the luminance component, in order to improve the prediction accuracy, here, after obtaining the reconstructed value of the first chrominance component and the reconstructed value of the second chrominance component, it is necessary to upsample the reconstructed value of the first chrominance component and the reconstructed value of the second chrominance component respectively, so that the resolution of the processed reconstructed value of the first chrominance component and the resolution of the processed reconstructed value of the second chrominance component are respectively the same as the resolution of the luminance component, so as to improve the prediction accuracy.

[0178] Then, after obtaining the processed reconstructed value of the first chrominance component and the processed reconstructed value of the second chrominance component, a prediction can be made based on the processed reconstructed value of the first chrominance component, the adjacent reference values ​​of the first chrominance component and the adjacent reference values ​​of the luminance component to obtain a first predicted value of the luminance component, and a prediction can be made based on the processed reconstructed value of the second chrominance component, the adjacent reference values ​​of the second chrominance component and the adjacent reference values ​​of the luminance component to obtain a second predicted value of the luminance component, and the predicted value of the luminance component of the current image block can be determined based on the first predicted value and the second predicted value obtained in this way.

[0179] Here, in upsampling the first predicted value and the second predicted value, in an optional embodiment, before determining the predicted value of the luminance component according to the first predicted value and the second predicted value, the method further includes:

[0180] When the resolution of the chrominance component is smaller than the resolution of the luminance component, upsampling the first predicted value and the second predicted value is performed respectively to obtain a processed first predicted value and a processed second predicted value;

[0181] Accordingly, determining a predicted value of the luminance component according to the first predicted value and the second predicted value includes:

[0182] A predicted value of the luminance component is determined based on the processed first predicted value and the processed second predicted value.

[0183] Here, when the resolution of the chrominance component is smaller than that of the luminance component, in order to adapt to the resolution of the luminance component, after obtaining the first prediction value and the second prediction value, the first prediction value and the second prediction value are upsampled respectively to obtain the processed first prediction value and the processed second prediction value. Finally, the prediction value of the luminance component is determined based on the processed first prediction value and the processed second prediction value.

[0184] In up-sampling the predicted value of the luminance component, in an optional embodiment, after determining the predicted value of the luminance component according to the first predicted value and the second predicted value, the method further includes:

[0185] When the resolution of the chrominance component is smaller than the resolution of the luminance component, the predicted value of the luminance component is upsampled to obtain the processed predicted value of the luminance component.

[0186] That is, after obtaining the predicted value of the luminance component, up-sampling is performed on the predicted value of the luminance component so that the resolution of the processed predicted value of the luminance component is the same as the resolution of the luminance component.

[0187] An embodiment of the present application provides a method for predicting image components, the method comprising: encoding the chrominance component in the encoding of the image component, and obtaining a predicted value of the luminance component based on the encoded chrominance component; that is, in an embodiment of the present application, the chrominance component is first encoded and decoded, and then the luminance component is predicted based on the encoded and decoded chrominance component. In this way, the luminance component is predicted based on the chrominance component obtained by encoding and decoding, that is, the relatively flat chrominance component is first encoded and decoded, and then the luminance component with rich texture is predicted based on the chrominance component obtained by encoding and decoding. This can improve the accuracy of the luminance component prediction, so that the predicted value of the luminance component is closer to the actual pixel value of the luminance component.

[0188] Example 2

[0189] Based on the same invention concept, Figure 5 This is a schematic diagram of the structure of an optional encoder proposed in an embodiment of the present application, such as Figure 5 As shown, the encoder proposed in the embodiment of the present application may include an encoding module 51 and a first acquisition module 52; wherein,

[0190] The encoding module 51 is configured to encode the chrominance component in the encoding of the image component;

[0191] The first acquisition module 52 is configured to acquire a predicted value of the luminance component according to the encoded chrominance component.

[0192] Furthermore, the first acquisition module 52 is specifically configured as follows:

[0193] Predicting a luminance component based on a first chroma component in the encoded chroma components and a second chroma component in the encoded chroma components to obtain a predicted value of the luminance component;

[0194] When the first chromaticity component is a blue chromaticity component, the second chromaticity component is a red chromaticity component; when the first chromaticity component is a red chromaticity component, the second chromaticity component is a blue chromaticity component.

[0195] Furthermore, the first acquisition module 52 performs prediction based on the first chroma component in the encoded chroma component and the second chroma component in the encoded chroma component to obtain a predicted value of the luminance component, including:

[0196] For the current image block, obtain a reconstructed value of the first chroma component, a reconstructed value of the second chroma component, an adjacent reference value of the first chroma component, an adjacent reference value of the second chroma component, and an adjacent reference value of the luminance component;

[0197] Predicting according to the reconstructed value of the first chrominance component, the adjacent reference values ​​of the first chrominance component, and the adjacent reference values ​​of the luminance component to obtain a first predicted value of the luminance component;

[0198] Performing prediction based on the reconstructed value of the second chrominance component, the adjacent reference values ​​of the second chrominance component, and the adjacent reference values ​​of the luminance component to obtain a second predicted value of the luminance component;

[0199] A predicted value of the luminance component is determined based on the first predicted value and the second predicted value.

[0200] Furthermore, the first acquisition module 52 performs prediction based on the reconstructed value of the first chrominance component, the adjacent reference value of the first chrominance component, and the adjacent reference value of the luminance component to obtain a first predicted value of the luminance component, including:

[0201] Determining parameters of a prediction model according to adjacent reference values ​​of the first chrominance component and adjacent reference values ​​of the luminance component;

[0202] According to the reconstructed value of the first chrominance component, a prediction model is called to obtain a first prediction value.

[0203] Furthermore, the first acquisition module 52 performs prediction based on the reconstructed value of the second chrominance component, the adjacent reference value of the second chrominance component, and the adjacent reference value of the luminance component to obtain a second predicted value of the luminance component, including:

[0204] Determining parameters of a prediction model according to adjacent reference values ​​of the second chrominance component and adjacent reference values ​​of the luminance component;

[0205] According to the reconstructed value of the second chrominance component, a prediction model is called to obtain a second prediction value.

[0206] Furthermore, the first acquisition module 52 determines the predicted value of the brightness component according to the first predicted value and the second predicted value, including:

[0207] Obtaining a weight value of the first prediction value and a weight value of the second prediction value;

[0208] According to the weight value of the first prediction value and the weight value of the second prediction value, the first prediction value and the second prediction value are weighted and summed to obtain the prediction value of the brightness component.

[0209] Furthermore, the first acquisition module 52 acquires the weight value of the first prediction value and the weight value of the second prediction value, including:

[0210] A set of weight values ​​is selected from a preset weight value group, one of the values ​​in the set of weight values ​​is determined as the weight value of the first prediction value, and another value in the set of weight values ​​is determined as the weight value of the second prediction value.

[0211] Furthermore, the first acquisition module 52 is specifically configured as follows:

[0212] After obtaining, for the current image block, a reconstructed value of the first chroma component, a reconstructed value of the second chroma component, adjacent reference values ​​of the first chroma component, adjacent reference values ​​of the second chroma component, and adjacent reference values ​​of the luminance component, when a resolution of the chroma component is smaller than a resolution of the luminance component, upsampling the reconstructed value of the first chroma component and the reconstructed value of the second chroma component respectively to obtain a reconstructed value of the first chroma component after processing and a reconstructed value of the second chroma component after processing;

[0213] Accordingly, the first acquisition module 52 performs prediction based on the reconstructed value of the first chrominance component, the adjacent reference value of the first chrominance component, and the adjacent reference value of the luminance component to obtain a first predicted value of the luminance component, including:

[0214] Predicting based on the reconstructed value of the first chrominance component, the adjacent reference values ​​of the first chrominance component, and the adjacent reference values ​​of the luminance component to obtain a first predicted value of the luminance component;

[0215] Accordingly, the first acquisition module 52 performs prediction based on the reconstructed value of the second chrominance component, the adjacent reference value of the second chrominance component, and the adjacent reference value of the luminance component to obtain a second predicted value of the luminance component, including:

[0216] Prediction is performed based on the reconstructed value of the second chrominance component after processing, the adjacent reference values ​​of the second chrominance component and the adjacent reference values ​​of the luminance component to obtain a second predicted value of the luminance component.

[0217] In an optional embodiment, the first acquisition module 52 is further configured to:

[0218] Before determining the predicted value of the luminance component based on the first predicted value and the second predicted value, when the resolution of the chrominance component is smaller than the resolution of the luminance component, upsampling the first predicted value and the second predicted value respectively to obtain a processed first predicted value and a processed second predicted value;

[0219] Accordingly, the first acquisition module 52 determines the predicted value of the luminance component according to the first predicted value and the second predicted value, including:

[0220] A predicted value of the luminance component is determined based on the processed first predicted value and the processed second predicted value.

[0221] In an optional embodiment, the first acquisition module 52 is further configured to:

[0222] After determining the predicted value of the luminance component according to the first predicted value and the second predicted value, when the resolution of the chrominance component is smaller than the resolution of the luminance component, the predicted value of the luminance component is upsampled to obtain the processed predicted value of the luminance component.

[0223] Based on the same invention concept, Figure 6 This is a schematic diagram of the structure of an optional decoder proposed in an embodiment of the present application, such as Figure 6 As shown, the decoder proposed in the embodiment of the present application may include a decoding module 61 and a second acquisition module 62; wherein,

[0224] A decoding module 61 is configured to decode the chrominance component during decoding of the image component;

[0225] The second acquisition module 62 is configured to acquire a predicted value of the luminance component according to the decoded chrominance component.

[0226] Furthermore, the second acquisition module 62 is specifically configured as follows:

[0227] Predicting a first chroma component in the decoded chroma components and a second chroma component in the decoded chroma components to obtain a predicted value of a luminance component;

[0228] When the first chromaticity component is a blue chromaticity component, the second chromaticity component is a red chromaticity component; when the first chromaticity component is a red chromaticity component, the second chromaticity component is a blue chromaticity component.

[0229] Furthermore, the second acquisition module 62 performs prediction based on the first chroma component in the decoded chroma component and the second chroma component in the decoded chroma component to obtain a predicted value of the luminance component, including:

[0230] For the current image block, obtain a reconstructed value of the first chroma component, a reconstructed value of the second chroma component, an adjacent reference value of the first chroma component, an adjacent reference value of the second chroma component, and an adjacent reference value of the luminance component;

[0231] Predicting according to the reconstructed value of the first chrominance component, the adjacent reference values ​​of the first chrominance component, and the adjacent reference values ​​of the luminance component to obtain a first predicted value of the luminance component;

[0232] Performing prediction based on the reconstructed value of the second chrominance component, the adjacent reference values ​​of the second chrominance component, and the adjacent reference values ​​of the luminance component to obtain a second predicted value of the luminance component;

[0233] A predicted value of the luminance component is determined according to the first predicted value and the second predicted value.

[0234] Furthermore, the second acquisition module 62 performs prediction based on the reconstructed value of the first chrominance component, the adjacent reference value of the first chrominance component, and the adjacent reference value of the luminance component to obtain a first predicted value of the luminance component, including:

[0235] Determining parameters of a prediction model according to adjacent reference values ​​of the first chrominance component and adjacent reference values ​​of the luminance component;

[0236] According to the reconstructed value of the first chrominance component, a prediction model is called to obtain a first prediction value.

[0237] Furthermore, the second acquisition module 62 performs prediction based on the reconstructed value of the second chrominance component, the adjacent reference value of the second chrominance component, and the adjacent reference value of the luminance component to obtain a second predicted value of the luminance component, including:

[0238] Determining parameters of a prediction model according to adjacent reference values ​​of the second chrominance component and adjacent reference values ​​of the luminance component;

[0239] According to the reconstructed value of the second chrominance component, a prediction model is called to obtain a second prediction value.

[0240] Furthermore, the second acquisition module 62 determines the predicted value of the brightness component according to the first predicted value and the second predicted value, including:

[0241] Obtaining a weight value of the first prediction value and a weight value of the second prediction value;

[0242] According to the weight value of the first prediction value and the weight value of the second prediction value, the first prediction value and the second prediction value are weighted and summed to obtain the prediction value of the brightness component.

[0243] Furthermore, the second acquisition module 62 acquires the weight value of the first prediction value and the weight value of the second prediction value, including:

[0244] A set of weight values ​​is selected from a preset weight value group, one of the values ​​in the set of weight values ​​is determined as the weight value of the first prediction value, and another value in the set of weight values ​​is determined as the weight value of the second prediction value.

[0245] Furthermore, the second acquisition module 62 is specifically configured as follows:

[0246] After obtaining, for the current image block, a reconstructed value of the first chroma component, a reconstructed value of the second chroma component, adjacent reference values ​​of the first chroma component, adjacent reference values ​​of the second chroma component, and adjacent reference values ​​of the luminance component, when a resolution of the chroma component is smaller than a resolution of the luminance component, upsampling the reconstructed value of the first chroma component and the reconstructed value of the second chroma component respectively to obtain a reconstructed value of the first chroma component after processing and a reconstructed value of the second chroma component after processing;

[0247] Accordingly, the second acquisition module 62 performs prediction based on the reconstructed value of the first chrominance component, the adjacent reference value of the first chrominance component, and the adjacent reference value of the luminance component to obtain a first predicted value of the luminance component, including:

[0248] Predicting based on the reconstructed value of the first chrominance component, the adjacent reference values ​​of the first chrominance component, and the adjacent reference values ​​of the luminance component to obtain a first predicted value of the luminance component;

[0249] Accordingly, the second acquisition module 62 performs prediction based on the reconstructed value of the second chrominance component, the adjacent reference value of the second chrominance component, and the adjacent reference value of the luminance component to obtain a second predicted value of the luminance component, including:

[0250] Prediction is performed based on the reconstructed value of the second chrominance component after processing, the adjacent reference values ​​of the second chrominance component and the adjacent reference values ​​of the luminance component to obtain a second predicted value of the luminance component.

[0251] In an optional embodiment, the second acquisition module 62 is further configured to:

[0252] Before determining the predicted value of the luminance component based on the first predicted value and the second predicted value, when the resolution of the chrominance component is smaller than the resolution of the luminance component, upsampling the first predicted value and the second predicted value respectively to obtain a processed first predicted value and a processed second predicted value;

[0253] Accordingly, the second acquisition module 62 determines the predicted value of the luminance component according to the first predicted value and the second predicted value, including:

[0254] A predicted value of the luminance component is determined based on the processed first predicted value and the processed second predicted value.

[0255] In an optional embodiment, the second acquisition module 62 is further configured to:

[0256] After determining the predicted value of the luminance component according to the first predicted value and the second predicted value, when the resolution of the chrominance component is smaller than the resolution of the luminance component, the predicted value of the luminance component is upsampled to obtain the processed predicted value of the luminance component.

[0257] Figure 7 This is a schematic diagram of the structure of another optional encoder proposed in the embodiment of the present application, such as Figure 7 As shown, the encoder 700 proposed in the embodiment of the present application may also include a processor 71 and a storage medium 72 storing instructions executable by the processor 71. The storage medium 72 relies on the processor 71 to perform operations through a communication bus 73. When the instructions are executed by the processor 71, the prediction method of the image component described in one or more of the above embodiments is executed.

[0258] It should be noted that in actual application, the various components in the terminal are coupled together through the communication bus 73. It is understood that the communication bus 73 is used to realize the connection and communication between these components. In addition to the data bus, the communication bus 73 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, Figure 7 Various buses are labeled as communication buses 73.

[0259] Figure 8 This is a schematic diagram of the structure of another optional decoder proposed in the embodiment of the present application, such as Figure 8 As shown, the encoder 800 proposed in the embodiment of the present application may also include a processor 81 and a storage medium 82 storing instructions executable by the processor 81. The storage medium 82 relies on the processor 81 to perform operations through a communication bus 83. When the instructions are executed by the processor 81, the prediction method of the image component described in one or more of the above embodiments is executed.

[0260] It should be noted that in actual application, the various components in the terminal are coupled together through the communication bus 83. It is understood that the communication bus 83 is used to realize the connection and communication between these components. In addition to the data bus, the communication bus 83 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Figure 8 Various buses are labeled as communication buses 83.

[0261] An embodiment of the present application provides a computer storage medium storing executable instructions. When the executable instructions are executed by one or more processors, the processors execute the image component prediction method described in one or more of the above embodiments.

[0262] It is understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM bus random access memory (DRRAM). The memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0263] The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits in the processor or by software instructions. The above processor may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The various methods, steps, and logic block diagrams disclosed in the embodiments of this application can be implemented or executed. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium mature in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.

[0264] It is understood that the embodiments described herein may be implemented using hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit may be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described herein, or a combination thereof.

[0265] For software implementation, the techniques described herein can be implemented by modules (e.g., procedures, functions, etc.) that perform the functions described herein. The software code can be stored in a memory and executed by a processor. The memory can be implemented in the processor or external to the processor.

[0266] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0267] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0268] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), including a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0269] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are protected by this application.

[0270] Industrial Applicability

[0271] An embodiment of the present application provides a method for predicting image components, an encoder, and a computer storage medium, including: in the encoding of image components, encoding the chrominance components, and obtaining a predicted value of the luminance component based on the encoded chrominance components, which can improve the accuracy of the luminance component prediction and make the predicted value of the luminance component closer to the actual pixel value of the luminance component.

Claims

1. A method for predicting image components, characterized in that: Applied to a decoder, the method comprises: Get the predicted value of the brightness component; Upsampling the predicted value of the luminance component to obtain a processed predicted value of the luminance component, wherein a resolution of the processed predicted value of the luminance component is the same as a resolution of the luminance component; decoding a first chrominance component; A second chroma component is determined based on the decoded first chroma component.

2. The method according to claim 1, characterized in that The first chrominance component is a blue chrominance component, and the second chrominance component is a red chrominance component.

3. The method according to claim 1, characterized in that The prediction model is a nonlinear model.

4. The method according to any one of claims 1 to 3, characterized in that The method further comprises: Parameters of a prediction model are determined, and a prediction value of the luminance component is determined based on the prediction model.

5. A method for predicting image components, characterized in that: Applied to an encoder, the method comprises: Get the predicted value of the brightness component; Upsampling the predicted value of the luminance component to obtain a processed predicted value of the luminance component, wherein a resolution of the processed predicted value of the luminance component is the same as a resolution of the luminance component; encoding a first chrominance component; A second chroma component is determined based on the encoded first chroma component.

6. The method according to claim 5, characterized in that The first chrominance component is a blue chrominance component, and the second chrominance component is a red chrominance component.

7. The method according to claim 5, characterized in that The prediction model is a nonlinear model.

8. The method according to any one of claims 5 to 7, characterized in that: The method further comprises: Parameters of a prediction model are determined, and a prediction value of the luminance component is determined based on the prediction model.

9. A decoder, characterized in that The decoder comprises: an acquisition module configured to obtain a predicted value of a brightness component; an upsampling module configured to perform an upsampling process on the predicted value of the luminance component to obtain a processed predicted value of the luminance component, wherein the resolution of the processed predicted value of the luminance component is the same as the resolution of the luminance component; a decoding module configured to decode the first chrominance component; The determining module is configured to determine a second chroma component according to the decoded first chroma component.

10. The decoder according to claim 9, characterized in that The first chrominance component is a blue chrominance component, and the second chrominance component is a red chrominance component.

11. The decoder according to claim 9, characterized in that The prediction model is a nonlinear model.

12. The decoder according to any one of claims 9 to 11, characterized in that: The acquisition module is further configured to: Parameters of a prediction model are determined, and a prediction value of the luminance component is determined based on the prediction model.

13. An encoder, characterized in that The encoder comprises: an acquisition module configured to obtain a predicted value of a brightness component; an upsampling module configured to perform an upsampling process on the predicted value of the luminance component to obtain a processed predicted value of the luminance component, wherein the resolution of the processed predicted value of the luminance component is the same as the resolution of the luminance component; an encoding module configured to encode the first chrominance component; The determining module is configured to determine a second chroma component according to the encoded first chroma component.

14. The encoder according to claim 13, wherein The first chrominance component is a blue chrominance component, and the second chrominance component is a red chrominance component.

15. The encoder according to claim 13, wherein The prediction model is a nonlinear model.

16. The encoder according to any one of claims 13 to 15, characterized in that: The acquisition module is further configured to: Parameters of a prediction model are determined, and a prediction value of the luminance component is determined based on the prediction model.

17. A computer-readable storage medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the computer program implements the image component prediction method according to any one of claims 1 to 4.

18. A computer-readable storage medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the computer program implements the image component prediction method according to any one of claims 5 to 8.

19. A computer-readable storage medium having a code stream stored thereon, wherein: The code stream is generated by executing the steps of the image component prediction method according to any one of claims 5 to 8.

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