Method, apparatus, and medium for video processing
By adjusting the strength factor for video units based on coding information, the method improves video coding efficiency and quality by reducing reliance on inaccurate pre-analysis, ensuring optimal bit allocation and refined quantization parameter determination.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2025-09-04
- Publication Date
- 2026-03-12
AI Technical Summary
Existing video coding technologies face challenges in achieving optimal coding efficiency and quality due to reliance on potentially inaccurate pre-analysis in determining quantization parameters, leading to suboptimal bit allocation.
A method is proposed that adjusts the strength factor for video units based on a scaling factor derived from coding information, incorporating factors like frame similarity, temporal layer, and base QP to refine quantization parameter (QP) determination, reducing dependency on pre-analysis and improving bit allocation reliability.
This approach enhances coding quality and efficiency by aligning quantization parameter adjustments with actual encoding results, leading to more accurate bit allocation and improved video quality.
Smart Images

Figure CN2025119129_12032026_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 video coding.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 and coding quality 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 current video unit within a current frame of a video and a bitstream of the video, a scaling factor based on coding information of the current frame; adjusting a strength factor for the current video unit based on the scaling factor; determining a quantization parameter (QP) for the current video unit based on the adjusted strength factor and information propagation associated with the current video unit; and performing the conversion based on the QP.
[0005] Based on the method in accordance with the first aspect of the present disclosure, a scaling factor is determined based on coding information of the current frame and used to adjust a strength factor for determining the QP for the current video unit. Compared with the conventional solution where the strength factor is used to determine the QP without adjustment, the proposed solution can advantageously reduce dependency on potentially inaccurate pre-analysis and improve the reliability of bit allocation for the current video unit, thereby improving coding quality and coding efficiency.
[0006] 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.
[0007] 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.
[0008] 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, for a conversion between a current video unit within a current frame of a video and a bitstream of the video, a scaling factor based on coding information of the current frame; adjusting a strength factor for the current video unit based on the scaling factor; determining a quantization parameter (QP) for the current video unit based on the adjusted strength factor and information propagation associated with the current video unit; and generating the bitstream based on the QP.
[0009] In a fifth aspect, a method for storing a bitstream of a video is proposed. The method comprises: determining, for a conversion between a current video unit within a current frame of a video and a bitstream of the video, a scaling factor based on coding information of the current frame; adjusting a strength factor for the current video unit based on the scaling factor; determining a quantization parameter (QP) for the current video unit based on the adjusted strength factor and information propagation associated with the current video unit; generating the bitstream based on the QP; and storing the bitstream in a non-transitory computer-readable recording medium.
[0010] 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
[0011] 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.
[0012] Fig. 1 illustrates a block diagram of an example video coding system in accordance with some embodiments of the present disclosure;
[0013] Fig. 2 illustrates a block diagram of an example video encoder in accordance with some embodiments of the present disclosure;
[0014] Fig. 3 illustrates a block diagram of an example video decoder in accordance with some embodiments of the present disclosure;
[0015] Fig. 4 illustrates a modeling process in accordance with some embodiments of the present disclosure;
[0016] Fig. 5 illustrates an example layered coding structure;
[0017] Fig. 6 illustrates a flowchart of a method for video processing in accordance with some embodiments of the present disclosure; and
[0018] Fig. 7 illustrates a block diagram of a computing device in which various embodiments of the present disclosure can be implemented.
[0019] Throughout the drawings, the same or similar reference numerals usually refer to the same or similar elements.DETAILED DESCRIPTION
[0020] 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.
[0021] 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.
[0022] 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.
[0023] 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.
[0024] 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
[0025] 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.
[0026] 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.
[0027] 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.
[0028] 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.
[0029] 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.
[0030] 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.
[0031] 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.
[0032] 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.
[0033] 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.
[0034] 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.
[0035] 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.
[0036] 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.
[0037] 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.
[0038] 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.
[0039] 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.
[0040] 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.
[0041] 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.
[0042] 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.
[0043] 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.
[0044] 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.
[0045] 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.
[0046] 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.
[0047] 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.
[0048] 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.
[0049] 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.
[0050] 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.
[0051] After the reconstruction unit 212 reconstructs the video block, loop filtering operation may be performed to reduce video blocking artifacts in the video block.
[0052] 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.
[0053] 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.
[0054] 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.
[0055] 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.
[0056] 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.
[0057] 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.
[0058] 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.
[0059] 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.
[0060] 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.
[0061] 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.
[0062] 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 In recent years, with the rapid development of multimedia technology and the increasing popularity of video streaming services, the demand for high-quality video encoding has become crucial. Video encoding is the process of converting raw video data into a compressed format suitable for transmission and storage. However, due to the limited bandwidth and storage capacity, it is essential to ensure efficient compression without compromising the quality of reconstructed videos. To address such challenge, researchers and engineers have developed numerous video coding standards such as H. 264, H. 265, and AV1. Those standards employ various compression techniques, including spatial and temporal redundancy removal, quantization, and entropy coding. While these standards have significantly improved video compression efficiency, the quality of the compressed video can still be affected by several factors, including the complexity of the video content, transmission errors, and bandwidth limitations. To overcome these limitations, the development of algorithms for coding compression through mutual information between coding units has become an active area of research. By constructing a mutual information model for information propagate between coding units, the compression model can efficiently make decisions and assign residual quantization steps, resulting in a more satisfactory bitrate-distortion balance. A typical coding unit mutual information optimisation algorithm is the MB-Tree method which has been proposed and implemented in H. 264. The MB-Tree algorithm enables adaptive shifting of the quantization parameters by discriminating the efficiency of information propagate between the encoding frame and its reference frames. 2. Introduction In general MB-Tree and its derived CU-Tree algorithms adjust the quantization parameters (QP) of the coded frames with a specific strength, where strength is the mapping factor between the information propagate efficiency and the QPs. This patent proposes a method of adaptive mutual information strength, which provides different mutual information mapping strengths for the coding unit to improve the efficiency of the algorithm through the similarity and coding accuracy of inter-frame signals. To better understand the proposed method, the following section introduces the role of the CU-tree and CU strength factor in x265. In x265, the CU-tree algorithm uses a concept known as CU strength to determine the importance of each Coding Unit (CU) in the context of future frames and how much bitrate should be allocated to it. CU strength plays a crucial role in how the CU-tree algorithm adjusts the quantization parameters (QP) for each CU during encoding, directly impacting video quality and compression efficiency. CU strength is a measure of how influential a particular Coding Unit (CU) is expected to be in predicting other CUs in subsequent frames. The stronger a CU is (i.e., the higher its CU strength) , the more bits it will be allocated because it will serve as an important reference for future frames. Conversely, a CU with lower strength is less important and may be allocated fewer bits. Key Factors Influencing CU Strength: 1. Motion Vectors: CUs that have significant motion vectors, especially those used as references in multiple future frames, tend to have higher CU strength. These CUs are critical for accurate motion prediction in later frames. 2. Prediction Residuals: The residual error after prediction (the difference between the predictor and actual CU content) influences CU strength. A lower residual error indicates a more accurate pre-diction, often leading to higher CU strength for that CU. 3. Scene Complexity: CUs in complex or high-detail areas of a scene might be assigned higher CU strength, as these areas require more bits to maintain quality, especially when referenced in future frames. 4. Temporal Importance: CUs that are expected to be referenced across multiple future frames, or that appear in important temporal layers (such as in hierarchical B-frames) , are given higher CU strength. How CU Strength Affects Encoding: 1. Bit Allocation: CUs with higher strength are allocated more bits, which translates to a lower QP (higher quality) . This ensures that these critical CUs are encoded with greater precision, preserving details that will be important for future frame predictions. 2. Adaptive Quantization: The CU-tree algorithm uses CU strength to adjust the QP adaptively across the frame. High-strength CUs get a lower QP, while low-strength CUs might get a higher QP. This dynamic adjustment optimizes the overall visual quality of the video. 3. Rate Control: CU strength informs the rate control mechanism in x265, helping to distribute bits more effectively across the entire video sequence. This results in better overall video quality, es-pecially in scenarios with varying motion and scene complexity. Implementation in CU-tree: During the encoding process, x265 calculates the strength of each CU as part of the CU-tree analysis. This involves: 1. Frame Analysis: The encoder assesses the contribution of each CU to future frames, taking into account motion vectors, residuals, and temporal importance. 2. CU-tree Propagation: The calculated strength is propagated through the CU-tree structure, influ- encing the QP decisions for each CU. 3. Bitrate Optimization: Based on the CU strength, the encoder adjusts bit allocation to optimize the quality and compression efficiency of the encoded video. Impact of CU Strength on Video Quality: 1. Sharper Key Areas: By allocating more bits to high-strength CUs, the encoder ensures that key areas of the video, especially those critical for future frame predictions, are preserved with higher quality. 2. Efficient Compression: CU strength allows x265 to achieve efficient compression by intelligently distributing bits, minimizing the impact on perceptual quality while maintaining low bitrates. In summary, CU strength is a vital component of the CU-tree algorithm in x265, directly influencing how bits are allocated across different parts of the video frame. This contributes to the overall efficiency and quality of the video encoding process. 3. Detailed Solutions The proposed solutions focus on optimizing the CU-tree mechanism in encoders such as x265 to improve video encoding efficiency and quality. The CU-tree model currently relies on pre-analysis reference relationships, which may not accurately reflect true rate-distortion (RD) outcomes. To address this, the method introduces a quantization model in the pre-analysis phase to enhance the accuracy of cost calculations, aligning them more closely with actual encoding results. Additionally, the refinement of CU Tree Strength-based on factors such as content consistency, quantization accuracy, and temporal hierarchy-ensures a more precise bit allocation during encoding. Simplifying the cost calculation models also reduces computational complexity while maintaining accuracy. These combined strategies aim to correct the CU-tree model using real encoding data, reduce dependency on potentially inaccurate pre-analysis, and improve the reliability of bit allocation, ultimately leading to a better video quality and compression efficiency. Fig. 4 illustrates the modeling process of the proposed method. In it, the distortion of the current frame can be expressed as the following formula. D0∝ (DA0+DB0) · (D′A0+D′B0) where D0 denotes the distortion between the current frame and its reconstructed counterpart. In other words, it represents the distortion between current frame and the reconstructed frame. DA0 and DB0 is the distortion of the forward reference frame and backward reference frame, respectively. Because fA and fB serve as the reference frames for the current frame, the reconstruction distortion of the current frame is directly proportional to the difference between the current frame and the reference frames. Since D′A0 represents the difference from the reconstructed reference frame, and the quality of the reconstructed reference frame is related to the quantization parameter (QP) , the formula can be further expressed as: D0∝ (DA0+DB0) · (Q (fA) +Q (fB) ) ·Q (f) In this equation, ‘DA0+DB0’ is the frame similarity of the current frame and its reference frame. ‘ (Q (fA) + Q(fB) ) ·Q (f) ’ is the impact of the quantization parameter (QP) on the distortion of the current frame. Therefore, the inter-frame similarity, quantization parameter, and the temporal layer of the current frame are the three most influential factors affecting the quality of the current frame. With these considerations, these three elements are used to fine-tune the strength of the CU-tree according to some example embodiments of the present disclosure. 3.1 Frame Similarity Calculate the degree of degradation of current frame's information by calculating the SSIM between the current encoding frame and all the reference frames on its reference information propagation path. δssim is the degree of degradation of current frame's information. N represents the number of the reference frames of the current encoding frame. f0 and fk represent the current encoding frame and the reference frame of the current encoding frame, respectively. σk is an adjustable parameter used to adjust the weight of the SSIM value for each frame. The value of this parameter can be determined through learning or manual adjustment methods. 3.2 Temporal Layer Fig. 5 illustrates the typical hierarchical structure used for encoding frames. When fine-tuning the strength of the CU (Coding Unit) within the CU-tree, the layer number of the current frame is considered a crucial factor. Determine the information degradation level that has occurred in the quantized frames. Higher temporal layer means more cumulative distortion in its reference frames, and at the same time lower desired quality of the current frame. δlayer=L×σl (2) δlayer determines the information degradation level based on the temporal layer of each frame. L stands for the hierarchical layer / temporal layer. σl is an adjustable parameter used to adjust the weight of the hierarchical layer for each frame. The value of this parameter can be determined through learning or manual adjustment methods. 3.3 Base QP The base QP determines the desired level of distortion of the current frame, determining the efficiency and strength of the mutual information optimizations. δqp=QP×σq (3) δqp represents the influence of QP on strength. σq is an adjustable parameter used to adjust the weight of the QP for each frame. The value of this parameter can be determined through learning or manual adjustment methods. 3.4 Strength Adjustment With above three properties, the scaling factor δstr of the mapping strength of the mutual information algorithm can be calculated as follows: δstr=α·δssim+β·δl+γ·δq-δ0 (4) δstr is the scaling factor that affect the value of CU strength. The value of CU strength will multiplied by δstr yields the updated strength value, which in turn affects the determination of the QP offset. In Equation (4) , α, β, γ and δ0 are adjustable parameter which can be determined through learning or manual adjustment methods. 3.5 Example Solutions 1. Scaling and / or shifting the strength factors of information-propagation algorithms through frame similarity, temporal layer and / or frame QP.
[0063] More details of the embodiments of the present disclosure will be described below which are related to video coding. The embodiments of the present disclosure should be considered as examples to explain the general concepts and should not be interpreted in a narrow way. Furthermore, these embodiments can be applied individually or combined in any manner.
[0064] As used herein, the term “video unit” may represent a macroblock (MB) , a coding tree block (CTB) , a coding tree unit (CTU) , a coding block (CB) , a coding unit (CU) , a prediction unit (PU) , a transform unit (TU) , a prediction block (PB) , a transform block (TB) , a subblock, a tile, a slice, a subpicture, a video processing unit comprising multiple samples / pixels, and / or the like. A video unit may be rectangular or non-rectangular.
[0065] Fig. 6 illustrates a flowchart of a method 600 for video processing in accordance with some embodiments of the present disclosure. The method 600 may be implemented during a conversion between a current video unit within a current frame of a video and a bitstream of the video. As shown in Fig. 6, the method 600 starts at 602 where a scaling factor is determined based on coding information of the current frame. By way of example rather than limitation, the coding information may comprise a value of a similarity metric between the current frame and at least one reference frame of the current frame, a temporal layer of the current frame, a base QP for the current frame, a motion vector for the current video unit, prediction residuals of the current video unit, a scene complexity of the current video unit, and / or the like. It should be understood that the possible implementations of the coding information described here are merely illustrative and therefore should not be construed as limiting the present disclosure in any way.
[0066] At 604, a strength factor for the current video unit is adjusted based on the scaling factor. For example, the strength factor to be adjusted may be predetermined. Alternatively, the strength factor to be derived based on x264 or x265 software. As used herein, the strength factor may also be referred to as a strength, a CU strength, or the like.
[0067] In one example embodiment, the strength factor may be scaled based on the scaling factor to obtain an adjusted strength factor. In another example embodiment, the strength factor may be scaled based on the scaling factor and the scaled strength factor may be biased to obtain an adjusted strength factor. For example, the scaling of the strength factor may be implemented with an arithmetic shifting operation, such as arithmetic right shift and / or arithmetic left shift. Alternatively or additionally, the scaling of the strength factor may be implemented with a multiplier and / or a divider. It should be understood that the possible implementations of the strength factor adjustment described here are merely illustrative and therefore should not be construed as limiting the present disclosure in any way.
[0068] At 606, a quantization parameter (QP) for the current video unit is determined based on the adjusted strength factor and information propagation associated with the current video unit. By way of example, a base QP for the current frame may be obtained. In addition, a QP offset for the current video unit may be determined based on the adjusted strength factor and the information propagation according to a macroblock-tree (MB-tree) scheme or a coding-unit-tree (CU-tree) scheme, and the base QP is adjusted with the QP offset to obtain the QP for the current video unit. In the MB-tree scheme or the CU-tree scheme, a propagation cost and an intra cost id calculated for each MB or CU, so as to generate a QP offset that implies a significance of the MB or CU. In one example embodiment, the QP offset may be determined as follows: ΔQP = -strength_adjusted × log2 ( (intra_cost + propagate_cost) / intra_cost) , where ΔQP represents the QP offset, strength_adjusted represents the adjusted strength factor, intra_cost represents the calculated intra cost, and propagate_cost represents the calculated propagation cost. It should be noted that the QP for the current video unit may also be determined based on the adjusted strength factor and the information propagation in any other suitable manner, and the scope of the present disclosure is not limited in this respect.
[0069] At 608, the conversion is performed based on the QP. In some embodiments, the conversion may include encoding the current video unit into the bitstream. Alternatively or additionally, the conversion may include decoding the current video unit from the bitstream. It should be understood that the above illustrations and / or examples are described merely for purpose of description. The scope of the present disclosure is not limited in this respect.
[0070] In view of the above, a scaling factor is determined based on coding information of the current frame and is further used to adjust a strength factor for determining the QP for the current video unit. Compared with the conventional solution where the strength factor is used to determine the QP without adjustment, the proposed solution can advantageously reduce dependency on potentially inaccurate pre-analysis and improve the reliability of bit allocation for the current video unit, thereby improving coding quality and coding efficiency.
[0071] In some embodiments, at 602, a first factor may be determined based on the value of the similarity metric. By way of example, the first factor may be determined as follows: where δfs represents the first factor, N represents the number of the at least one reference frame of the current frame, f0 represents the current frame, fk represents the k-th reference frame of the current frame, FS(f0, fk) represents a value of the similarity metric between frames f0 and fk, and σk represents a weighting factor for the k-th reference frame. In some embodiments, the similarity metric may be a structure similarity index measure (SSIM) , a mean squared error (MSE) , a structural dissimilarity (DSSIM) or the like. In some embodiments, the weighting factor σk may be determined through a machine-learning process or a manual adjustment process. The machine-learning process may be trained with real coding data, so as to improve the accuracy of the proposed solution. It should be understood that the above examples are described merely for purpose of description. The scope of the present disclosure is not limited in this respect.
[0072] Additionally or alternatively, at 602, a second factor may be determined based on the temporal layer. By way of example, the second factor may be determined as follows: δl=L×σl, where δl represents the second factor, L represents the temporal layer of the current frame, and σl represents a weighting factor. For example, the weighting factor σl may be determined through a machine-learning process or a manual adjustment process. The machine-learning process may be trained with real coding data, so as to improve the accuracy of the proposed solution. It should be understood that the above examples are described merely for purpose of description. The scope of the present disclosure is not limited in this respect.
[0073] In some additional or alternative embodiments, at 602, a third factor may be determined based on the base QP. By way of example, the third factor may be determined as follows: δq=QP×σq, where δq represents the third factor, QP represents the base QP for the current frame, and σq represents a weighting factor. For example, the weighting factor σq may be determined through a machine-learning process or a manual adjustment process. The machine-learning process may be trained with real coding data, so as to improve the accuracy of the proposed solution. It should be understood that the above examples are described merely for purpose of description. The scope of the present disclosure is not limited in this respect.
[0074] In some embodiments, the scaling factor may be determined based on a weighted sum of at least two of following: the first factor, the second factor, or the third factor. By way of example, the scaling factor may be determined as follows: δstr=α·δfs+β·δl+γ·δq-δ0, where δstr represents the scaling factor, δfs represents the first factor, δl represents the second factor, δq represents the third factor, δ0 represents an offset, and each of α, β and γ represents a weighting factor. In some embodiments, at least one of α, β, γ, or δ0 may be determined through a machine-learning process or a manual adjustment process. The machine-learning process may be trained with real coding data, so as to improve the accuracy of the proposed solution. It should be understood that the above examples are described merely for purpose of description. The scope of the present disclosure is not limited in this respect.
[0075] In view of the above, the solutions in accordance with some embodiments of the present disclosure can advantageously improve coding efficiency and coding quality.
[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, for a conversion between a current video unit within a current frame of a video and a bitstream of the video, a scaling factor based on coding information of the current frame; adjusting a strength factor for the current video unit based on the scaling factor; determining a quantization parameter (QP) for the current video unit based on the adjusted strength factor and information propagation associated with the current video unit; and generating the bitstream based on the QP.
[0077] According to still further embodiments of the present disclosure, a method for storing bitstream of a video is provided. The method comprises: determining, for a conversion between a current video unit within a current frame of a video and a bitstream of the video, a scaling factor based on coding information of the current frame; adjusting a strength factor for the current video unit based on the scaling factor; determining a quantization parameter (QP) for the current video unit based on the adjusted strength factor and information propagation associated with the current video unit; generating the bitstream based on the QP; 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 current video unit within a current frame of a video and a bitstream of the video, a scaling factor based on coding information of the current frame; adjusting a strength factor for the current video unit based on the scaling factor; determining a quantization parameter (QP) for the current video unit based on the adjusted strength factor and information propagation associated with the current video unit; and performing the conversion based on the QP.
[0080] Clause 2. The method of clause 1, wherein the coding information comprises at least one of the following: a value of a similarity metric between the current frame and at least one reference frame of the current frame, a temporal layer of the current frame, or a base QP for the current frame.
[0081] Clause 3. The method of clause 2, wherein determining the scaling factor comprises at least one of the following: determining a first factor based on the value of the similarity metric; determining a second factor based on the temporal layer; or determining a third factor based on the base QP.
[0082] Clause 4. The method of clause 3, wherein the first factor is determined as follows: wherein δfs represents the first factor, N represents the number of the at least one reference frame of the current frame, f0 represents the current frame, fk represents the k-th reference frame of the current frame, FS(f0, fk) represents a value of the similarity metric between frames f0 and fk, and σk represents a weighting factor for the k-th reference frame.
[0083] Clause 5. The method of clause 4, wherein the similarity metric comprises a structure similarity index measure (SSIM) , and / or the weighting factor σk is determined through a machine-learning process or a manual adjustment process.
[0084] Clause 6. The method of any of clauses 3-5, wherein the second factor is determined as follows: δl=L×σl, wherein δl represents the second factor, L represents the temporal layer of the current frame, and σl represents a weighting factor.
[0085] Clause 7. The method of clause 6, wherein the weighting factor σl is determined through a machine-learning process or a manual adjustment process.
[0086] Clause 8. The method of any of clauses 3-7, wherein the third factor is determined as follows: δq=QP×σq, wherein δq represents the third factor, QP represents the base QP for the current frame, and σq represents a weighting factor.
[0087] Clause 9. The method of clause 8, wherein the weighting factor σq is determined through a machine-learning process or a manual adjustment process.
[0088] Clause 10. The method of any of clauses 3-9, wherein the scaling factor is determined based on a weighted sum of at least two of following: the first factor, the second factor, or the third factor.
[0089] Clause 11. The method of clause 10, wherein the scaling factor is determined as follows: δstr=α·δfs+β·δl+γ·δq-δ0, wherein δstr represents the scaling factor, δfs represents the first factor, δl represents the second factor, δq represents the third factor, δ0 represents an offset, and each of α, β and γ represents a weighting factor.
[0090] Clause 12. The method of clause 11, wherein at least one of α, β, γ, or δ0 is determined through a machine-learning process or a manual adjustment process.
[0091] Clause 13. The method of any of clauses 1-12, wherein adjusting the strength factor comprises: scaling the strength factor based on the scaling factor to obtain the adjusted strength factor.
[0092] Clause 14. The method of clause 13, wherein the scaling of the strength factor is implemented with an arithmetic shifting operation.
[0093] Clause 15. The method of any of clauses 1-14, wherein determining the QP for the current video unit comprises: obtaining a base QP for the current frame; determining a QP offset for the current video unit based on the adjusted strength factor and the information propagation according to a macroblock-tree (MB-tree) scheme or a coding-unit-tree (CU-tree) scheme; and adjusting the base QP with the QP offset to obtain the QP for the current video unit.
[0094] Clause 16. The method of any of clauses 1-15, wherein the current video unit comprises a macroblock (MB) or a coding unit (CU) .
[0095] Clause 17. The method of any of clauses 1-16, wherein the conversion includes encoding the current video unit into the bitstream.
[0096] Clause 18. The method of any of clauses 1-16, wherein the conversion includes decoding the current video unit from the bitstream.
[0097] Clause 19. 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 1-18.
[0098] Clause 20. A non-transitory computer-readable storage medium storing instructions that cause a processor to perform a method in accordance with any of clauses 1-18.
[0099] Clause 21. 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, for a conversion between a current video unit within a current frame of a video and a bitstream of the video, a scaling factor based on coding information of the current frame; adjusting a strength factor for the current video unit based on the scaling factor; determining a quantization parameter (QP) for the current video unit based on the adjusted strength factor and information propagation associated with the current video unit; and generating the bitstream based on the QP.
[0100] Clause 22. A method for storing a bitstream of a video, comprising: determining, for a conversion between a current video unit within a current frame of a video and a bitstream of the video, a scaling factor based on coding information of the current frame; adjusting a strength factor for the current video unit based on the scaling factor; determining a quantization parameter (QP) for the current video unit based on the adjusted strength factor and information propagation associated with the current video unit; generating the bitstream based on the QP; and storing the bitstream in a non-transitory computer-readable recording medium. Example Device
[0101] Fig. 7 illustrates a block diagram of a computing device 700 in which various embodiments of the present disclosure can be implemented. The computing device 700 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) .
[0102] It would be appreciated that the computing device 700 shown in Fig. 7 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.
[0103] As shown in Fig. 7, the computing device 700 includes a general-purpose computing device 700. The computing device 700 may at least comprise one or more processors or processing units 710, a memory 720, a storage unit 730, one or more communication units 740, one or more input devices 750, and one or more output devices 760.
[0104] In some embodiments, the computing device 700 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 700 can support any type of interface to a user (such as “wearable” circuitry and the like) .
[0105] The processing unit 710 may be a physical or virtual processor and can implement various processes based on programs stored in the memory 720. 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 700. The processing unit 710 may also be referred to as a central processing unit (CPU) , a microprocessor, a controller or a microcontroller.
[0106] The computing device 700 typically includes various computer storage medium. Such medium can be any medium accessible by the computing device 700, including, but not limited to, volatile and non-volatile medium, or detachable and non-detachable medium. The memory 720 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 730 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 700.
[0107] The computing device 700 may further include additional detachable / non-detachable, volatile / non-volatile memory medium. Although not shown in Fig. 7, 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.
[0108] The communication unit 740 communicates with a further computing device via the communication medium. In addition, the functions of the components in the computing device 700 can be implemented by a single computing cluster or multiple computing machines that can communicate via communication connections. Therefore, the computing device 700 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.
[0109] The input device 750 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 760 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 740, the computing device 700 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 700, or any devices (such as a network card, a modem and the like) enabling the computing device 700 to communicate with one or more other computing devices, if required. Such communication can be performed via input / output (I / O) interfaces (not shown) .
[0110] In some embodiments, instead of being integrated in a single device, some or all components of the computing device 700 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.
[0111] The computing device 700 may be used to implement video encoding / decoding in embodiments of the present disclosure. The memory 720 may include one or more video coding modules 725 having one or more program instructions. These modules are accessible and executable by the processing unit 710 to perform the functionalities of the various embodiments described herein.
[0112] In the example embodiments of performing video encoding, the input device 750 may receive video data as an input 770 to be encoded. The video data may be processed, for example, by the video coding module 725, to generate an encoded bitstream. The encoded bitstream may be provided via the output device 760 as an output 780.
[0113] In the example embodiments of performing video decoding, the input device 750 may receive an encoded bitstream as the input 770. The encoded bitstream may be processed, for example, by the video coding module 725, to generate decoded video data. The decoded video data may be provided via the output device 760 as the output 780.
[0114] 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 current video unit within a current frame of a video and a bitstream of the video, a scaling factor based on coding information of the current frame;adjusting a strength factor for the current video unit based on the scaling factor;determining a quantization parameter (QP) for the current video unit based on the adjusted strength factor and information propagation associated with the current video unit; andperforming the conversion based on the QP.2.The method of claim 1, wherein the coding information comprises at least one of the following:a value of a similarity metric between the current frame and at least one reference frame of the current frame,a temporal layer of the current frame, ora base QP for the current frame.3.The method of claim 2, wherein determining the scaling factor comprises at least one of the following:determining a first factor based on the value of the similarity metric;determining a second factor based on the temporal layer; ordetermining a third factor based on the base QP.4.The method of claim 3, wherein the first factor is determined as follows: wherein δfs represents the first factor, N represents the number of the at least one reference frame of the current frame, f0 represents the current frame, fk represents the k-th reference frame of the current frame, FS (f0, fk) represents a value of the similarity metric between frames f0 and fk, and σk represents a weighting factor for the k-th reference frame.5.The method of claim 4, wherein the similarity metric comprises a structure similarity index measure (SSIM) , and / or the weighting factor σk is determined through a machine-learning process or a manual adjustment process.6.The method of any of claims 3-5, wherein the second factor is determined as follows: δl=L×σl,wherein δl represents the second factor, L represents the temporal layer of the current frame, and σl represents a weighting factor.7.The method of claim 6, wherein the weighting factor σl is determined through a machine-learning process or a manual adjustment process.8.The method of any of claims 3-7, wherein the third factor is determined as follows: δq=QP×σq,wherein δq represents the third factor, QP represents the base QP for the current frame, and σq represents a weighting factor.9.The method of claim 8, wherein the weighting factor σq is determined through a machine-learning process or a manual adjustment process.10.The method of any of claims 3-9, wherein the scaling factor is determined based on a weighted sum of at least two of following: the first factor, the second factor, or the third factor.11.The method of claim 10, wherein the scaling factor is determined as follows: δstr=α·δfs+β·δl+γ·δq-δ0,wherein δstr represents the scaling factor, δfs represents the first factor, δl represents the second factor, δq represents the third factor, δ0 represents an offset, and each of α, β and γ represents a weighting factor.12.The method of claim 11, wherein at least one of α, β, γ, or δ0 is determined through a machine-learning process or a manual adjustment process.13.The method of any of claims 1-12, wherein adjusting the strength factor comprises:scaling the strength factor based on the scaling factor to obtain the adjusted strength factor.14.The method of claim 13, wherein the scaling of the strength factor is implemented with an arithmetic shifting operation.15.The method of any of claims 1-14, wherein determining the QP for the current video unit comprises:obtaining a base QP for the current frame;determining a QP offset for the current video unit based on the adjusted strength factor and the information propagation according to a macroblock-tree (MB-tree) scheme or a coding-unit-tree (CU-tree) scheme; andadjusting the base QP with the QP offset to obtain the QP for the current video unit.16.The method of any of claims 1-15, wherein the current video unit comprises a macroblock (MB) or a coding unit (CU) .17.The method of any of claims 1-16, wherein the conversion includes encoding the current video unit into the bitstream.18.The method of any of claims 1-16, wherein the conversion includes decoding the current video unit from the bitstream.19.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 1-18.20.A non-transitory computer-readable storage medium storing instructions that cause a processor to perform a method in accordance with any of claims 1-18.21.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, for a conversion between a current video unit within a current frame of a video and a bitstream of the video, a scaling factor based on coding information of the current frame;adjusting a strength factor for the current video unit based on the scaling factor;determining a quantization parameter (QP) for the current video unit based on the adjusted strength factor and information propagation associated with the current video unit; andgenerating the bitstream based on the QP.22.A method for storing a bitstream of a video, comprising:determining, for a conversion between a current video unit within a current frame of a video and a bitstream of the video, a scaling factor based on coding information of the current frame;adjusting a strength factor for the current video unit based on the scaling factor;determining a quantization parameter (QP) for the current video unit based on the adjusted strength factor and information propagation associated with the current video unit;generating the bitstream based on the QP; andstoring the bitstream in a non-transitory computer-readable recording medium.
Citation Information
Patent Citations
Variations of rho-domain rate control
US20160205404A1
Fractional Quantization Parameter Offset In Video Compression
US20190020875A1
Method and system for signaling chroma quantization parameter offset
US20210092380A1
Signaling of Quantization Parameters in Video Coding
US20230007256A1