Method, apparatus, and medium for video processing
The cross-component prior module in the YUV color space addresses the inefficiencies in existing video compression technologies by modeling correlations between luma and chroma components, improving coding efficiency and quality in video processing.
Patent Information
- Application Number
- PCT/CN2025/108945
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2024-07-17
- Filing Date
- 2025-07-16
- Publication Date
- 2026-01-22
AI Technical Summary
Existing video compression technologies, such as MPEG-2, AVC, HEVC, and VVC, have limitations in coding efficiency and quality, particularly due to the strong inter-channel relationship between RGB components in the RGB color space.
An end-to-end learned image compression framework utilizing a cross-component prior module to model correlations between luma and chroma components in the YUV color space, guiding the coding process to enhance coding efficiency and quality.
Improves coding efficiency and quality by leveraging textural and structural guidance from luma to chroma components, reducing redundancy and enhancing compression performance.
Smart Images

Figure CN2025108945_22012026_PF_FP_ABST
Abstract
Description
METHOD, APPARATUS, AND MEDIUM FOR VIDEO PROCESSINGFIELDS
[0001] Embodiments of the present disclosure relates generally to video processing techniques, and more particularly, to a compression framework based on cross-component prior.BACKGROUND
[0002] In nowadays, digital video capabilities are being applied in various aspects of peoples’ lives. Multiple types of video compression technologies, such as motion picture expert group (MPEG) -2, MPEG-4, international telecommunication union -telecommunication standardization sector (ITU-T) H. 263, ITU-T H. 264 / MPEG-4 Part 10 advanced video coding (AVC) , ITU-T H. 265 high efficiency video coding (HEVC) standard, versatile video coding (VVC) standard, have been proposed for video encoding / decoding. However, coding efficiency of video coding techniques is generally expected to be further improved.SUMMARY
[0003] Embodiments of the present disclosure provide a solution for video processing.
[0004] In a first aspect, a method for video processing is proposed. The method comprises: determining, for a conversion between a video unit of a video and a bitstream of the video, a set of parameters based on a training framework using a train dataset, wherein the training framework comprises a cross-component prior module between a luma component and a chroma component that is applied before an encoder and a decoder; determining a compression framework based on the set of parameters; and performing the conversion based on the compression framework. The method in accordance with the first aspect of the present disclosure can advantageously improve coding efficiency and coding quality.
[0005] In a second aspect, an apparatus for video processing is proposed. The apparatus comprises a processor and a non-transitory memory with instructions thereon. The instructions upon execution by the processor, cause the processor to perform a method in accordance with the first aspect of the present disclosure.
[0006] In a third aspect, a non-transitory computer-readable storage medium is proposed. The non-transitory computer-readable storage medium stores instructions that cause a processor to perform a method in accordance with the first aspect of the present disclosure.
[0007] In a fourth aspect, another non-transitory computer-readable recording medium is proposed. The non-transitory computer-readable recording medium stores a bitstream of a video which is generated by a method performed by an apparatus for video processing. The method comprises: determining a set of parameters based on a training framework using a train dataset, wherein the training framework comprises a cross-component prior module between a luma component and a chroma component that is applied before an encoder and a decoder; determining a compression framework based on the set of parameters; and generating the bitstream based on the compression framework.
[0008] In a fifth aspect, a method for storing a bitstream of a video is proposed. The method comprises: determining a set of parameters based on a training framework using a train dataset, wherein the training framework comprises a cross-component prior module between a luma component and a chroma component that is applied before an encoder and a decoder; determining a compression framework based on the set of parameters; performing the conversion based on the compression framework; and storing the bitstream in a non-transitory computer-readable recording medium.
[0009] This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.BRIEF DESCRIPTION OF THE DRAWINGS
[0010] Through the following detailed description with reference to the accompanying drawings, the above and other objectives, features, and advantages of example embodiments of the present disclosure will become more apparent. In the example embodiments of the present disclosure, the same reference numerals usually refer to the same components.
[0011] Fig. 1 illustrates a block diagram of an example video coding system in accordance with some embodiments of the present disclosure;
[0012] Fig. 2 illustrates a block diagram of an example video encoder in accordance with some embodiments of the present disclosure;
[0013] Fig. 3 illustrates a block diagram of an example video decoder in accordance with some embodiments of the present disclosure;
[0014] Fig. 4 illustrates an architecture of a proposed image compression framework;
[0015] Fig. 5 illustrates a flowchart of a method for video processing in accordance with some embodiments of the present disclosure;
[0016] Fig. 6 illustrates a block diagram of a computing device in which various embodiments of the present disclosure can be implemented.
[0017] Throughout the drawings, the same or similar reference numerals usually refer to the same or similar elements.DETAILED DESCRIPTION
[0018] Principle of the present disclosure will now be described with reference to some embodiments. It is to be understood that these embodiments are described only for the purpose of illustration and help those skilled in the art to understand and implement the present disclosure, without suggesting any limitation as to the scope of the disclosure. The disclosure described herein can be implemented in various manners other than the ones described below.
[0019] In the following description and claims, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skills in the art to which this disclosure belongs.
[0020] References in the present disclosure to “one embodiment, ” “an embodiment, ” “an example embodiment, ” and the like indicate that the embodiment described may include a particular feature, structure, or characteristic, but it is not necessary that every embodiment includes the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an example embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.
[0021] It shall be understood that although the terms “first” and “second” etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and similarly, a second element could be termed a first element, without departing from the scope of example embodiments. As used herein, the term “and / or” includes any and all combinations of one or more of the listed terms.
[0022] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a” , “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” , “comprising” , “has” , “having” , “includes” and / or “including” , when used herein, specify the presence of stated features, elements, and / or components etc., but do not preclude the presence or addition of one or more other features, elements, components and / or combinations thereof. Example Environment
[0023] Fig. 1 is a block diagram that illustrates an example video coding system 100 that may utilize the techniques of this disclosure. As shown, the video coding system 100 may include a source device 110 and a destination device 120. The source device 110 can be also referred to as a video encoding device, and the destination device 120 can be also referred to as a video decoding device. In operation, the source device 110 can be configured to generate encoded video data and the destination device 120 can be configured to decode the encoded video data generated by the source device 110. The source device 110 may include a video source 112, a video encoder 114, and an input / output (I / O) interface 116.
[0024] The video source 112 may include a source such as a video capture device. Examples of the video capture device include, but are not limited to, an interface to receive video data from a video content provider, a computer graphics system for generating video data, and / or a combination thereof.
[0025] The video data may comprise one or more pictures. The video encoder 114 encodes the video data from the video source 112 to generate a bitstream. The bitstream may include a sequence of bits that form a coded representation of the video data. The bitstream may include coded pictures and associated data. The coded picture is a coded representation of a picture. The associated data may include sequence parameter sets, picture parameter sets, and other syntax structures. The I / O interface 116 may include a modulator / demodulator and / or a transmitter. The encoded video data may be transmitted directly to destination device 120 via the I / O interface 116 through the network 130A. The encoded video data may also be stored onto a storage medium / server 130B for access by destination device 120.
[0026] The destination device 120 may include an I / O interface 126, a video decoder 124, and a display device 122. The I / O interface 126 may include a receiver and / or a modem. The I / O interface 126 may acquire encoded video data from the source device 110 or the storage medium / server 130B. The video decoder 124 may decode the encoded video data. The display device 122 may display the decoded video data to a user. The display device 122 may be integrated with the destination device 120, or may be external to the destination device 120 which is configured to interface with an external display device.
[0027] The video encoder 114 and the video decoder 124 may operate according to a video compression standard, such as the High Efficiency Video Coding (HEVC) standard, Versatile Video Coding (VVC) standard and other current and / or further standards.
[0028] Fig. 2 is a block diagram illustrating an example of a video encoder 200, which may be an example of the video encoder 114 in the system 100 illustrated in Fig. 1, in accordance with some embodiments of the present disclosure.
[0029] The video encoder 200 may be configured to implement any or all of the techniques of this disclosure. In the example of Fig. 2, the video encoder 200 includes a plurality of functional components. The techniques described in this disclosure may be shared among the various components of the video encoder 200. In some examples, a processor may be configured to perform any or all of the techniques described in this disclosure.
[0030] In some embodiments, the video encoder 200 may include a partition unit 201, a prediction unit 202 which may include a mode select unit 203, a motion estimation unit 204, a motion compensation unit 205 and an intra-prediction unit 206, a residual generation unit 207, a transform unit 208, a quantization unit 209, an inverse quantization unit 210, an inverse transform unit 211, a reconstruction unit 212, a buffer 213, and an entropy encoding unit 214.
[0031] In other examples, the video encoder 200 may include more, fewer, or different functional components. In an example, the prediction unit 202 may include an intra block copy (IBC) unit. The IBC unit may perform prediction in an IBC mode in which at least one reference picture is a picture where the current video block is located.
[0032] Furthermore, although some components, such as the motion estimation unit 204 and the motion compensation unit 205, may be integrated, but are represented in the example of Fig. 2 separately for purposes of explanation.
[0033] The partition unit 201 may partition a picture into one or more video blocks. The video encoder 200 and the video decoder 300 may support various video block sizes.
[0034] The mode select unit 203 may select one of the coding modes, intra or inter, e.g., based on error results, and provide the resulting intra-coded or inter-coded block to a residual generation unit 207 to generate residual block data and to a reconstruction unit 212 to reconstruct the encoded block for use as a reference picture. In some examples, the mode select unit 203 may select a combined inter and intra prediction (CIIP) mode in which the prediction is based on an inter prediction signal and an intra prediction signal. The mode select unit 203 may also select a resolution for a motion vector (e.g., a sub-pixel or integer pixel precision) for the block in the case of inter-prediction.
[0035] To perform inter prediction on a current video block, the motion estimation unit 204 may generate motion information for the current video block by comparing one or more reference frames from buffer 213 to the current video block. The motion compensation unit 205 may determine a predicted video block for the current video block based on the motion information and decoded samples of pictures from the buffer 213 other than the picture associated with the current video block.
[0036] The motion estimation unit 204 and the motion compensation unit 205 may perform different operations for a current video block, for example, depending on whether the current video block is in an I-slice, a P-slice, or a B-slice. As used herein, an “I-slice” may refer to a portion of a picture composed of macroblocks, all of which are based upon macroblocks within the same picture. Further, as used herein, in some aspects, “P-slices” and “B-slices” may refer to portions of a picture composed of macroblocks that are not dependent on macroblocks in the same picture.
[0037] In some examples, the motion estimation unit 204 may perform uni-directional prediction for the current video block, and the motion estimation unit 204 may search reference pictures of list 0 or list 1 for a reference video block for the current video block. The motion estimation unit 204 may then generate a reference index that indicates the reference picture in list 0 or list 1 that contains the reference video block and a motion vector that indicates a spatial displacement between the current video block and the reference video block. The motion estimation unit 204 may output the reference index, a prediction direction indicator, and the motion vector as the motion information of the current video block. The motion compensation unit 205 may generate the predicted video block of the current video block based on the reference video block indicated by the motion information of the current video block.
[0038] Alternatively, in other examples, the motion estimation unit 204 may perform bi-directional prediction for the current video block. The motion estimation unit 204 may search the reference pictures in list 0 for a reference video block for the current video block and may also search the reference pictures in list 1 for another reference video block for the current video block. The motion estimation unit 204 may then generate reference indexes that indicate the reference pictures in list 0 and list 1 containing the reference video blocks and motion vectors that indicate spatial displacements between the reference video blocks and the current video block. The motion estimation unit 204 may output the reference indexes and the motion vectors of the current video block as the motion information of the current video block. The motion compensation unit 205 may generate the predicted video block of the current video block based on the reference video blocks indicated by the motion information of the current video block.
[0039] In some examples, the motion estimation unit 204 may output a full set of motion information for decoding processing of a decoder. Alternatively, in some embodiments, the motion estimation unit 204 may signal the motion information of the current video block with reference to the motion information of another video block. For example, the motion estimation unit 204 may determine that the motion information of the current video block is sufficiently similar to the motion information of a neighboring video block.
[0040] In one example, the motion estimation unit 204 may indicate, in a syntax structure associated with the current video block, a value that indicates to the video decoder 300 that the current video block has the same motion information as the another video block.
[0041] In another example, the motion estimation unit 204 may identify, in a syntax structure associated with the current video block, another video block and a motion vector difference (MVD) . The motion vector difference indicates a difference between the motion vector of the current video block and the motion vector of the indicated video block. The video decoder 300 may use the motion vector of the indicated video block and the motion vector difference to determine the motion vector of the current video block.
[0042] As discussed above, video encoder 200 may predictively signal the motion vector. Two examples of predictive signaling techniques that may be implemented by video encoder 200 include advanced motion vector prediction (AMVP) and merge mode signaling.
[0043] The intra prediction unit 206 may perform intra prediction on the current video block. When the intra prediction unit 206 performs intra prediction on the current video block, the intra prediction unit 206 may generate prediction data for the current video block based on decoded samples of other video blocks in the same picture. The prediction data for the current video block may include a predicted video block and various syntax elements.
[0044] The residual generation unit 207 may generate residual data for the current video block by subtracting (e.g., indicated by the minus sign) the predicted video block (s) of the current video block from the current video block. The residual data of the current video block may include residual video blocks that correspond to different sample components of the samples in the current video block.
[0045] In other examples, there may be no residual data for the current video block, for example in a skip mode, and the residual generation unit 207 may not perform the subtracting operation.
[0046] The transform unit 208 may generate one or more transform coefficient video blocks for the current video block by applying one or more transforms to a residual video block associated with the current video block.
[0047] After the transform unit 208 generates a transform coefficient video block associated with the current video block, the quantization unit 209 may quantize the transform coefficient video block associated with the current video block based on one or more quantization parameter (QP) values associated with the current video block.
[0048] The inverse quantization unit 210 and the inverse transform unit 211 may apply inverse quantization and inverse transforms to the transform coefficient video block, respectively, to reconstruct a residual video block from the transform coefficient video block. The reconstruction unit 212 may add the reconstructed residual video block to corresponding samples from one or more predicted video blocks generated by the prediction unit 202 to produce a reconstructed video block associated with the current video block for storage in the buffer 213.
[0049] After the reconstruction unit 212 reconstructs the video block, loop filtering operation may be performed to reduce video blocking artifacts in the video block.
[0050] The entropy encoding unit 214 may receive data from other functional components of the video encoder 200. When the entropy encoding unit 214 receives the data, the entropy encoding unit 214 may perform one or more entropy encoding operations to generate entropy encoded data and output a bitstream that includes the entropy encoded data.
[0051] Fig. 3 is a block diagram illustrating an example of a video decoder 300, which may be an example of the video decoder 124 in the system 100 illustrated in Fig. 1, in accordance with some embodiments of the present disclosure.
[0052] The video decoder 300 may be configured to perform any or all of the techniques of this disclosure. In the example of Fig. 3, the video decoder 300 includes a plurality of functional components. The techniques described in this disclosure may be shared among the various components of the video decoder 300. In some examples, a processor may be configured to perform any or all of the techniques described in this disclosure.
[0053] In the example of Fig. 3, the video decoder 300 includes an entropy decoding unit 301, a motion compensation unit 302, an intra prediction unit 303, an inverse quantization unit 304, an inverse transform unit 305, a reconstruction unit 306 and a buffer 307. The video decoder 300 may, in some examples, perform a decoding pass generally reciprocal to the encoding pass described with respect to video encoder 200.
[0054] The entropy decoding unit 301 may retrieve an encoded bitstream. The encoded bitstream may include entropy coded video data (e.g., encoded blocks of video data) . The entropy decoding unit 301 may decode the entropy coded video data, and from the entropy decoded video data, the motion compensation unit 302 may determine motion information including motion vectors, motion vector precision, reference picture list indexes, and other motion information. The motion compensation unit 302 may, for example, determine such information by performing the AMVP and merge mode. AMVP is used, including derivation of several most probable candidates based on data from adjacent PBs and the reference picture. Motion information typically includes the horizontal and vertical motion vector displacement values, one or two reference picture indices, and, in the case of prediction regions in B slices, an identification of which reference picture list is associated with each index. As used herein, in some aspects, a “merge mode” may refer to deriving the motion information from spatially or temporally neighboring blocks.
[0055] The motion compensation unit 302 may produce motion compensated blocks, possibly performing interpolation based on interpolation filters. Identifiers for interpolation filters to be used with sub-pixel precision may be included in the syntax elements.
[0056] The motion compensation unit 302 may use the interpolation filters as used by the video encoder 200 during encoding of the video block to calculate interpolated values for sub-integer pixels of a reference block. The motion compensation unit 302 may determine the interpolation filters used by the video encoder 200 according to the received syntax information and use the interpolation filters to produce predictive blocks.
[0057] The motion compensation unit 302 may use at least part of the syntax information to determine sizes of blocks used to encode frame (s) and / or slice (s) of the encoded video sequence, partition information that describes how each macroblock of a picture of the encoded video sequence is partitioned, modes indicating how each partition is encoded, one or more reference frames (and reference frame lists) for each inter-encoded block, and other information to decode the encoded video sequence. As used herein, in some aspects, a “slice” may refer to a data structure that can be decoded independently from other slices of the same picture, in terms of entropy coding, signal prediction, and residual signal reconstruction. A slice can either be an entire picture or a region of a picture.
[0058] The intra prediction unit 303 may use intra prediction modes for example received in the bitstream to form a prediction block from spatially adjacent blocks. The inverse quantization unit 304 inverse quantizes, i.e., de-quantizes, the quantized video block coefficients provided in the bitstream and decoded by entropy decoding unit 301. The inverse transform unit 305 applies an inverse transform.
[0059] The reconstruction unit 306 may obtain the decoded blocks, e.g., by summing the residual blocks with the corresponding prediction blocks generated by the motion compensation unit 302 or intra-prediction unit 303. If desired, a deblocking filter may also be applied to filter the decoded blocks in order to remove blockiness artifacts. The decoded video blocks are then stored in the buffer 307, which provides reference blocks for subsequent motion compensation / intra prediction and also produces decoded video for presentation on a display device.
[0060] Some example embodiments of the present disclosure will be described in detailed hereinafter. It should be understood that section headings are used in the present document to facilitate ease of understanding and do not limit the embodiments disclosed in a section to only that section. Furthermore, while certain embodiments are described with reference to Versatile Video Coding or other specific video codecs, the disclosed techniques are applicable to other video coding technologies also. Furthermore, while some embodiments describe video coding steps in detail, it will be understood that corresponding steps decoding that undo the coding will be implemented by a decoder. Furthermore, the term video processing encompasses video coding or compression, video decoding or decompression and video transcoding in which video pixels are represented from one compressed format into another compressed format or at a different compressed bitrate. 1. Brief summary
[0061] This disclosure is related to video coding technologies. Specifically, it is an end-to-end learned image compression framework, integrating cross-component technologies into the compression framework. We design the cross-component prior gate (CPG) to model cross-component information between luma and chroma components based on local and global levels. The approach guides the coding process of chroma components to improve coding efficiency. 2. Introduction
[0062] Image compression has played an important role in signal processing, enabling efficient image transmission and storage. Traditional image compression standards JPEG, High Efficiency Video Coding (HEVC) , and Versatile Video Coding (VVC) typically designed handcrafted modules to remove the redundancy and improve the coding efficiency, which consists of transform matrix, entropy model, and quantization modules. Motivated by the progress of deep neural networks on computer vision tasks, end-to-end image compression methods have been proposed to achieve more efficient image coding.
[0063] In recent years, significant advancements have been made in image compression methods. Optimization of analysis / synthesis transform networks and entropy models has improved compression performance. The first end-to-end image compression framework was proposed in 2016, transforming images from the pixel domain into compact representations. Moreover, integration of hyperprior and autoregressive models has enabled more precise entropy estimation. Moreover, the attention mechanism has been widely applied to the analysis / synthesis transform networks to generate more compact representation. The non-local attention modules can achieve efficient extraction of non-local and local information. Transformer-based architectures to incorporate the local modeling ability of CNN and the non-local modeling ability of transformers to improve the overall architecture of image compression models. 3. Problems
[0064] Related image compression methods mainly focus on optimizing and compressing images within the RGB color space. However, the strong inter-channel relationship between RGB components degrades the coding efficiency. The transformation from RGB to YUV color space can reduce the correlation between the channels. Therefore, the approach decomposes the image compression problem on RGB color space into two parts: converting RGB to YUV, and image compression on YUV color space. The luma component contains more structural and textural information compared to chroma components. In video coding, the cross-component prediction has been widely adopted, such as the Cross Component Linear Model (CCLM) , the Cross-Component Prediction (CCP) supported in the HEVC range extensions and the Cross-Component Adaptive Loop Filtering (CC-ALF) adopted in VVC. Therefore, the approach can improve the performance based on cross-component prior. 4. Detailed solutions
[0065] The detailed embodiments below should be considered as examples to explain general concepts. These embodiments should not be interpreted in a narrow way. Furthermore, these embodiments can be combined in any manner.
[0066] It is proposed to develop an image compression framework using cross-component priors. To achieve efficient image compression in YUV space, an attention mechanism is employed to model the cross-component prior between luma and chroma components to guide the coding process. The approach leverages textural and structural guidance from luma to chroma components to improve coding efficiency based on cross-component prior. 1. In one example, Fig. 4 shows the architecture of the proposed image compression framework based on the cross-component prior. a. In one example, encoded images undergo transformation from RGB to YUV444 color space using BT. 601 for enhanced coding efficiency. b. In one example, chroma components and luma component are split for input into the cross- component prior module. Cross-component prior module model correlations between Y and UV components, guiding UV coding process based on spatial priors from Y. c. In one example, the Y and UV component are fused and then fed into the encoder and de- coder part to generate bitstream and decoded images. d. In testing phase, the images of test datasets are fed into the compression framework to achieve coding and decoding process.
[0067] Fig. 5 illustrates a flowchart of a method 500 for video processing in accordance with embodiments of the present disclosure. The method 500 is implemented during a conversion between a video unit of a video and a bitstream of the video.
[0068] At block 510, for a conversion between a video unit of a video and a bitstream of the video, a set of parameters is determined based on a training framework using a train dataset. In this case, the training framework includes a cross-component prior module between a luma component and a chroma component that is applied before an encoder and a decoder.
[0069] At block 520, a compression framework is determined based on the set of parameters.
[0070] At block 530, the conversion is performed based on the compression framework. In some embodiments, the conversion may include encoding the video unit into the bitstream. Alternatively, the conversion may include decoding the video unit from the bitstream. The method 500 enables coding efficiency and coding quality to be advantageously improved.
[0071] As an example, as shown in Fig. 4, a train dataset 410 may be input into a training framework 420. A cross-component prior module 422 may be included in the training framework 420, and the cross-component prior module 422 may be applied before an encoder 424 and an decoder 426. In addition, a set of parameters may be determined based on the training framework 420 and the set of parameters may be used to determine a compression framework 430.
[0072] In some embodiments, an encoded image may be transformed from RGB color space to YUV color space. As an example, the YUV color space may include 4: 4: 4. For example, the transformation from RGB to YUV444 color space may be performed by using BT. 601. As another example, BT. 709 may be used. Alternatively, BT. 2020 may be used. In this way, the coding efficiency can be enhanced. It should be noted that the approach used in the transformation is only an example, which is not intended to limit the scope of the present disclosure.
[0073] In some embodiments, a set of chroma components and luma components included in the train dataset may be input into the cross-component prior module. In some embodiments, the set of chroma components and the luma components may be split before being input into the cross-component prior module. In some embodiments, a correlation between the luma component and the chroma component may be determined with the cross-component prior module. In some embodiments, a coding process of a chroma component of the video unit may be performed based on a spatial prior of a luma component of the video unit according to the correlation between the luma component and the chroma component. As an example, the cross-component prior module 422 may model correlations between Y and UV components, to guide UV coding process based on spatial priors from Y.
[0074] In some embodiments, a luma component and a chroma component of the video unit may be fused. In some embodiments, the fusion of the luma component and the chroma component may be fed into the encoder. In this case, the bitstream may be generated at the encoder. In some other embodiments, the fusion of the luma component and the chroma component may be fed into the decoder. In this case, a decoded image may be generated at the decoder.
[0075] In some embodiments, a set of images included in a test dataset may be fed into the compression framework. For example, as shown in Fig. 4, the images of a test dataset 440 may be fed into the compression framework 430. In some embodiments, a conversion associated with the test dataset may be performed based on the set of images included in the test dataset. For example, the images of the test dataset 440 may be fed into the compression framework 430 to achieve coding and decoding process.
[0076] According to further embodiments of the present disclosure, a non-transitory computer-readable recording medium is provided. The non-transitory computer-readable recording medium stores a bitstream of a video which is generated by a method performed by an apparatus for video processing. The method comprises: determining a set of parameters based on a training framework using a train dataset, wherein the training framework comprises a cross-component prior module between a luma component and a chroma component that is applied before an encoder and a decoder; determining a compression framework based on the set of parameters; and generating the bitstream based on the compression framework.
[0077] According to still further embodiments of the present disclosure, a method for storing bitstream of a video is provided. The method comprises: determining a set of parameters based on a training framework using a train dataset, wherein the training framework comprises a cross-component prior module between a luma component and a chroma component that is applied before an encoder and a decoder; determining a compression framework based on the set of parameters; performing the conversion based on the compression framework; and storing the bitstream in a non-transitory computer-readable recording medium.
[0078] Implementations of the present disclosure can be described in view of the following clauses, the features of which can be combined in any reasonable manner.
[0079] Clause 1. A method for video processing, comprising: determining, for a conversion between a video unit of a video and a bitstream of the video, a set of parameters based on a training framework using a train dataset, wherein the training framework comprises a cross-component prior module between a luma component and a chroma component that is applied before an encoder and a decoder; determining a compression framework based on the set of parameters; and performing the conversion based on the compression framework.
[0080] Clause 2. The method of clause 1, wherein an encoded image is transformed from RGB color space to YUV color space.
[0081] Clause 3. The method of clause 2, wherein the YUV color space comprises 4: 4: 4.
[0082] Clause 4. The method of clause 1, wherein a set of chroma components and luma components comprised in the train dataset are input into the cross-component prior module.
[0083] Clause 5. The method of clause 4, wherein the set of chroma components and the luma components are split before being input into the cross-component prior module.
[0084] Clause 6. The method of clause 4, wherein a correlation between the luma component and the chroma component is determined with the cross-component prior module.
[0085] Clause 7. The method of clause 6, wherein a coding process of a chroma component of the video unit is performed based on a spatial prior of a luma component of the video unit according to the correlation between the luma component and the chroma component.
[0086] Clause 8. The method of clause 1, wherein a luma component and a chroma component of the video unit are fused.
[0087] Clause 9. The method of clause 8, wherein the fusion of the luma component and the chroma component is fed into the encoder, wherein the bitstream is generated at the encoder.
[0088] Clause 10. The method of clause 8, wherein the fusion of the luma component and the chroma component is fed into the decoder, wherein a decoded image is generated at the decoder.
[0089] Clause 11. The method of clause 1, wherein a set of images comprised in a test dataset are fed into the compression framework.
[0090] Clause 12. The method of clause 1, wherein a conversion associated with the test dataset is performed based on the set of images comprised in the test dataset.
[0091] Clause 13. The method of any of clauses 1 to 12, wherein the conversion includes encoding the video unit into the bitstream.
[0092] Clause 14. The method of any of clauses 1 to 12, wherein the conversion includes decoding the video unit from the bitstream.
[0093] Clause 15. An apparatus for video processing comprising a processor and a non-transitory memory with instructions thereon, wherein the instructions upon execution by the processor, cause the processor to perform a method in accordance with any of clauses 1-14.
[0094] Clause 16. A non-transitory computer-readable storage medium storing instructions that cause a processor to perform a method in accordance with any of clauses 1-14.
[0095] Clause 17. A non-transitory computer-readable recording medium storing a bitstream of a video which is generated by a method performed by an apparatus for video processing, wherein the method comprises: determining a set of parameters based on a training framework using a train dataset, wherein the training framework comprises a cross-component prior module between a luma component and a chroma component that is applied before an encoder and a decoder; determining a compression framework based on the set of parameters; and generating the bitstream based on the compression framework.
[0096] Clause 18. A method for storing a bitstream of a video, comprising: determining a set of parameters based on a training framework using a train dataset, wherein the training framework comprises a cross-component prior module between a luma component and a chroma component that is applied before an encoder and a decoder; determining a compression framework based on the set of parameters; performing the conversion based on the compression framework; and storing the bitstream in a non-transitory computer-readable recording medium. Example Device
[0097] Fig. 6 illustrates a block diagram of a computing device 600 in which various embodiments of the present disclosure can be implemented. The computing device 600 may be implemented as or included in the source device 110 (or the video encoder 114 or 200) or the destination device 120 (or the video decoder 124 or 300) .
[0098] It would be appreciated that the computing device 600 shown in Fig. 6 is merely for purpose of illustration, without suggesting any limitation to the functions and scopes of the embodiments of the present disclosure in any manner.
[0099] As shown in Fig. 6, the computing device 600 includes a general-purpose computing device 600. The computing device 600 may at least comprise one or more processors or processing units 610, a memory 620, a storage unit 630, one or more communication units 640, one or more input devices 650, and one or more output devices 660.
[0100] In some embodiments, the computing device 600 may be implemented as any user terminal or server terminal having the computing capability. The server terminal may be a server, a large-scale computing device or the like that is provided by a service provider. The user terminal may for example be any type of mobile terminal, fixed terminal, or portable terminal, including a mobile phone, station, unit, device, multimedia computer, multimedia tablet, Internet node, communicator, desktop computer, laptop computer, notebook computer, netbook computer, tablet computer, personal communication system (PCS) device, personal navigation device, personal digital assistant (PDA) , audio / video player, digital camera / video camera, positioning device, television receiver, radio broadcast receiver, E-book device, gaming device, or any combination thereof, including the accessories and peripherals of these devices, or any combination thereof. It would be contemplated that the computing device 600 can support any type of interface to a user (such as “wearable” circuitry and the like) .
[0101] The processing unit 610 may be a physical or virtual processor and can implement various processes based on programs stored in the memory 620. In a multi-processor system, multiple processing units execute computer executable instructions in parallel so as to improve the parallel processing capability of the computing device 600. The processing unit 610 may also be referred to as a central processing unit (CPU) , a microprocessor, a controller or a microcontroller.
[0102] The computing device 600 typically includes various computer storage medium. Such medium can be any medium accessible by the computing device 600, including, but not limited to, volatile and non-volatile medium, or detachable and non-detachable medium. The memory 620 can be a volatile memory (for example, a register, cache, Random Access Memory (RAM) ) , a non-volatile memory (such as a Read-Only Memory (ROM) , Electrically Erasable Programmable Read-Only Memory (EEPROM) , or a flash memory) , or any combination thereof. The storage unit 630 may be any detachable or non-detachable medium and may include a machine-readable medium such as a memory, flash memory drive, magnetic disk or another other media, which can be used for storing information and / or data and can be accessed in the computing device 600.
[0103] The computing device 600 may further include additional detachable / non-detachable, volatile / non-volatile memory medium. Although not shown in Fig. 6, it is possible to provide a magnetic disk drive for reading from and / or writing into a detachable and non-volatile magnetic disk and an optical disk drive for reading from and / or writing into a detachable non-volatile optical disk. In such cases, each drive may be connected to a bus (not shown) via one or more data medium interfaces.
[0104] The communication unit 640 communicates with a further computing device via the communication medium. In addition, the functions of the components in the computing device 600 can be implemented by a single computing cluster or multiple computing machines that can communicate via communication connections. Therefore, the computing device 600 can operate in a networked environment using a logical connection with one or more other servers, networked personal computers (PCs) or further general network nodes.
[0105] The input device 650 may be one or more of a variety of input devices, such as a mouse, keyboard, tracking ball, voice-input device, and the like. The output device 660 may be one or more of a variety of output devices, such as a display, loudspeaker, printer, and the like. By means of the communication unit 640, the computing device 600 can further communicate with one or more external devices (not shown) such as the storage devices and display device, with one or more devices enabling the user to interact with the computing device 600, or any devices (such as a network card, a modem and the like) enabling the computing device 600 to communicate with one or more other computing devices, if required. Such communication can be performed via input / output (I / O) interfaces (not shown) .
[0106] In some embodiments, instead of being integrated in a single device, some or all components of the computing device 600 may also be arranged in cloud computing architecture. In the cloud computing architecture, the components may be provided remotely and work together to implement the functionalities described in the present disclosure. In some embodiments, cloud computing provides computing, software, data access and storage service, which will not require end users to be aware of the physical locations or configurations of the systems or hardware providing these services. In various embodiments, the cloud computing provides the services via a wide area network (such as Internet) using suitable protocols. For example, a cloud computing provider provides applications over the wide area network, which can be accessed through a web browser or any other computing components. The software or components of the cloud computing architecture and corresponding data may be stored on a server at a remote position. The computing resources in the cloud computing environment may be merged or distributed at locations in a remote data center. Cloud computing infrastructures may provide the services through a shared data center, though they behave as a single access point for the users. Therefore, the cloud computing architectures may be used to provide the components and functionalities described herein from a service provider at a remote location. Alternatively, they may be provided from a conventional server or installed directly or otherwise on a client device.
[0107] The computing device 600 may be used to implement video encoding / decoding in embodiments of the present disclosure. The memory 620 may include one or more video coding modules 625 having one or more program instructions. These modules are accessible and executable by the processing unit 610 to perform the functionalities of the various embodiments described herein.
[0108] In the example embodiments of performing video encoding, the input device 650 may receive video data as an input 670 to be encoded. The video data may be processed, for example, by the video coding module 625, to generate an encoded bitstream. The encoded bitstream may be provided via the output device 660 as an output 680.
[0109] In the example embodiments of performing video decoding, the input device 650 may receive an encoded bitstream as the input 670. The encoded bitstream may be processed, for example, by the video coding module 625, to generate decoded video data. The decoded video data may be provided via the output device 660 as the output 680.
[0110] While this disclosure has been particularly shown and described with references to example embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present application as defined by the appended claims. Such variations are intended to be covered by the scope of this present application. As such, the foregoing description of embodiments of the present application is not intended to be limiting.
Claims
1.A method for video processing, comprising:determining, for a conversion between a video unit of a video and a bitstream of the video, a set of parameters based on a training framework using a train dataset, wherein the training framework comprises a cross-component prior module between a luma component and a chroma component that is applied before an encoder and a decoder;determining a compression framework based on the set of parameters; andperforming the conversion based on the compression framework.2.The method of claim 1, wherein an encoded image is transformed from RGB color space to YUV color space.3.The method of claim 2, wherein the YUV color space comprises 4: 4: 4.4.The method of claim 1, wherein a set of chroma components and luma components comprised in the train dataset are input into the cross-component prior module.5.The method of claim 4, wherein the set of chroma components and the luma components are split before being input into the cross-component prior module.6.The method of claim 4, wherein a correlation between the luma component and the chroma component is determined with the cross-component prior module.7.The method of claim 6, wherein a coding process of a chroma component of the video unit is performed based on a spatial prior of a luma component of the video unit according to the correlation between the luma component and the chroma component.8.The method of claim 1, wherein a luma component and a chroma component of the video unit are fused.9.The method of claim 8, wherein the fusion of the luma component and the chroma component is fed into the encoder, wherein the bitstream is generated at the encoder.10.The method of claim 8, wherein the fusion of the luma component and the chroma component is fed into the decoder, wherein a decoded image is generated at the decoder.11.The method of claim 1, wherein a set of images comprised in a test dataset are fed into the compression framework.12.The method of claim 1, wherein a conversion associated with the test dataset is performed based on the set of images comprised in the test dataset.13.The method of any of claims 1 to 12, wherein the conversion includes encoding the video unit into the bitstream.14.The method of any of claims 1 to 12, wherein the conversion includes decoding the video unit from the bitstream.15.An apparatus for video processing comprising a processor and a non-transitory memory with instructions thereon, wherein the instructions upon execution by the processor, cause the processor to perform a method in accordance with any of claims 1-14.16.A non-transitory computer-readable storage medium storing instructions that cause a processor to perform a method in accordance with any of claims 1-14.17.A non-transitory computer-readable recording medium storing a bitstream of a video which is generated by a method performed by an apparatus for video processing, wherein the method comprises:determining a set of parameters based on a training framework using a train dataset, wherein the training framework comprises a cross-component prior module between a luma component and a chroma component that is applied before an encoder and a decoder;determining a compression framework based on the set of parameters; andgenerating the bitstream based on the compression framework.18.A method for storing a bitstream of a video, comprising:determining a set of parameters based on a training framework using a train dataset, wherein the training framework comprises a cross-component prior module between a luma component and a chroma component that is applied before an encoder and a decoder;determining a compression framework based on the set of parameters;performing the conversion based on the compression framework; andstoring the bitstream in a non-transitory computer-readable recording medium.
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