Reference node resampling for inter prediction in regional adaptive hierarchical transform coding

Abstract

A mechanism for processing video data is disclosed. The mechanism can include determining, as part of a region adaptive hierarchical transform (RAHT) operation, resampling of alternating current (AC) inter prediction in a sample domain or mean attribute space based on an occupancy of a current node to obtain a sample domain direct current (DC) prediction for a sub-node. Conversion between visual media data and a bitstream can then be performed based on the RAHT operation.

Description

[0001] Cross-references to related applications

[0002] This application claims priority and benefit from International Application No. PCT / CN2024 / 083226, filed March 22, 2024, and International Application No. PCT / CN2024 / 091686, filed May 8, 2024. Both applications are incorporated herein by reference in their entirety. Technical Field

[0003] This disclosure relates to the generation, storage, and use of digital audio and video media information in file formats. Background Technology

[0004] Digital video accounts for the largest share of bandwidth used on the internet and other digital communication networks. As the number of connected user devices capable of receiving and displaying video increases, the bandwidth demand for digital video is likely to continue to grow. Summary of the Invention

[0005] The first aspect relates to a method for processing video data, comprising: as part of a Region-Adaptive Hierarchical Transform (RAHT) operation, determining, based on the occupancy of the current node, to resample the Alternating Current (AC) inter-frame prediction in the sample domain or mean attribute space to obtain a sample domain Direct Current (DC) prediction for the child node; and performing a conversion between visual media data and a bitstream based on the RAHT operation.

[0006] The second aspect relates to an apparatus for processing video data, comprising: a processor; and a non-transitory memory having instructions thereon, wherein the instructions, when executed by the processor, cause the processor to perform any of the preceding aspects.

[0007] The third aspect relates to a non-transitory computer-readable medium comprising a computer program product for use by a video codec apparatus, the computer program product including computer-executable instructions stored on the non-transitory computer-readable medium such that, when executed by a processor, the video codec apparatus performs the methods of any of the preceding aspects.

[0008] The fourth aspect relates to a non-transitory computer-readable recording medium for storing a bitstream of video, the bitstream being generated by a method performed by a video processing apparatus, wherein the method includes: as part of a Region Adaptive Hierarchical Transform (RAHT) operation, determining, based on the occupancy of a current node, to resample an AC inter-frame prediction in a sample domain or mean attribute space to obtain a sample domain DC prediction for a child node; and generating the bitstream based on the determination.

[0009] The fifth aspect relates to a method for storing a bitstream of video, comprising: as part of a Region Adaptive Hierarchical Transform (RAHT) operation, determining, based on the occupancy of a current node, to resample an AC inter-frame prediction in a sample domain or mean attribute space to obtain a sample domain DC prediction for a child node; generating a bitstream based on the determination; and storing the bitstream in a non-transitory computer-readable recording medium.

[0010] The sixth aspect relates to the methods, apparatus, or systems described in this disclosure.

[0011] For clarity, any of the embodiments described above may be combined with one or more other embodiments described above to create new embodiments within the scope of this disclosure.

[0012] These and other features will become clearer through the following detailed description of the embodiments with reference to the accompanying drawings and claims. Attached Figure Description

[0013] To gain a more complete understanding of this disclosure, reference is now made to the following brief description, taken in conjunction with the accompanying drawings and detailed description, wherein like reference numerals denote like parts.

[0014] Figure 1 This is an example of the parent node of each child node of the transformation unit node.

[0015] Figure 2 This is a block diagram illustrating an example video processing system.

[0016] Figure 3 This is a block diagram of an example video processing device.

[0017] Figure 4 This is a flowchart of an example method for video processing.

[0018] Figure 5 This is a block diagram illustrating an example video codec system.

[0019] Figure 6 This is a block diagram showing an example encoder.

[0020] Figure 7 This is a block diagram showing an example decoder.

[0021] Figure 8 This is a schematic diagram of an example encoder. Detailed Implementation

[0022] First, it should be understood that although illustrative implementations of one or more embodiments are provided below, the disclosed systems and / or methods can be implemented using any number of techniques, whether currently known or yet to be developed. This disclosure should not be limited in any way to the illustrative implementations, drawings, and techniques shown below, including the exemplary designs and implementations shown and described herein, but rather to modifications and the full scope of their equivalents within the scope of the appended claims.

[0023] 1. Preliminary Discussion

[0024] This disclosure relates to media file formats. Specifically, it relates to inter-frame prediction of point cloud attributes in region-adaptive hierarchical transformation. These ideas can be applied individually or in various combinations to any standard or non-standard point cloud codec, such as the geometry-based point cloud compression (G-PCC) currently under development.

[0025] 2. Abbreviation

[0026] G-PCC Geometric-Based Point Cloud Compression

[0027] MPEG Moving Picture Experts Group

[0028] 3DG 3D Graphics Codec

[0029] CFP Proposal Solicitation

[0030] V-PCC: Video-based Point Cloud Compression

[0031] RAHT region adaptive hierarchical transformation

[0032] 3. Further discussion

[0033] MPEG is an abbreviation for Moving Picture Experts Group, one of the major standardization organizations for processing multimedia. In 2017, the MPEG 3D Graphics Codec Group (3DG) released a Call for Proposals (CFP) document to begin developing a point cloud coding and decoding standard [1]. The final standard will include two types of solutions. Video-based Point Cloud Compression (V-PCC) is suitable for point sets with a relatively uniform point distribution [2]. Geometry-based Point Cloud Compression (G-PCC) is suitable for sparser distributions [3]. Both V-PCC and G-PCC support encoding and decoding of single point clouds and sequences of point clouds.

[0034] A point cloud can contain geometric information and attribute information. Geometric information describes the geometric location of the data points. Attribute information records details of the data points, such as texture, normal vectors, and reflections.

[0035] 3.1 Regional Adaptive Hierarchical Transformation

[0036] In G-PCC, one of the important point cloud attribute encoding and decoding tools is RAHT. RAHT is a transformation that uses attributes associated with nodes in lower levels of an octree to predict the attributes of nodes in the next level [4]. RAHT assumes that the location of the points is given at both the encoder and decoder. RAHT follows the octree scan backward from the leaf nodes to the root node, recombining the nodes into larger nodes at each step until the root node is reached. At each level of the octree, the nodes are processed in Morton order. Instead of combining all eight nodes at once at each decomposition, RAHT does so in three steps along each dimension (e.g., along z, then y, then x). If there are nodes in the octree... If there are several levels, then RAHT needs to The tree is traversed backwards at each level.

[0037] Assumption level The node at is For integers . Through the and The results are obtained through combinations, with combinations along the first dimension being an example. RAHT only processes occupied nodes. If one node in a pair is not occupied, the other node is promoted to the next level and not processed; that is, if the latter is the occupied node in the pair, then... The combination process is repeated until the root is reached. Note that the combination process generates lower-level nodes, which are the result of combining different numbers of voxels along the way. The nodes are combined to generate nodes. The number of nodes is the weight of that node. .

[0038] In two nodes (e.g.) and Each time ) is combined, their respective weights are used. and RAHT applies the following transformations: , in, and as well as . Note that the transformation matrix is ​​constantly changing to adapt to the weights, that is, to adapt to each... The actual number of leaf nodes represented. Used to combine and form further nodes at lower levels. These are the actual high-pass coefficients to be encoded and transmitted, generated by the transformation. Furthermore, the weights are accumulated at the levels described above. In the example above,

[0039] In the final stage, the roots of the tree, the remaining two voxels and Transformed into the final two coefficients:

[0040] in, .

[0041] 3.2 Upsampling Transform Domain Prediction in RAHT

[0042] Figure 1 This is an example of the parent node of each child node of the transformation unit node.

[0043] Transform domain prediction is introduced to improve the encoding and decoding efficiency of RAHT[5]. RAHT consists of two parts.

[0044] First, the RAHT tree traversal is changed from the previous ascending-based method to a descending-based method, i.e., a tree of attributes and weights is constructed, and then RAHT is performed on both the encoder and decoder from the root to the leaf. This transformation is also performed in an octree node transformation unit with 2×2×2 child nodes. Within a node, the encoder transformation order is from leaf to root.

[0045] Secondly, for each child node of the transform unit, a corresponding predictive child node is generated by upsampling the previous transform level. In fact, only child nodes containing the last point will generate corresponding predictive child nodes. The transform unit containing 2×2×2 predictive child nodes is transformed and subtracted from the transform attributes on the encoder side.

[0046] Each child node of a transformation unit node is predicted by 7 parent-level nodes, including 3 collinear parent-level neighbor nodes, 3 coplanar parent-level neighbor nodes, and 1 parent node. Coplanar neighbors and collinear neighbors are the neighbors that share faces and edges with the current transformation unit node, respectively. Figure 1 The diagram shows the seven parent-level nodes of each child node of the transformation unit node.

[0047] Attributes of each child node Based on its distance from its parent node, it is predicted as follows:

[0048] in, It is a property of a parent node of this child node, and It depends on the distance weight. In G-PCC, .

[0049] For the AC coefficients, the residuals will be predicted through signal transmission.

[0050] For DC coefficients, the coefficients are inherited from previous levels, which means that DC coefficients are transmitted through the signal without prediction.

[0051] 3.3 Attribute Inter-Frame Prediction in RAHT

[0052] Inter-frame prediction in RAHT is discussed in [6]. It is proposed to apply inter-frame prediction to the DC and AC coefficients in RAHT. The same octree decomposition is performed on the current frame and the reference frame.

[0053] For the first L layers (as specified in the bitstream), the same octree scan is performed on both frames. Before performing the backward octree scan, a point-to-point matching process is performed to ensure that nodes in the reference frame can establish corresponding one-to-one relationships with nodes in the current frame. For each point in the reference frame, it is matched to a point in the current frame using the "top-match" method. The Morton value of the matched point is the smallest Morton value greater than the current point's Morton value.

[0054] For the DC coefficients, the residual between the DC coefficients for the root node of the current frame and the DC coefficients for the root node of the reference frame is calculated as follows:

[0055] Through signal transmission To the decoder, to replace .

[0056] For each node in the first L layers, the average attribute of nodes at the same octree position in the reference frame is calculated as follows: And the corresponding AC coefficient is calculated as .

[0057] For the AC coefficients, the prediction residuals are transmitted via signal as follows:

[0058]

[0059] if If it equals 0, then It is used for prediction in the original transform domain.

[0060] Another approach in GPCC is to perform predictions in the RAHT domain, rather than in attributes and space. Therefore, there are two types in GPCC: Type 0 performs inter-frame predictions in the RAHT domain, and Type 1 performs predictions in attributes and space.

[0061] 4. Technical problems solved by the disclosed embodiments

[0062] The example design for inter-frame prediction of point cloud attributes in Region Adaptive Hierarchical Transformation (RAHT) has the following problems: First, in the example design, during AC prediction, the inter-frame prediction signal in the sample domain has a different occupancy than the current node, resulting in poor prediction.

[0063] Second, in the example design, inter-frame prediction is transformed using a kernel that depends on the weight distribution of the reference node, while reconstruction is transformed using a kernel that depends on the weight distribution of the current node. This leads to a mismatch, resulting in suboptimality.

[0064] 5. List of solutions and implementation examples

[0065] To address the issues mentioned above and other unmentioned problems, the following outlined methods are disclosed. These items should be considered as examples for explaining general concepts, and not interpreted in a narrow sense. Furthermore, these examples can be applied individually or in combination in any way.

[0066] In the following description, point cloud (PC) samples can refer to frames / subframes / images / subimages / strips / substrips / pieces, etc. The sample domain refers to the signal corresponding to the DC of the child node, and the mean attribute space refers to the average value of the attribute values ​​of the child node.

[0067] 1) In order to solve the shortcomings of problem 1, the embodiments of this disclosure can modify or resample the AC inter-frame prediction in the sample domain (or mean attribute space) based on the current node occupancy to obtain the sample domain prediction (DC prediction of child nodes).

[0068] a. In one example, if a child node in the current node is not occupied, the inter-frame prediction signal corresponding to that child node is set to zero.

[0069] b. In one example, if a child node in the current node is occupied, while the corresponding child node in the reference node is not occupied, the prediction of that child node can be obtained by interpolation.

[0070] i. In one example, interpolation can be the parent DC of a reference child node.

[0071] ii. Alternatively, the interpolation can be the parent DC of the current child node.

[0072] iii. Alternatively, interpolation can be a weighted sum of the parent DC of the current node and the parent DC of the reference node, such as the average of the two DC values.

[0073] iv. In one example, interpolation can be obtained by first upsampling the weighted sum of the reconstructed nearest neighbors in the reference node in the mean attribute space (similar to upsampling for intra-frame prediction), and then weighting it by the square root of the current child node to obtain the DC prediction of the child node.

[0074] v. Alternatively, interpolation can be obtained by: reconstructing the nearest neighbors in the current node in the mean attribute space, performing an upsampling process in the current node, and then weighting it by the square root of the current child nodes.

[0075] vi. In one example, interpolation can be obtained by: performing a joint upsampling process in the mean attribute space based on the weighted sum of the reconstructed nearest neighbors in the reference node and the current node, and then weighting it by the square root of the current child node.

[0076] vii. Alternatively, the prediction can be made in the mean attribute space, in which case the above prediction can be derived in the mean attribute space rather than in the sample domain.

[0077] c. In one example, this method is applied only to the last level (leaf level) of the RAHT node to achieve point matching between voxels in the current frame and voxels in the reference frame.

[0078] i. For example, the occupancy matching process can be applied to establish the correspondence between the 2x2x2 nodes in the last layer.

[0079] d. In an example where multiple reference frames exist, the exposed method can be applied to a subset of those reference frames.

[0080] 2) To address the shortcomings of problem 2, embodiments of this disclosure can obtain inter-frame prediction in the sample domain based on the weight distribution of the current node. Transform domain prediction can then be obtained by applying a transform to the RAHT kernel of the current node.

[0081] a. In one example, the method from Example 1 above can be applied first to match occupancy.

[0082] b. In one example, the prediction is first obtained in the mean attribute space of the reference node. Then, the sample domain prediction (or DC child node prediction) for the current node can be obtained by inverse normalization by multiplying it by the square root of the weight of the current node.

[0083] c. In one example, the derivation of the prediction in the mean attribute space of the reference node and the subsequent prediction in the sample domain for the current node is applicable only when both the current child node and its reference child node have non-zero weights.

[0084] d. In one example, given the DC of the corresponding child node in the reference node, the mean attribute prediction can be obtained by multiplying it by the inverse square root of the weight of the reference child node.

[0085] e. Alternatively, given the DC of the corresponding child node in the reference node, the mean attribute prediction can be obtained by dividing it by the square root of the weight of the reference child node.

[0086] f. In one example, if the weight of the reference child node is 1, the above multiplication / division in obtaining the mean attribute prediction can be bypassed.

[0087] g. In one example, if the weight of the current child node is 1, the inverse normalization of the DC prediction of the current child node in the mean attribute prediction can be skipped.

[0088] h. In one example, if the weights of the child nodes of the current node are the same as the weights of the corresponding child nodes in the reference node, the DC predictions of the child nodes can be used unchanged.

[0089] i. In one example, when multiple reference frames exist, the exposed method can be applied to a subset of those reference frames.

[0090] i. For example, this method is applied only if the current child node and its reference child node have non-zero weights.

[0091] 3) For lossless attribute encoding and decoding, the above-disclosed method can be modified as follows: a. In one example, the proposed method can be enabled or disabled by signaling a flag.

[0092] b. In one example, the definition of the node's mean property can be replaced with the average value formed during the construction of the integer-Haar transform tree for lossless property encoding / decoding. In the integer-Haar transform, two nodes are combined to simply form an average value, rather than taking a weighted average as in lossy RAHT, and the average value is rounded down.

[0093] c. In one example, if the mean attribute is taken as the actual average of the attribute values ​​of the leaf voxels under the node, the average can be rounded or mapped to the nearest integer to achieve lossless attribute encoding and decoding.

[0094] d. In one example, for the previously disclosed joint upsampling, the mean attribute value used for upsampling can be a mean attribute calculated in a lossy RAHT style (i.e., using the actual weighted sum).

[0095] e. In one example, for the previously disclosed joint upsampling, the mean attribute value used for upsampling can be a mean attribute calculated in lossless integer RAHT style (i.e., using the continuous simple average of the two nodes).

[0096] f. In one example, the inverse normalization applied to the mean attribute space can be bypassed to facilitate the use of the integer-Haar transform.

[0097] g. In one example, the obtained prediction can always be transformed to perform transform-domain prediction. Furthermore, depending on whether resampling is employed, the kernel can depend on either the reference transform tree or the current transform tree.

[0098] 4) Whether and / or how the methods disclosed above can be applied to transmit signals from the encoder to the decoder in a bitstream / frame / slice / strip / octree / etc.

[0099] 5) Whether and / or how to apply the methods disclosed above may depend on encoding and decoding information, such as dimensions, color format, color components, and stripe / image type.

[0100] 6. References

[0101] [1]MPEG 3DG and Requirements, “Call for Proposals for Point CloudCompression V2”, ISO / IEC JTC1 / SC29 WG11 N16763.

[0102] [2]ISO / IEC JTC 1 / SC 29 / WG 07, “Information technology — CodedRepresentation of Immersive Media — Part 5: Visual Volumetric Video-basedCoding (V3C) and Video-based Point Cloud Compression (V-PCC)”, ISO / IEC 23090-5.

[0103] [3] ISO / IEC JTC 1 / SC 29 / WG 11, “Information technology — MPEG-I(Coded Representation of Immersive Media) — Part 9: Geometry-based PointCloud Compression”, ISO / IEC 23090-9:2020(E).

[0104] [4] Ricardo L. De Queiroz and Philip A. Chou, “Compression of 3DPoint Clouds Using a Region-Adaptive Hierarchical Transform”, IEEETransactions on Image Processing.

[0105] [5] S. Lasserre, D. Flynn, “On an improvement of RAHT to exploitattribute correlation”, ISO / IEC JTC1 / SC29 / WG11 M47378.

[0106] [6] Y.-Z. Xu, W. Wang, K. Zhang, L. Zhang, [G-PCC][EE13.2 related][New proposal] Inter-Prediction for RAHT Attribute Coding, ISO / IEC JTC1 / SC29 / WG7 m61083, October 2022.

[0107] Figure 2This is a block diagram illustrating an example video processing system 4000 in which various embodiments disclosed herein may be implemented. Various implementations may include some or all of the components of system 4000. System 4000 may include an input 4002 for receiving video content. The video content may be received in a raw or uncompressed format, such as 8 or 10-bit multi-component pixel values, or in a compressed or encoded format. Input 4002 may represent a network interface, a peripheral bus interface, or a storage interface. Examples of network interfaces include wired interfaces (such as Ethernet, Passive Optical Network (PON), etc.) and wireless interfaces (such as Wi-Fi or cellular interfaces).

[0108] System 4000 may include an encoding / decoding component 4004 capable of implementing the various encoding / decoding or coding methods described in this disclosure. Encoding / decoding component 4004 can reduce the average bit rate from the video input 4002 to the output of encoding / decoding component 4004 to produce an encoded / decoded representation of the video. Encoding / decoding techniques are therefore sometimes referred to as video compression or video transcoding techniques. The output of encoding / decoding component 4004 may be stored or transmitted via a communication connection, such as that represented by component 4006. The stored or communicatively transmitted bitstream (or encoded / decoded) representation of the video received at input 4002 may be used by component 4008 to generate pixel values ​​or displayable video that is sent to display interface 4010. The process of generating user-visible video from the bitstream representation is sometimes referred to as video decompression. Furthermore, although some video processing operations are referred to as “encoding / decoding” operations or tools, it should be understood that encoding / decoding tools or operations are used by the encoder, and the corresponding decoding tools or operations that inversely convert the encoding / decoding result will be performed by the decoder.

[0109] Examples of peripheral bus interfaces or display interfaces may include Universal Serial Bus (USB), High Definition Multimedia Interface (HDMI), or display interfaces. Examples of storage interfaces include Serial Advanced Technology Attachment (SATA), Peripheral Component Interconnect (PCI), Integrated Drive Electronics (IDE), and so on. The embodiments described in this disclosure can be embodied in various electronic devices, such as mobile phones, laptops, smartphones, or other devices capable of performing digital data processing and / or video display.

[0110] Figure 3This is a block diagram of an example video processing apparatus 4100. Apparatus 4100 can be used to implement one or more methods described herein. Apparatus 4100 can be embodied in a smartphone, tablet, computer, Internet of Things (IoT) receiver, etc. Apparatus 4100 may include one or more processors 4102, one or more memories 4104, and video processing circuitry 4106. The processors 4102(s) may be configured to implement one or more methods described herein. The memories 4104(s) may be used to store data and code for implementing the methods and embodiments described herein. The video processing circuitry 4106 may be used to implement some embodiments described herein in hardware circuitry. In some embodiments, the video processing circuitry 4106 may be at least partially included in the processor 4102, such as a graphics coprocessor.

[0111] Figure 4 This is a flowchart of an example method 4200 for video processing. In method 4200, at step 4202, as part of a RAHT operation, based on the occupancy of the current node, it is determined to resample the AC inter-frame prediction in the sample domain or mean attribute space to obtain the sample domain DC prediction for the child node. At step 4204, a conversion between visual media data and a bitstream is performed based on the RAHT operation. According to the example, the conversion in step 4204 may include encoding at the encoder or decoding at the decoder.

[0112] It should be noted that method 4200 can be implemented in a means of processing video data, including a processor and a non-transitory memory having instructions thereon, such as a video encoder 4400, a video decoder 4500, and / or an encoder 4600. In this case, the instructions, when executed by the processor, cause the processor to perform method 4200. Furthermore, method 4200 can be executed by a non-transitory computer-readable medium, which includes a computer program product for use by a video encoding / decoding device. The computer program product includes computer-executable instructions stored on the non-transitory computer-readable medium, causing the video encoding / decoding device to perform method 4200 when executed by a processor.

[0113] Figure 5 This is a block diagram illustrating an example video encoding / decoding system 4300 that can utilize embodiments of the present disclosure. The video encoding / decoding system 4300 may include a source device 4310 and a target device 4320. The source device 4310 generates encoded video data, and this source device 4310 may be referred to as a video encoding device. The target device 4320 can decode the encoded video data generated by the source device 4310, and this target device 4320 may be referred to as a video decoding device.

[0114] Source device 4310 may include video source 4312, video encoder 4314, and input / output (I / O) interface 4316. Video source 4312 may include sources such as video capture devices, interfaces for receiving video data from video content providers, and / or computer graphics systems for generating video data, or combinations thereof. Video data may include one or more pictures. Video encoder 4314 encodes the video data from video source 4312 to generate a bitstream. The bitstream may include a sequence of bits forming a codec representation of the video data. The bitstream may include codec pictures and associated data. Codec pictures are codec representations of pictures. Associated data may include sequence parameter sets, picture parameter sets, and other syntax structures. I / O interface 4316 may include a modulator / demodulator (modem) and / or a transmitter. Encoded video data may be transmitted directly to target device 4320 via network 4330 through I / O interface 4316. Encoded video data may also be stored on storage medium / server 4340 for access by target device 4320.

[0115] Target device 4320 may include I / O interface 4326, video decoder 4324, and display device 4322. I / O interface 4326 may include a receiver and / or a modem. I / O interface 4326 may acquire encoded video data from source device 4310 or storage medium / server 4340. Video decoder 4324 may decode the encoded video data. Display device 4322 may display the decoded video data to a user. Display device 4322 may be integrated with target device 4320 or may be external to target device 4320, wherein target device 4320 may be configured to interface with an external display device.

[0116] The video encoder 4314 and the video decoder 4324 can operate according to video compression standards, such as the High Efficiency Video Codec (HEVC) standard, the Multi-Functional Video Codec (VVM) standard, and other existing and / or further standards.

[0117] Figure 6 This is a block diagram illustrating an example of a video encoder 4400, which can be... Figure 5 The system 4300 shown includes a video encoder 4314. The video encoder 4400 can be configured to perform any or all embodiments of this disclosure. The video encoder 4400 includes multiple functional components. The embodiments described in this disclosure can be shared among various components of the video encoder 4400. In some examples, a processor can be configured to perform any or all embodiments described in this disclosure.

[0118] The functional components of the video encoder 4400 may include a segmentation unit 4401, a prediction unit 4402, a residual generation unit 4407, a transform unit 4408, a quantization unit 4409, an inverse quantization unit 4410, an inverse transform unit 4411, a reconstruction unit 4412, a buffer 4413, and an entropy coding unit 4414. The prediction unit 4402 may include a mode selection unit 4403, a motion estimation unit 4404, a motion compensation unit 4405, and an intra-frame prediction unit 4406.

[0119] In other examples, the video encoder 4400 may include more, fewer, or different functional components. In one example, the prediction unit 4402 may include an intra-block copy (IBC) unit. The IBC unit can perform prediction in an IBC mode, where at least one reference picture is the picture in which the current video block is located.

[0120] Furthermore, some components such as the motion estimation unit 4404 and the motion compensation unit 4405 can be highly integrated, but for illustrative purposes, they are shown separately in the example of the video encoder 4400.

[0121] The segmentation unit 4401 can segment an image into one or more video blocks. The video encoder 4400 and the video decoder 4500 can support various video block sizes.

[0122] The mode selection unit 4403 can select one of several encoding / decoding modes (intra-frame encoding / decoding or inter-frame encoding / decoding), for example, based on error results, and provide the resulting intra-frame or inter-frame encoded / decoded block to the residual generation unit 4407 to generate residual block data, and to the reconstruction unit 4412 to reconstruct the coded block for use as a reference image. In some examples, the mode selection unit 4403 can select an intra-frame / inter-frame joint prediction (CIIP) mode, where prediction is based on inter-frame prediction signals and intra-frame prediction signals. In the case of inter-frame prediction, the mode selection unit 4403 can also select a resolution for the block based on motion vectors (e.g., sub-pixel precision or integer pixel precision).

[0123] To perform inter-frame prediction on the current video block, motion estimation unit 4404 can generate motion information for the current video block by comparing one or more reference frames from buffer 4413 with the current video block. Motion compensation unit 4405 can determine the predicted video block for the current video block based on the motion information and decoded samples of images from buffer 4413 other than the image associated with the current video block.

[0124] The motion estimation unit 4404 and the motion compensation unit 4405 can perform different operations on the current video block, for example, depending on whether the current video block is in an I-band, P-band, or B-band.

[0125] In some examples, motion estimation unit 4404 can perform unidirectional prediction on the current video block, and can search for reference images in list 0 or list 1 to find a reference video block for the current video block. Motion estimation unit 4404 can then generate a reference index indicating the reference image containing the reference video block in list 0 or list 1, and a motion vector indicating the spatial displacement between the current video block and the reference video block. Motion estimation unit 4404 can output the reference index, prediction direction indicator, and motion vector as motion information for the current video block. Motion compensation unit 4405 can generate a predicted video block for the current block based on the reference video block indicated by the motion information of the current video block.

[0126] In other examples, motion estimation unit 4404 can perform bidirectional prediction on the current video block. Motion estimation unit 4404 can search for reference images in list 0 to find a reference video block for the current video block, and can also search for reference images in list 1 to find another reference video block for the current video block. Motion estimation unit 4404 can then generate reference indices indicating the reference images containing the reference video blocks in lists 0 and 1, and motion vectors indicating the spatial displacement between the reference video blocks and the current video block. Motion estimation unit 4404 can output the reference index and motion vector of the current video block as motion information for the current video block. Motion compensation unit 4405 can generate a predicted video block for the current video block based on the reference video blocks indicated by the motion information of the current video block.

[0127] In some examples, the motion estimation unit 4404 can output a complete set of motion information for use in the decoder's decoding process. In some examples, the motion estimation unit 4404 may not output a complete set of motion information for the current video. Instead, the motion estimation unit 4404 can reference the motion information of another video block to transmit the motion information of the current video block via a signal. For example, the motion estimation unit 4404 may determine that the motion information of the current video block is sufficiently similar to the motion information of neighboring video blocks.

[0128] In one example, the motion estimation unit 4404 may indicate a value to the video decoder 4500 in the syntax structure associated with the current video block, which indicates that the current video block has the same motion information as another video block.

[0129] In another example, motion estimation unit 4404 may identify another video block and motion vector difference (MVD) in the syntax structure associated with the current video block. The motion vector difference indicates the difference between the motion vector of the current video block and the motion vector of the indicated video block. Video decoder 4500 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.

[0130] As discussed above, the video encoder 4400 can transmit motion vectors via signaling in a predictive manner. Two examples of predictive signaling techniques that can be implemented by the video encoder 4400 include Advanced Motion Vector Prediction (AMVP) and Merge Pattern Signaling.

[0131] Intra-prediction unit 4406 can perform intra-prediction on the current video block. When intra-prediction unit 4406 performs intra-prediction on the current video block, it can generate prediction data for the current video block based on decoded samples from other video blocks in the same frame. The prediction data for the current video block can include the predicted video block and various syntax elements.

[0132] The residual generation unit 4407 can generate residual data for the current video block by subtracting (or more) predicted video blocks from the current video block. The residual data for the current video block may include residual video blocks corresponding to different sample components of the samples in the current video block.

[0133] In other examples, there may be no residual data for the current video block, such as in skip mode, and the residual generation unit 4407 may not perform subtraction operations.

[0134] The transform processing unit 4408 can generate one or more transform coefficient video blocks for the current video block by applying one or more transforms to the residual video blocks associated with the current video block.

[0135] After the transform processing unit 4408 generates a transform coefficient video block associated with the current video block, the quantization unit 4409 can 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.

[0136] The inverse quantization unit 4410 and the inverse transform unit 4411 can apply inverse quantization and inverse transform to the transform coefficient video block respectively to reconstruct the residual video block from the transform coefficient video block. The reconstruction unit 4412 can add the reconstructed residual video block to the corresponding samples of one or more predicted video blocks generated by the prediction unit 4402 to generate a reconstructed video block associated with the current block for storage in the buffer 4413.

[0137] After the video block is reconstructed by reconstruction unit 4412, a loop filtering operation can be performed to reduce video block artifacts in the video block.

[0138] Entropy encoding unit 4414 can receive data from other functional components of video encoder 4400. When entropy encoding unit 4414 receives data, it can perform one or more entropy encoding operations to generate entropy-encoded data and output a bitstream including the entropy-encoded data.

[0139] Figure 7 This is a block diagram illustrating an example of a video decoder 4500, which can be... Figure 5 The system 4300 shown includes a video decoder 4324. The video decoder 4500 can be configured to perform any or all embodiments of this disclosure. In the example shown, the video decoder 4500 includes multiple functional components. The embodiments described in this disclosure can be shared among various components of the video decoder 4500. In some examples, a processor can be configured to perform any or all embodiments described in this disclosure.

[0140] In the example shown, the video decoder 4500 includes an entropy decoding unit 4501, a motion compensation unit 4502, an intra-frame prediction unit 4503, an inverse quantization unit 4504, an inverse transform unit 4505, a reconstruction unit 4506, and a buffer 4507. In some examples, the video decoder 4500 can perform a decoding process that is generally the inverse of the encoding process described with respect to the video encoder 4400.

[0141] The entropy decoding unit 4501 can retrieve the encoded bitstream. The encoded bitstream may include entropy-encoded video data (e.g., encoded video data blocks). The entropy decoding unit 4501 can decode the entropy-encoded video data, and based on the entropy-decoded video data, the motion compensation unit 4502 can determine motion information including motion vectors, motion vector precision, reference image list index, and other motion information. The motion compensation unit 4502 can determine this information, for example, by executing AMVP and Merge modes.

[0142] The motion compensation unit 4502 can generate motion compensation blocks, possibly performing interpolation based on an interpolation filter. The identifier of the interpolation filter to be used, with sub-pixel accuracy, can be included in the syntax element.

[0143] The motion compensation unit 4502 can use the interpolation filter used by the video encoder 4400 during the encoding of a video block to calculate the interpolation for sub-integer pixels of the reference block. The motion compensation unit 4502 can determine the interpolation filter used by the video encoder 4400 based on the received syntax information, and the motion compensation unit 4502 can use the interpolation filter to generate a prediction block.

[0144] The motion compensation unit 4502 may use some syntax information to determine the size of the blocks of (multiple) frames and / or (multiple) stripes used to encode the encoded video sequence, segmentation information describing how each macroblock of the picture of the encoded video sequence is segmented, a mode indicating how each segment is encoded, one or more reference frames (and a list of reference frames) for each inter-frame codec block, and other information for decoding the encoded video sequence.

[0145] Intra-prediction unit 4503 can use, for example, an intra-prediction mode received in the bitstream to form prediction blocks from spatially adjacent blocks. Inverse quantization unit 4504 inverse quantizes (i.e., dequantizes) the quantized video block coefficients provided in the bitstream and decoded by entropy decoding unit 4501. Inverse transform unit 4505 applies the inverse transform.

[0146] The reconstruction unit 4506 can add the residual block to the corresponding predicted block generated by the motion compensation unit 4502 or the intra-frame prediction unit 4503 to form a decoded block. If necessary, a deblocking filter can also be applied to filter the decoded block to remove block artifacts. The decoded video block is then stored in a buffer 4507, which provides a reference block for subsequent motion compensation / intra-frame prediction and also generates decoded video for presentation on a display device.

[0147] Figure 8 This is a schematic diagram of an example encoder 4600. Encoder 4600 is suitable for implementing VVC techniques. Encoder 4600 includes three loop filters: a deblocking filter (DF) 4602, a sample adaptive compensation (SAO) 4604, and an adaptive loop filter (ALF) 4606. Unlike DF 4602, which uses predefined filters, SAO 4604 and ALF 4606 utilize the original samples of the current image, respectively, by adding an offset and by applying a finite impulse response (FIR) filter, and by utilizing the encoded / decoded side information through signal transmission offset and filter coefficients to reduce the mean square error between the original and reconstructed samples. ALF 4606 is located in the final processing stage of each image and can be considered as a tool for attempting to capture and repair artifacts caused by previous stages.

[0148] The encoder 4600 also includes an intra-frame prediction component 4608 and a motion estimation / compensation (ME / MC) component 4610 configured to receive input video. The intra-frame prediction component 4608 is configured to perform intra-frame prediction, while the ME / MC component 4610 is configured to perform inter-frame prediction using a reference image obtained from a reference image buffer 4612. Residual blocks from inter-frame or intra-frame prediction are fed into a transform (T) component 4614 and a quantization (Q) component 4616 to generate quantized residual transform coefficients, which are then fed into an entropy encoding / decoding component 4618. The entropy encoding / decoding component 4618 entropy-encodes and decodes the prediction results and quantized transform coefficients and transmits them toward a video decoder (not shown). The quantization component output from the quantization component 4616 can be fed into an inverse quantization (IQ) component 4620, an inverse transform component 4622, and a reconstruction (REC) component 4624. REC component 4624 is able to output images to DF 4602, SAO 4604 and ALF 4606 for filtering before these images are stored in reference image buffer 4612.

[0149] The following is a list of some preferred solutions.

[0150] 1. A method for processing media data, comprising: as part of a Region Adaptive Hierarchical Transformation (RAHT) operation, determining, based on the current node occupancy, to resample AC inter-frame predictions in a sample domain or mean attribute space to obtain sample domain DC predictions for child nodes; and performing a conversion between visual media data and a bitstream based on the RAHT operation.

[0151] 2. According to the method of Solution 1, wherein when a child node in the current node is not occupied, the corresponding inter-frame prediction signal of the child node is set to zero.

[0152] 3. The method according to any one of solutions 1-2, wherein when a child node in the current node is occupied, while the corresponding reference child node in the reference node is not occupied, the prediction of the child node is obtained by interpolation.

[0153] 4. The method according to any one of solutions 1-3, wherein the interpolation is: the parent DC of the reference child node; the parent DC of the current child node; a weighted sum of the parent DC of the current node and the parent DC of the reference node, including the average of the two parent DC values; obtained by first upsampling the weighted sum of the reconstructed nearest neighbors in the reference node in the mean attribute space, and then weighting by the square root of the current child node to obtain the DC prediction of the child node; obtained by upsampling the current node based on the reconstructed nearest neighbors in the mean attribute space, and then weighting by the square root of the current child node; obtained by jointly upsampling the reconstructed nearest neighbors in the reference node and the reconstructed nearest neighbors in the current node in the mean attribute space, and then weighting by the square root of the current child node; or completed in the mean attribute space, in which case the prediction is derived in the mean attribute space rather than in the sample domain.

[0154] 5. The method according to any one of solutions 1-4, wherein the determination is applied only to the last level of the RAHT node, which includes leaf-level nodes, to achieve point matching between voxels in the current frame and voxels in the reference frame.

[0155] 6. The method according to any one of solutions 1-5, wherein the occupancy matching process is applied to the 2x2x2 nodes in the last layer to establish the correspondence between the nodes.

[0156] 7. The method according to any one of solutions 1-6, wherein when multiple reference frames exist, the determination is applied to a subset of the reference frames.

[0157] 8. The method according to any one of solutions 1-7, wherein inter-frame prediction is obtained in the sample domain for the weight distribution of the current node, and wherein transform domain prediction is then obtained by applying a transform to the RAHT kernel for the current node.

[0158] 9. The method according to any one of solutions 1-8, wherein the determination is first applied to match the occupancy.

[0159] 10. The method according to any one of solutions 1-9, wherein the prediction is first obtained in the mean attribute space of the reference node, and the sample domain prediction or the DC child node prediction for the current node is obtained by inverse normalization by multiplying it by the square root of the weights of the weight distribution of the current node.

[0160] 11. The method according to any one of solutions 1-10, wherein the derivation process of the prediction in the mean attribute space of the reference node and the subsequent sample domain prediction for the current node is applicable only when both the current child node and the reference child node have non-zero weights.

[0161] 12. The method according to any one of solutions 1-11, wherein, given the DC of a corresponding child node in the reference node, the mean attribute prediction is obtained by multiplying by the inverse square root of the weight of the reference child node.

[0162] 13. The method according to any one of solutions 1-12, wherein, given the DC of the corresponding child node in the reference node, the mean attribute prediction is obtained by dividing by the square root of the weight of the reference child node.

[0163] 14. The method according to any one of solutions 1-13, wherein when the weight of the reference child node is 1, the multiplication or division in obtaining the mean attribute prediction is bypassed.

[0164] 15. The method according to any one of solutions 1-14, wherein when the weight of the current child node is 1, the inverse normalization of the DC prediction of the current child node obtained from the mean attribute prediction is skipped.

[0165] 16. The method according to any one of solutions 1-15, wherein the DC prediction of the child node is used unchanged when the weight of the child node of the current node is the same as the weight of the corresponding child node in the reference node.

[0166] 17. The method according to any one of solutions 1-16, wherein when multiple reference frames exist, the determination is applied to a subset of the reference frames, or the determination is applied only when both the current child node and the reference child node have non-zero weights.

[0167] 18. The method according to any one of solutions 1-17, wherein the determination is transmitted via signaling in a bit stream, parameter set, header, frame, slice, stripe, or octree.

[0168] 19. The method according to any one of solutions 1-18, wherein the determined application depends on encoding / decoding information including color format, color components, stripe type, or picture type.

[0169] 20. An apparatus for processing video data, comprising: a processor; and a non-transitory memory having instructions thereon, wherein the instructions, when executed by the processor, cause the processor to perform the method according to any one of solutions 1-19.

[0170] 21. A non-transitory computer-readable medium comprising a computer program product for use by a video codec device, the computer program product comprising computer-executable instructions stored on the non-transitory computer-readable medium such that, when executed by a processor, the video codec device performs the method according to any one of solutions 1-19.

[0171] 22. A non-transitory computer-readable recording medium for storing a bitstream of video, the bitstream being generated by a method performed by a video processing apparatus, wherein the method comprises: as part of a Region Adaptive Hierarchical Transform (RAHT) operation, determining, based on the occupancy of a current node, to resample an AC inter-frame prediction in a sample domain or a mean attribute space to obtain a sample domain DC prediction for a child node; and generating a bitstream based on the determination.

[0172] 23. A method for storing a bitstream of video, comprising: as part of a Region Adaptive Hierarchical Transform (RAHT) operation, determining, based on the occupancy of a current node, to resample an AC inter-frame prediction in a sample domain or mean attribute space to obtain a sample domain DC prediction for a child node; generating a bitstream based on the determination; and storing the bitstream in a non-transitory computer-readable recording medium.

[0173] 24. A method, apparatus or system described in this disclosure.

[0174] In the described solution, the encoder conforms to the format rules by generating a codec representation based on those rules. In the described solution, the decoder parses the syntax elements in the codec representation using known information about their presence or absence, based on the format rules, to produce the decoded video.

[0175] In this disclosure, the term "video processing" can refer to video encoding, video decoding, video compression, or video decompression. For example, a video compression algorithm can be applied during the conversion from a pixel representation of a video to a corresponding bitstream representation, and vice versa. For example, the bitstream representation of the current video block can correspond to bits at co-positions or propagated at different positions in the bitstream defined by the syntax. For example, a macroblock can be encoded based on the error residual value after transformation and encoding / decoding, and also using bits from the header and other fields in the bitstream. Furthermore, during the conversion, the decoder can, based on this determination, parse the bitstream knowing whether some fields may or may not be present, as described in the solutions above. Similarly, the encoder can determine whether to include or exclude specific syntax fields and generate the codec representation accordingly by including or excluding syntax fields from the codec representation.

[0176] The disclosed and other solutions, examples, embodiments, modules, and functional operations described herein can be implemented in digital electronic circuits, or in computer software, firmware, or hardware, including the structures disclosed herein and their structural equivalents, or in combinations thereof. The disclosed embodiments and other embodiments can be implemented as one or more computer program products, i.e., one or more computer program instruction modules encoded on a computer-readable medium for execution by or control of the operation of a data processing apparatus. The computer-readable medium can be a machine-readable storage device, a machine-readable storage substrate, a storage device, a material composition affecting machine-readable propagation signals, or a combination thereof. The term "data processing apparatus" includes all means, devices, and machines for processing data, including, for example, a programmable processor, a computer, or multiple processors or computers. In addition to hardware, the apparatus may also include code that creates an execution environment for an associated computer program, such as code constituting processor firmware, a protocol stack, a database management system, an operating system, or a combination thereof. Propagation signals are artificially generated signals, such as machine-generated electrical signals, optical signals, or electromagnetic signals, which are generated to encode information to be transmitted to a suitable receiver device.

[0177] Computer programs (also known as programs, software, software applications, scripts, or code) can be written in any programming language, including compiled or interpreted languages, and can be deployed in any form, including standalone programs or modules, components, subroutines, or other units suitable for use in a computing environment. A computer program does not necessarily correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the related program, or in multiple co-located files (e.g., a file storing one or more modules, subroutines, or code portions). A computer program can be deployed to execute on one computer or on multiple computers located at a single site or distributed across multiple sites and interconnected by a communications network.

[0178] The processing and logic flows described in this disclosure can be executed by one or more programmable processors that execute one or more computer programs to perform functions by manipulating input data and generating outputs. The processing and logic flows can also be executed by special-purpose logic circuitry, and the apparatus can be implemented as special-purpose logic circuitry, such as field-programmable gate arrays (FPGAs) or application-specific integrated circuits (ASICs).

[0179] Processors suitable for executing computer programs include, for example, general-purpose and special-purpose microprocessors, and any one or more processors of any type of digital computer. Typically, a processor receives instructions and data from read-only memory or random access memory, or both. The basic components of a computer are a processor that executes instructions and one or more storage devices that store the instructions and data. Typically, a computer will also include one or more mass storage devices for storing data, such as magnetic disks, magneto-optical disks, or optical disks, or receive data from or transfer data to one or more mass storage devices via operative coupling, or both. However, a computer does not necessarily have such devices. Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media, and storage devices, including, for example, semiconductor storage devices such as erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and flash memory devices; magnetic disks, such as internal hard disks or removable hard disks; magneto-optical disks; and optical disc read-only memory (CD ROM) and digital versatile disc read-only memory (DVD-ROM). Processors and memory may be supplemented by or incorporated into dedicated logic circuitry.

[0180] While this disclosure contains numerous details, these details should not be construed as limiting any subject matter or the scope of the claims, but rather as descriptions of features specific to particular embodiments of this disclosure. Certain features described in the context of individual embodiments in this disclosure may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented separately in multiple embodiments, or in any suitable sub-combination. Furthermore, although features may function in certain combinations as described above, and even were originally claimed in this manner, in some cases one or more features in a claimed combination may be removed from that combination, and the claimed combination may be for sub-combinations or variations thereof.

[0181] Similarly, although operations are depicted in a specific order in the accompanying drawings, this should not be construed as requiring such operations to be performed sequentially in the particular order or sequence shown, or requiring all shown operations to be performed in order to achieve the desired result. Furthermore, the partitioning of various system components in the embodiments described in this disclosure should not be construed as requiring such partitioning in all embodiments.

[0182] Only a few implementations and examples are described, and other implementations, improvements and variations may be made based on what is described and shown in this disclosure.

[0183] When there are no intermediate components other than a line, trace, or other medium between the first and second components, the first component is directly coupled to the second component. When there are intermediate components other than a line, trace, or other medium between the first and second components, the first component is indirectly coupled to the second component. The term "coupling" and its variations include direct coupling and indirect coupling. The use of the term "about" means including a range of ±10% of the following figures, unless otherwise specified.

[0184] While several embodiments have been provided in this disclosure, it should be understood that the disclosed systems and methods may be embodied in many other specific forms without departing from the spirit or scope of this disclosure. The present examples are to be considered illustrative rather than restrictive and are not intended to be limited to the details set forth herein. For example, various elements or components may be combined or integrated into another system, or certain features may be omitted or not implemented.

[0185] Furthermore, the technologies, systems, subsystems, and methods described and illustrated as discrete or separate in the various embodiments can be combined or integrated with other systems, modules, technologies, or methods without departing from the scope of this disclosure. Other items shown or discussed as couplings can be directly connected or indirectly coupled or communicated through some interface, device, or intermediate component, whether electrical, mechanical, or otherwise. Other examples of variations, substitutions, and modifications will be apparent to those skilled in the art and can be made without departing from the spirit and scope of this disclosure.

Claims

1. A method for processing media data, comprising: As part of the Region Adaptive Hierarchical Transformation (RAHT) operation, based on the current node occupancy, it is determined to resample the AC inter-frame prediction in the sample domain or mean attribute space to obtain the sample domain DC prediction of the child node. as well as The conversion between visual media data and bitstream is performed based on the RAHT operation.

2. The method according to claim 1, wherein, When a child node in the current node is not occupied, the inter-frame prediction signal corresponding to the child node is set to zero.

3. The method according to any one of claims 1-2, wherein when a child node in the current node is occupied, while the corresponding reference child node in the reference node is not occupied, the DC prediction of the child node is obtained by interpolation.

4. The method according to any one of claims 1-3, wherein, The interpolation is the parent DC of the reference child node.

5. The method according to any one of claims 1-4, wherein, The interpolation is: The parent DC of the current child node; The weighted sum of the parent DC of the current node and the parent DC of the reference node, including the average value of the two parent DC values; The DC prediction of the child node is obtained by first upsampling the weighted sum of the reconstructed nearest neighbors in the reference node in the mean attribute space, and then weighting it with the square root of the current child node; or by upsampling the current node based on the reconstructed nearest neighbors in the mean attribute space, and then weighting it with the square root of the current child node. The result is obtained by performing the joint upsampling process in the mean attribute space based on the weighted sum of the reconstructed nearest neighbors in the reference node and the reconstructed nearest neighbors in the current node, and then weighting it with the square root of the current child node. or The prediction is determined in the mean attribute space, in which case the prediction is derived in the mean attribute space, not in the sample domain.

6. The method according to any one of claims 1-5, wherein, The determination is applied only to the last level of RAHT nodes, including leaf-level nodes, to achieve point matching between voxels in the current frame and voxels in the reference frame.

7. The method according to any one of claims 1-6, wherein, The last layer uses an occupation matching process to establish the correspondence between the 2x2x2 nodes.

8. The method according to any one of claims 1-7, wherein, The determination is applied to a subset of multiple reference frames.

9. The method according to any one of claims 1-8, wherein, For the weight distribution of the current node, inter-frame prediction is obtained in the sample domain, and then transform domain prediction is obtained by applying a transform to the RAHT kernel for the current node.

10. The method according to any one of claims 1-9, wherein, The determination is first applied to match the occupancy.

11. The method according to any one of claims 1-10, wherein, First, the DC prediction of the child node is obtained in the mean attribute space of the reference node. Then, by multiplying it by the square root of the weight of the weight distribution of the current node and performing inverse normalization, the sample domain prediction or the DC child node prediction for the current node is obtained.

12. The method according to any one of claims 1-11, wherein, The prediction in the mean attribute space of the reference node and the subsequent derivation of the sample domain prediction for the current node are applicable only when both the current child node and the reference child node have non-zero weights.

13. The method according to any one of claims 1-12, wherein, Given the DC of the corresponding child node in the reference node, the prediction in the mean attribute space is obtained by multiplying it by the inverse square root of the weight of the reference child node.

14. The method according to any one of claims 1-13, wherein, Given the DC of the corresponding child node in the reference node, the prediction in the mean attribute space is obtained by dividing by the square root of the weight of the reference child node.

15. The method according to any one of claims 1-14, wherein, When the weight of the reference child node is 1, the multiplication or division of the prediction obtained in the mean attribute space is bypassed.

16. The method according to any one of claims 1-15, wherein, When the weight of the current child node is 1, the inverse normalization of the DC prediction of the current child node obtained from the prediction in the mean attribute space is skipped.

17. The method according to any one of claims 1-16, wherein, When the weight of the child node of the current node is the same as the weight of the corresponding child node in the reference node, the DC prediction of the child node is used unchanged.

18. The method according to any one of claims 1-17, wherein, The determination may be applied to a subset of multiple reference frames, or the determination may be applied only when both the current child node and the reference child node have non-zero weights.

19. The method according to any one of claims 1-18, wherein, Whether the determination is applied in bitstream, parameter set, header, frame, slice, strip, or octree is transmitted via signal.

20. The method according to any one of claims 1-19, wherein, The determined application depends on encoding and decoding information including color format, color components, stripe type, image type, or a combination thereof.

21. The method according to any one of claims 1-20, wherein, The determination is enabled or disabled by transmitting a signal flag.

22. The method according to any one of claims 1-21, wherein, The conversion includes encoding the visual media data into the bitstream.

23. The method according to any one of claims 1-21, wherein, The conversion includes decoding the visual media data from the bitstream.

24. An apparatus for processing video data, comprising: processor; and a non-transitory memory thereon having instructions, wherein the instructions, when executed by the processor, cause the processor to perform the method according to any one of claims 1-23.

25. A non-transitory computer-readable medium comprising a computer program product for use by a video codec apparatus, the computer program product comprising computer-executable instructions stored on the non-transitory computer-readable medium such that, when executed by a processor, the video codec apparatus performs the method according to any one of claims 1-23.

26. A non-transitory computer-readable recording medium for storing a bitstream of video, the bitstream being generated by a method performed by a video processing apparatus, wherein the method comprises: As part of the Region Adaptive Hierarchical Transformation (RAHT) operation, based on the current node occupancy, it is determined to resample the AC inter-frame prediction in the sample domain or mean attribute space to obtain the sample domain DC prediction of the child node. as well as Based on the determination, a bit stream is generated.

27. A method for storing a bitstream of video, comprising: As part of the Region Adaptive Hierarchical Transformation (RAHT) operation, based on the current node occupancy, it is determined to resample the AC inter-frame prediction in the sample domain or mean attribute space to obtain the sample domain DC prediction of the child node. Based on the determination, a bit stream is generated; as well as The bit stream is stored in a non-transitory computer-readable recording medium.

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