Attribute information decoding method and apparatus, attribute information coding method and apparatus, and device

Abstract

The present application belongs to the technical field of communications. Disclosed are an attribute information decoding method and apparatus, an attribute information coding method and apparatus, and a device. The decoding method comprises: decoding and dequantizing data to be decoded to obtain reconstruction transform coefficients corresponding to each node, the reconstruction transform coefficients comprising: a first reconstruction transform coefficient corresponding to a luma component, a second reconstruction residual transform coefficient corresponding to a first chroma component, and a third reconstruction residual transform coefficient corresponding to a second chroma component; on the basis of the first reconstruction transform coefficient and the second reconstruction residual transform coefficient, determining a second reconstruction transform coefficient; and performing at least one of the following: on the basis of the second reconstruction transform coefficient and the third reconstruction residual transform coefficient, determining a third reconstruction transform coefficient corresponding to the second chroma component; on the basis of the first reconstruction transform coefficient and the third reconstruction residual transform coefficient, determining the third reconstruction transform coefficient; and, on the basis of the first reconstruction transform coefficient, the second reconstruction transform coefficient, and the third reconstruction residual transform coefficient, determining the third reconstruction transform coefficient.

Description

Decoding and encoding methods, devices and equipment for attribute information

[0001] Cross-references to related applications

[0002] This application claims priority to Chinese Patent Application No. 202411522915.9, filed in China on October 29, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application belongs to the field of communication technology, and specifically relates to a method, apparatus and device for decoding and encoding attribute information. Background Technology

[0004] In the Geometry-based Point Cloud Compression (G-PCC) encoder framework, the geometric and attribute information of the point cloud are encoded separately. Currently, G-PCC attribute encoding can be divided into Region Adaptive Harm Transform (RAHT) based on upsampling prediction and Lift Transform based on hierarchical structure partitioning. In RAHT, the attribute information across multiple channels may exhibit strong correlations. Current lossy color attribute encoding in G-PCC uses the YCbCr component format, where Y represents the luma component, and Cb and Cr represent the chroma components. Current G-PCC RAHT attribute encoding requires encoding each component separately, resulting in a complex encoding process and low encoding efficiency. Summary of the Invention

[0005] This application provides a method, apparatus, and device for decoding and encoding attribute information, which can solve the problem of low encoding efficiency.

[0006] Firstly, a method for decoding attribute information is provided, executed by the decoding end, the method comprising:

[0007] The decoding end decodes and dequantizes the data to be decoded to obtain the reconstruction transform coefficients corresponding to each node; the reconstruction transform coefficients are the reconstruction transform coefficients of the transform coefficients corresponding to the attribute information of each node; the reconstruction transform coefficients include: the first reconstruction transform coefficient corresponding to the luminance component of the transform coefficient, the second reconstruction residual transform coefficient corresponding to the first chrominance component of the transform coefficient, and the third reconstruction residual transform coefficient corresponding to the second chrominance component of the transform coefficient.

[0008] The decoding end determines the second reconstruction transformation coefficient corresponding to the first chromaticity component based on the first reconstruction transformation coefficient and the second reconstruction residual transformation coefficient;

[0009] The decoding end performs at least one of the following:

[0010] Based on the second reconstruction transformation coefficient and the third reconstruction residual transformation coefficient, determine the third reconstruction transformation coefficient corresponding to the second chromaticity component;

[0011] Based on the first reconstruction transformation coefficient and the third reconstruction residual transformation coefficient, determine the third reconstruction transformation coefficient corresponding to the second chromaticity component;

[0012] The third reconstruction transformation coefficient corresponding to the second chromaticity component is determined based on the first reconstruction transformation coefficient, the second reconstruction transformation coefficient, and the third reconstruction residual transformation coefficient.

[0013] Secondly, a method for encoding attribute information is provided, executed by the encoding end, the method including:

[0014] The encoding end performs Region Adaptive Hierarchical Transformation (RAHT) on each node to obtain the transformation coefficients corresponding to the attribute information of each node; the transformation coefficients include: luminance component, first chrominance component and second chrominance component;

[0015] The encoding end uses the first reconstruction transform coefficients corresponding to the luminance component to predict and encode the first chrominance component, thereby obtaining the second residual transform coefficients corresponding to the first chrominance component.

[0016] Based on the first reconstruction transform coefficient and the second residual transform coefficient, determine the second reconstruction transform coefficient corresponding to the first chromaticity component;

[0017] The encoding end performs at least one of the following:

[0018] The second chromaticity component is predicted and encoded using the second reconstruction transform coefficients to obtain the third residual transform coefficients corresponding to the second chromaticity component.

[0019] The second chromaticity component is predicted and encoded using the first reconstruction transform coefficients to obtain the third residual transform coefficients corresponding to the second chromaticity component.

[0020] The second chromaticity component is predicted and encoded using the first reconstruction transform coefficients to obtain the first residual value of the third residual transform coefficients corresponding to the second chromaticity component; the first residual value is predicted and encoded using the second reconstruction transform coefficients to obtain the third residual transform coefficients.

[0021] Thirdly, a decoding device for attribute information is provided, applied at a decoding end, the device comprising:

[0022] The first decoding module is used to decode and dequantize the data to be decoded to obtain the reconstruction transform coefficients corresponding to each node; the reconstruction transform coefficients are the reconstruction transform coefficients of the transform coefficients corresponding to the attribute information of each node; the reconstruction transform coefficients include: the first reconstruction transform coefficient corresponding to the luminance component of the transform coefficient, the second reconstruction residual transform coefficient corresponding to the first chrominance component of the transform coefficient, and the third reconstruction residual transform coefficient corresponding to the second chrominance component of the transform coefficient.

[0023] The first determining module is used to determine the second reconstruction transformation coefficient corresponding to the first chromaticity component based on the first reconstruction transformation coefficient and the second reconstruction residual transformation coefficient.

[0024] A first processing module is configured to perform at least one of the following at the decoding end:

[0025] Based on the second reconstruction transformation coefficient and the third reconstruction residual transformation coefficient, determine the third reconstruction transformation coefficient corresponding to the second chromaticity component;

[0026] Based on the first reconstruction transformation coefficient and the third reconstruction residual transformation coefficient, determine the third reconstruction transformation coefficient corresponding to the second chromaticity component;

[0027] The third reconstruction transformation coefficient corresponding to the second chromaticity component is determined based on the first reconstruction transformation coefficient, the second reconstruction transformation coefficient, and the third reconstruction residual transformation coefficient.

[0028] Fourthly, an attribute information encoding device is provided, applied at the encoding end, the device comprising:

[0029] The transformation module is used to perform Region Adaptive Hierarchical Transformation (RAHT) on each node to obtain the transformation coefficients corresponding to the attribute information of each node; the transformation coefficients include: luminance component, first chrominance component and second chrominance component;

[0030] The first encoding module is used to predict and encode the first chromaticity component using the first reconstruction transform coefficients corresponding to the luminance component, and obtain the second residual transform coefficients corresponding to the first chromaticity component.

[0031] The third determining module is used to determine the second reconstruction transform coefficient corresponding to the first chromaticity component based on the first reconstruction transform coefficient and the second residual transform coefficient.

[0032] The second processing module is configured to perform at least one of the following:

[0033] The second chromaticity component is predicted and encoded using the second reconstruction transform coefficients to obtain the third residual transform coefficients corresponding to the second chromaticity component.

[0034] The second chromaticity component is predicted and encoded using the first reconstruction transform coefficients to obtain the third residual transform coefficients corresponding to the second chromaticity component.

[0035] The second chromaticity component is predicted and encoded using the first reconstruction transform coefficients to obtain the first residual value of the third residual transform coefficients corresponding to the second chromaticity component; the first residual value is predicted and encoded using the second reconstruction transform coefficients to obtain the third residual transform coefficients.

[0036] Fifthly, an electronic device is provided, the terminal including a processor and a memory, the memory storing a program or instructions executable on the processor, the program or instructions, when executed by the processor, implementing the steps of the method as described in the first aspect, or implementing the steps of the method as described in the second aspect.

[0037] In a sixth aspect, an electronic device is provided, including a processor and a communication interface, wherein, when the electronic device is a decoding end device, the processor is configured to: decode and dequantize the data to be decoded to obtain reconstruction transform coefficients corresponding to each node; the reconstruction transform coefficients are reconstruction transform coefficients of transform coefficients corresponding to the attribute information of each node; the reconstruction transform coefficients include: a first reconstruction transform coefficient corresponding to the luminance component of the transform coefficient, a second reconstruction residual transform coefficient corresponding to the first chrominance component of the transform coefficient, and a third reconstruction residual transform coefficient corresponding to the second chrominance component of the transform coefficient; determine a second reconstruction transform coefficient corresponding to the first chrominance component based on the first reconstruction transform coefficient and the second reconstruction residual transform coefficient; and perform at least one of the following: determine a third reconstruction transform coefficient corresponding to the second chrominance component based on the second reconstruction transform coefficient and the third reconstruction residual transform coefficient; determine a third reconstruction transform coefficient corresponding to the second chrominance component based on the first reconstruction transform coefficient and the third reconstruction residual transform coefficient; and determine a third reconstruction transform coefficient corresponding to the second chrominance component based on the first reconstruction transform coefficient, the second reconstruction transform coefficient, and the third reconstruction residual transform coefficient.

[0038] Alternatively, when the electronic device is an encoding end device, the processor is configured to: perform Region Adaptive Hierarchical Transformation (RAHT) on each node to obtain transformation coefficients corresponding to the attribute information of each node; the transformation coefficients include: a luminance component, a first chrominance component, and a second chrominance component; use the first reconstructed transformation coefficients corresponding to the luminance component to perform predictive coding on the first chrominance component to obtain a second residual transformation coefficient corresponding to the first chrominance component; determine the second reconstructed transformation coefficients corresponding to the first chrominance component based on the first reconstructed transformation coefficients and the second residual transformation coefficients; perform at least one of the following: use the second reconstructed transformation coefficients to perform predictive coding on the second chrominance component to obtain a third residual transformation coefficient corresponding to the second chrominance component; use the first reconstructed transformation coefficients to perform predictive coding on the second chrominance component to obtain a third residual transformation coefficient corresponding to the second chrominance component; use the first reconstructed transformation coefficients to perform predictive coding on the second chrominance component to obtain a first residual value of the third residual transformation coefficient corresponding to the second chrominance component; use the second reconstructed transformation coefficients to perform predictive coding on the first residual value to obtain a third residual transformation coefficient.

[0039] A seventh aspect provides an electronic device comprising: a memory configured to store video data, and processing circuitry configured to implement the steps of the method described in the first aspect, or the steps of the method described in the second aspect.

[0040] Eighthly, a readable storage medium is provided, on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect, or implement the steps of the method described in the second aspect.

[0041] A ninth aspect provides an encoding / decoding system, comprising: an encoding end device and a decoding end device, wherein the encoding end device is configured to perform the steps of the method described in the second aspect, and the decoding end device is configured to perform the steps of the method described in the first aspect.

[0042] In a tenth aspect, a chip is provided, the chip including a processor and a communication interface coupled to the processor, the processor being configured to run a program or instructions to implement the steps of the method described in the first aspect, or to implement the steps of the method described in the second aspect.

[0043] Eleventhly, a computer program / program product is provided, which is stored in a storage medium and is executed by at least one processor to implement the steps of the method as described in the first aspect, or to implement the steps of the method as described in the second aspect.

[0044] In a twelfth aspect, a computer program product is provided, including computer instructions that, when executed by a processor, implement the steps of the method as described in the first aspect, or implement the steps of the method as described in the second aspect.

[0045] In this embodiment, the decoding end determines the reconstruction information of each attribute component based on the correlation between the various attribute components of the node. Specifically, based on the correlation between the luminance component and the first chrominance component, the reconstruction information of the first chrominance component is determined using the first reconstruction transform coefficient of the luminance component and the second reconstruction residual transform coefficient of the first chrominance component; the reconstruction information corresponding to the second chrominance component is determined based on the correlation between the luminance component and the second chrominance component, or based on the correlation between the first chrominance component and the second chrominance component. By considering the correlation between different components when reconstructing the attribute information of the node, the decoding end effectively reduces the bit rate and improves decoding efficiency. Attached Figure Description

[0046] Figure 1 is a schematic diagram of the encoding and decoding system provided in an embodiment of this application;

[0047] Figure 2a is a flowchart of the encoding process performed by an encoder based on the AVS-PCC encoding framework;

[0048] Figure 2b is a flowchart of the encoding process performed by the encoder based on the MPEG G-PCC encoding framework;

[0049] Figure 3a is a flowchart of the decoding process performed by the decoder based on the AVS-PCC decoding framework;

[0050] Figure 3b is a flowchart of the decoding process performed by the decoder based on the MPEG G-PCC decoding framework;

[0051] Figure 4 is a flowchart illustrating the method for decoding attribute information according to an embodiment of this application;

[0052] Figure 5 is a flowchart illustrating the method for encoding attribute information according to an embodiment of this application;

[0053] Figure 6 is a schematic diagram of the structure of the attribute information decoding device according to an embodiment of this application;

[0054] Figure 7 is a schematic diagram of the structure of the attribute information encoding device according to an embodiment of this application;

[0055] Figure 8 is a schematic diagram of the structure of an electronic device according to an embodiment of this application;

[0056] Figure 9 is a schematic diagram of the terminal structure according to an embodiment of this application. Detailed Implementation

[0057] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0058] The terms "first," "second," etc., used in this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of the same class, without limiting the number of objects; for example, the first object can be one or more. Furthermore, "or" in this application indicates at least one of the connected objects. For example, "A or B" covers three scenarios: Scenario 1: including A but not B; Scenario 2: including B but not A; Scenario 3: including both A and B. The character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0059] Before introducing the technical solutions provided in the embodiments of this application, the meanings of some terms will be explained first.

[0060] Point cloud: A point cloud is a set of discrete points in space that are randomly distributed and represent the spatial structure and surface properties of a three-dimensional object or scene. Point clouds can be classified into different categories according to different classification criteria. For example, according to the method of acquiring the point cloud, it can be divided into dense point clouds and sparse point clouds; or according to the temporal type of the point cloud, it can be divided into static point clouds and dynamic point clouds.

[0061] Point cloud data: Point cloud data is composed of the geometric coordinates and attribute information of each point. Geometric coordinate information, also known as 3D position information, refers to the spatial coordinates (x, y, z) of a point in the point cloud. This can include the coordinate values ​​of the point along each coordinate axis of a 3D coordinate system, such as the coordinate value x along the X-axis, the coordinate value y along the Y-axis, and the coordinate value z along the Z-axis. The attribute information of a point in the point cloud can include at least one of the following: color information, material information, and laser reflection intensity information (also known as reflectivity). Typically, each point in the point cloud has the same number of attribute information. For example, each point in the point cloud can have both color information and laser reflection intensity information, or it can have color information, material information, and laser reflection intensity information.

[0062] Point cloud compression (PCC) refers to the process of encoding the geometric coordinates and attribute information of each point in a point cloud to obtain a compressed bitstream. Point cloud compression includes two main processes: geometric coordinate information encoding and attribute information encoding. Currently, point cloud compression frameworks that can compress point clouds include the Geometry Point Cloud Compression (G-PCC) or Video Point Cloud Compression (V-PCC) framework provided by the Moving Picture Experts Group (MPEG), or the AVS-PCC framework provided by the Audio Video Standard (AVS).

[0063] Point cloud decoding: Point cloud decoding refers to decoding the compressed bitstream obtained from point cloud encoding to reconstruct the point cloud. More specifically, it refers to the process of reconstructing the geometric coordinates and attribute information of each point in the point cloud based on the geometric bitstream and attribute bitstream in the compressed bitstream. After obtaining the compressed bitstream at the decoding end, for the geometric bitstream, entropy decoding is first performed to obtain the quantized information of each point in the point cloud, and then inverse quantization is performed to reconstruct the geometric coordinates of each point in the point cloud. For the attribute bitstream, entropy decoding is first performed to obtain the quantized attribute residual information or quantized transform coefficients of each point in the point cloud; then, inverse quantization is performed on the quantized attribute residual information to obtain the reconstructed residual information, and inverse quantization is performed on the quantized transform coefficients to obtain the reconstructed transform coefficients. The reconstructed transform coefficients are then inversely transformed to obtain the reconstructed residual information. Based on the reconstructed residual information of each point in the point cloud, the attribute information of each point in the point cloud can be reconstructed. The reconstructed attribute information of each point in the point cloud is then matched one-to-one with the reconstructed geometric coordinate information in sequence to reconstruct the point cloud.

[0064] Figure 1 is a schematic diagram of the encoding / decoding system 10 provided in an embodiment of this application. The technical solution of this application embodiment relates to encoding / decoding (CODEC) point cloud data (including encoding or decoding).

[0065] As shown in Figure 1, the encoding / decoding system 10 includes a source device 100, which provides encoded point cloud data to be decoded and displayed by the destination device 110. Specifically, the source device 100 provides the point cloud data to the destination device 110 via a communication medium 120. The source device 100 and the destination device 110 may include any one or more of the following: desktop computer, laptop computer, tablet computer, set-top box, mobile phone, wearable device (e.g., smartwatch or wearable camera), television, camera, display device, in-vehicle device, virtual reality (VR) device, augmented reality (AR) device, mixed reality (MR) device, digital media player, video game console, video conferencing equipment, video streaming equipment, broadcast receiver equipment, broadcast transmitter equipment, spacecraft, aircraft, robot, satellite, etc.

[0066] In the example of Figure 1, source device 100 includes a data source 101, a memory 102, an encoder 200, and an output interface 104. Destination device 110 includes an input interface 111, a decoder 300, a memory 113, and a display device 114. Source device 100 represents an example of an encoding device, while destination device 110 represents an example of a decoding device. In other examples, source device 100 and destination device 110 may not include some of the components shown in Figure 1, or they may include components other than those shown in Figure 1. For example, source device 100 may acquire point cloud data through an external capture device. Similarly, destination device 110 may interface with an external display device instead of including an integrated display device. Furthermore, memory 102 and memory 113 may be external memories.

[0067] Although Figure 1 illustrates the source device 100 and the destination device 110 as separate devices, in some examples, they may be integrated into a single device. In such embodiments, the same hardware or software, separate hardware or software, or any combination thereof may be used to implement the functionality corresponding to the source device 100 and the functionality corresponding to the destination device 110.

[0068] In some examples, source device 100 and destination device 110 can perform unidirectional or bidirectional data transmission. In the case of bidirectional data transmission, source device 100 and destination device 110 can operate in a substantially symmetrical manner, i.e., each of source device 100 and destination device 110 includes an encoder and a decoder.

[0069] Data source 101 represents the source of point cloud data (i.e., raw, unencoded point cloud data) and provides the point cloud data to encoder 200, which encodes the point cloud data. Source device 100 may include capture devices (e.g., camera devices, sensing devices, or scanning devices), archives containing previously captured point cloud data, or feed interfaces for receiving point cloud data from data content providers. Camera devices may include ordinary cameras, stereo cameras, and light field cameras; sensing devices may include laser devices, radar devices, etc.; and scanning devices may include 3D laser scanning devices, etc. Point cloud data can be obtained by capturing real-world visual scenes using capture devices. Alternatively, data source 101 may generate computer graphics-based data as source data, or combine real-time data, archived data, and computer-generated data. For example, the data source may generate point cloud data based on virtual objects (e.g., virtual 3D objects and virtual 3D scenes obtained through 3D modeling).

[0070] Encoder 200 encodes captured, pre-captured, or computer-generated data. Encoder 200 can rearrange point cloud data from the received order (sometimes referred to as the "display order") according to the encoded order. Encoder 200 can generate a bitstream including the encoded point cloud data. Source device 100 can then output the encoded point cloud data to communication medium 120 via output interface 104 for reception or retrieval, for example, by input interface 111 of destination device 110.

[0071] The memory 102 of the source device 100 and the memory 113 of the destination device 110 represent general-purpose memory. In some examples, memory 102 may store raw data from data source 101, and memory 113 may store decoded point cloud data from decoder 300. Additionally or alternatively, memories 102 and 113 may respectively store software instructions executable by, for example, encoder 200 and decoder 300. Although memories 102 and 113 are shown separately from encoder 200 and decoder 300 in this example, it should be understood that encoder 200 and decoder 300 may also include internal memory for functionally similar or equivalent purposes. If encoder 200 and decoder 300 are deployed on the same hardware device, memories 102 and 113 may be the same memory. Furthermore, memories 102 and 113 may store, for example, encoded point cloud data output from encoder 200 and input to decoder 300. In some examples, portions of memories 102 and 113 may be allocated as one or more point cloud buffers, for example, to store raw, decoded, or encoded point cloud data.

[0072] In some examples, source device 100 can output encoded data from output interface 104 to memory 113. Similarly, destination device 110 can access encoded data from memory 113 via input interface 111. Memory 113 or memory 102 can include any of a variety of distributed or locally accessed data storage media, such as hard drives, Blu-ray discs, digital versatile discs (DVDs), compact disc read-only memory (CD-ROMs), flash memory, volatile or non-volatile memory, or any other suitable digital storage medium for storing encoded point cloud data.

[0073] Output interface 104 may include any type of medium or device capable of transmitting encoded point cloud data from source device 100 to destination device 110. For example, output interface 104 may include a transmitter or transceiver, such as an antenna, configured to transmit encoded point cloud data directly from source device 100 to destination device 110 in real time. The encoded point cloud data may be modulated according to the communication standards of a wireless communication protocol and transmitted to destination device 110.

[0074] Communication medium 120 may include transient media, such as wireless broadcasting or wired network transmission. For example, communication medium 120 may include radio frequency (RF) spectrum or one or more physical transmission lines (e.g., cables). Communication medium 120 may form part of a packet-based network (such as a local area network, a wide area network, or a global network such as the Internet). Communication medium 120 may also take the form of a storage medium (e.g., a non-transitory storage medium), such as a hard disk, flash drive, compact disk, digital point cloud disk, Blu-ray disc, volatile or non-volatile memory, or any other suitable digital storage medium for storing encoded point cloud data.

[0075] In some implementations, the communication medium 120 may include a router, switch, base station, or any other device that can be used to facilitate communication from source device 100 to destination device 110. For example, a server (not shown) may receive encoded point cloud data from source device 100 and provide it to destination device 110, for example, via network transmission. The server may include (e.g., a web server for a website), a server configured to provide file transfer protocol services (such as File Transfer Protocol (FTP) or File Delivery Over Unidirectional Transport (FLUTE) protocol), a content delivery network (CDN) device, a Hypertext Transfer Protocol (HTTP) server, a Multimedia Broadcast Multicast Services (MBMS) or Evolved Multimedia Broadcast Multicast Service (eMBMS) server, or a Network-attached storage (NAS) device, etc. The server can implement one or more HTTP streaming protocols, such as MPEG Media Transport (MMT), Dynamic Adaptive Streaming over HTTP (DASH), HTTP Live Streaming (HLS), or Real Time Streaming Protocol (RTSP).

[0076] Destination device 110 can access encoded point cloud data from a server, for example via a wireless channel (e.g., a wireless Fidelity (WIFI) connection) or a wired connection (e.g., a digital subscriber line (DSL), cable modem, etc.) for accessing encoded point cloud data stored on the server.

[0077] Output interface 104 and input interface 111 can represent a wireless transmitter / receiver, a modem, a wired networking component (e.g., an Ethernet card), a wireless communication component operating according to the IEEE 802.11 or IEEE 802.15 standard (e.g., ZigBee™), Bluetooth standard, or other physical components. In an example where output interface 104 and input interface 111 include wireless components, output interface 104 and input interface 111 can be configured to transmit data, such as encoded point cloud data, via Wi-Fi, Ethernet, cellular networks (such as 4G, LTE, LTE-Advanced, 5G, 6G, etc.).

[0078] The technology provided in this application can be applied to support one or more of the following application scenarios: machine-perceived point clouds, which can be used in autonomous navigation systems, real-time inspection systems, geographic information systems, visual sorting robots, disaster relief robots, and other scenarios; human-perceived point clouds, which can be used in point cloud application scenarios such as digital cultural heritage, free-viewpoint broadcasting, 3D immersive communication, and 3D immersive interaction.

[0079] The input interface 111 of the destination device 110 receives an encoded bitstream from the communication medium 120. The encoded bitstream may include high-level syntax elements and encoded data units (e.g., sequences, image groups, images, slices, blocks, etc.), where the high-level syntax elements are used to decode the encoded data units to obtain decoded point cloud data. The display device 114 displays the decoded point cloud data to the user. The display device 114 may include a cathode ray tube (CRT), a liquid crystal display (LCD), a plasma display, an organic light-emitting diode (OLED) display, or other types of display devices. In some examples, the destination device 110 may not have a display device 114; for example, if the decoded point cloud data is used to determine the location of a physical object, the display device 114 may be replaced by a processor.

[0080] The encoder 200 and decoder 300 can be implemented as one or more of various processing circuits, which may include microprocessors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), discrete logic, hardware, or any combination thereof. When the technology is implemented wholly or partially in software, the device may store instructions for the software in a suitable non-transitory computer-readable storage medium and use one or more processors to execute the instructions in hardware to perform the technology provided in the embodiments of this application.

[0081] The basic principles of the encoder 200 and decoder 300 provided in this application embodiment are introduced below, taking the G-PCC and AVS-PCC codec frameworks as examples.

[0082] The encoding and decoding frameworks of G-PCC and AVS-PCC are largely the same. Figure 2a shows the encoding flowchart executed by the encoder based on the AVS-PCC encoding framework, and Figure 2b shows the encoding flowchart executed by the encoder based on the MPEG G-PCC encoding framework. The encoder mentioned above can be the encoder 200 shown in Figure 1. The above encoding frameworks can generally be divided into a geometric coordinate information encoding process and an attribute information encoding process. In the geometric information encoding process, the geometric coordinate information of each point in the point cloud is encoded to obtain a geometric bitstream; in the attribute information encoding process, the attribute information of each point in the point cloud is encoded to obtain an attribute bitstream; the geometric bitstream and the attribute bitstream together constitute the compressed bitstream of the point cloud.

[0083] For the geometric information encoding process, the encoding flow executed by encoder 200 is as follows:

[0084] 1. Pre-processing: This can include coordinate transformation and voxelization. Through scaling and translation operations, pre-processing converts the point cloud data in 3D space into integer form and moves its smallest geometric position to the origin. In some examples, encoder 200 may not perform pre-processing.

[0085] 2. Geometric Coding: For the AVS-PCC coding framework, geometric coding includes two modes: octree-based geometric coding and prediction tree-based geometric coding. For the G-PCC coding framework, geometric coding includes three modes: octree-based geometric coding, trisoup-based geometric coding, and prediction tree-based prediction coding. Among them:

[0086] Geometric coding based on multi-way trees, such as geometric coding based on octrees: An octree is a tree-like data structure that uniformly divides a predefined bounding box in three-dimensional space, with each node having eight child nodes. By using "1" and "0" to indicate whether each child node of the octree is occupied, occupancy code information is obtained as the code stream of point cloud geometric information.

[0087] Geometric coding based on prediction trees: A prediction tree is generated using a prediction strategy. Starting from the root node of the prediction tree, each node is traversed, and the residual coordinate value corresponding to each traversed node is encoded.

[0088] Geometric encoding based on triangulation: The point cloud is divided into blocks of a certain size, and the intersection points (called vertices) of the point cloud surface with the edges of the blocks are located. Geometric information is compressed by encoding whether there are intersection points on the edges of the blocks and the positions of the intersection points.

[0089] 3. Geometric Entropy Encoding: This method uses statistical compression encoding to encode the occupancy code information of the multi-way tree, the prediction residual information of the prediction tree, and the vertex information of the triangular representation, finally outputting a binary (0 or 1) compressed bitstream. Statistical coding is a lossless coding method that can effectively reduce the bit rate required to represent the same signal. A commonly used statistical coding method is Content Adaptive Binary Arithmetic Coding (CABAC).

[0090] 4. Geometric Reconstruction: Decoding and reconstructing the geometric information after geometric encoding.

[0091] For the attribute information encoding process, the encoding flow executed by encoder 200 is as follows:

[0092] 1. Color Transformation: Apply transformations to change the color information of an attribute to a different domain. For example, color information can be transformed from the RGB color space to the YCbCr color space.

[0093] 2. Attribute Recoloring: In lossy encoding, after encoding the geometric coordinate information, the encoding end needs to decode and reconstruct the geometric information, that is, restore the geometric information of each point in the point cloud. Attribute information corresponding to one or more neighboring points in the original point cloud is used as the attribute information for the reconstructed point.

[0094] In some examples, encoder 200 may not perform color transformation or attribute recoloring.

[0095] 3. Attribute information processing: In AVS-PCC, attribute information processing can include three modes: prediction coding, transformation coding, and prediction & transformation coding. These three coding modes can be used under different conditions.

[0096] Predictive coding refers to determining the neighboring points of the point to be coded as prediction points among the already coded points based on information such as distance or spatial relationships. Based on set criteria, the predicted attribute information of the point to be coded is calculated according to the attribute information of the prediction points. The difference between the actual attribute information and the predicted attribute information of the point to be coded is calculated as attribute residual information. This attribute residual information is then quantized, transformed (optional), and entropy encoded.

[0097] Transform coding refers to using transformation methods such as Discrete Cosine Transform (DCT) and Haar Transform (Haar) to group and transform attribute information, quantize the transformation coefficients, obtain attribute reconstruction information through inverse quantization and inverse transformation, calculate the difference between the real attribute information and the attribute reconstruction information to obtain attribute residual information and quantize it, and then entropy-encode the quantized transformation coefficients and attribute residuals.

[0098] Predictive transform coding refers to using the attribute residual information obtained from prediction to perform transformation, and then quantizing and entropy coding the transform coefficients.

[0099] In MPEG G-PCC, attribute information processing can include three modes: Prediction Transform coding, Lifting Transform coding, and Region Adaptive Hierarchical Transform (RAHT) coding. These three coding modes can be used under different conditions.

[0100] Predictive transform coding refers to dividing the point cloud into multiple different levels of detail (LoD) based on distance-selected subsets of points, achieving a multi-quality, hierarchical point cloud representation from coarse to fine. Bottom-up prediction is possible between adjacent layers, where neighboring points in the coarse layer predict the attribute information of points introduced in the fine layer, obtaining the corresponding attribute residual information. The points at the lowest level are encoded as reference information.

[0101] Lift transform coding refers to introducing a weight update strategy for neighboring points on the basis of LoD neighboring layer prediction, and finally obtaining the predicted attribute information of each point and the corresponding attribute residual information.

[0102] Hierarchical region adaptive transform coding refers to the process of transforming attribute information into the transform domain, which is called the transform coefficient.

[0103] 4. Attribute Quantization: The fineness of quantization is usually determined by the quantization parameters. The transformation coefficients or attribute residuals obtained from attribute information processing are quantized, and the quantized results are entropy-coded. For example, in predictive transform coding and boost transform coding, entropy coding is performed on the quantized attribute residuals; in RAHT, entropy coding is performed on the quantized transform coefficients.

[0104] 5. Entropy Coding: The quantized attribute residual information and / or transform coefficients are generally compressed using run-length coding and arithmetic coding. The corresponding coding mode, quantization parameters, and other information are also encoded using an entropy encoder.

[0105] The encoder 200 encodes the geometric coordinate information of each point in the point cloud to obtain a geometric bitstream, and encodes the attribute information of each point in the point cloud to obtain an attribute bitstream. The encoder 200 can transmit the encoded geometric bitstream and attribute bitstream together to the decoder 300.

[0106] Figure 3a shows a decoding flowchart executed by the decoder in the AVS-PCC-based decoding framework, and Figure 3b shows a decoding flowchart executed by the decoder in the MPEG G-PCC-based decoding framework. The decoder can be the decoder 300 shown in Figure 1. After receiving the compressed bitstream (i.e., attribute bitstream and geometric bitstream) transmitted by the encoder 200, the decoder 300 decodes the geometric bitstream to reconstruct the geometric coordinate information of each point in the point cloud, and decodes the attribute bitstream to reconstruct the attribute information of each point in the point cloud.

[0107] The decoding process performed by decoder 300 is as follows:

[0108] 1. Entropy Decoding: Perform entropy decoding on the geometric bitstream and attribute bitstream respectively to obtain geometric syntax elements and attribute syntax elements.

[0109] 2. Geometric Decoding: For the AVS-PCC coding framework, geometric decoding includes two modes: octree-based geometric decoding and prediction tree-based geometric decoding. For the G-PCC coding framework, geometric decoding includes three modes: octree-based geometric decoding, trisoup-based geometric decoding, and prediction tree-based prediction decoding.

[0110] Geometric decoding based on multi-way trees, such as geometric decoding based on octrees: reconstructing the octree based on the geometric syntax elements obtained from parsing the geometric bitstream.

[0111] Geometric Decoding Based on Prediction Trees: Reconstructing the prediction tree based on the geometric syntax elements obtained from parsing the geometric bitstream.

[0112] Geometric Decoding Based on Triangle Representation: Reconstructing the triangular model based on the geometric syntax elements obtained from parsing the geometric bitstream.

[0113] 3. Geometric Reconstruction: Perform reconstruction to obtain the geometric coordinate information of the points in the point cloud.

[0114] 4. Inverse coordinate transformation: Perform an inverse transformation on the reconstructed geometric coordinate information to convert the reconstructed coordinates (positions) of points in the point cloud from the transformation domain back to the initial domain.

[0115] 5. Dequantization: Dequantizes attribute syntax elements.

[0116] 6. Attribute Information Processing: In AVS-PCC, attribute information processing determines the color information of points in the point cloud by predicting or predicting the transformation of the inverse-quantized prediction residual or prediction residual transformation coefficients, or by transforming the transformation coefficients of the inverse-quantized transformation.

[0117] In MPEG G-PCC, attribute information processing determines the color information of points in the point cloud by using RAHT to invert the attribute information, or by using LOD and inverse boosting to determine the color information of points in the point cloud.

[0118] 7. Inverse Color Transformation: Transforms color information from the YCbCr color space to the RGB color space. In some examples, the inverse color transformation operation may not be necessary.

[0119] The attribute encoding of G-PCC can be divided into region adaptive transformation based on upsampling prediction and lifting transformation based on hierarchical structure partitioning.

[0120] Among them, the region adaptive transformation based on upsampling prediction includes:

[0121] First, construct the transformation tree structure. Starting from the bottom layer, build an octree structure from the bottom up. During the construction of the transformation tree, it is necessary to generate corresponding Morton code information, attribute information, and weight information for the merged nodes.

[0122] Then, from top to bottom, starting from the root node, upsampling prediction and Region Adaptive Harm Transform (RAHT) are performed layer by layer.

[0123] If the current node is the root node, then no upsampling prediction is performed. Instead, the node's attribute information is directly subjected to RAHT transformation, and then the DC and AC coefficients obtained from the transformation are quantized and entropy encoded.

[0124] If the node is not the root node, the number of grandparent and parent nodes determines whether to predict the current node. If prediction is required, for the current node to be encoded, the following are selected for its child nodes: the parent node of the current child node, the neighboring parent node coplanar and collinear with the current child node, and the neighboring child node coplanar and collinear with the current child node. A weighted prediction is then performed to obtain the predicted attribute value of the current child node. Then, the predicted attribute value and the original attribute value of the current child node are subjected to RAHT transformation, and the resulting AC coefficient residuals are calculated. The AC coefficient residuals are then quantized and entropy encoded. If prediction is not required, the original attribute value of the current child node is directly subjected to RAHT transformation, and the resulting AC coefficients are quantized and entropy encoded to finally obtain the attribute bitstream.

[0125] The lifting transform based on hierarchical structure partitioning includes the following steps: First, the point cloud to be encoded is hierarchically partitioned using Level of Detail (LoD) partitioning to establish its hierarchical structure. In this process, the lowest-level nodes are encoded and decoded first, allowing the prediction of higher-level points using the lowest-level points and reconstructed points at the same level, thus achieving progressive encoding and decoding. Then, using the lowest-level and same-level points as reference points, the point to be encoded searches within these reference points, selecting the K nearest reference points as prediction reference points. Linear interpolation prediction is then performed using the reconstructed attribute values ​​of these K nearest neighbors, with the weight being the reciprocal of the Euclidean distance between the nearest neighbor and the point to be encoded. Finally, the lifting transform is performed, which includes segmentation, prediction, and update. The segmentation stage spatially divides the input point cloud data into high-level and low-level point clouds. In the prediction stage, the attribute information of the low-level point cloud is used to predict the attribute information of the high-level point cloud, obtaining the prediction residual. During the segmentation and prediction process, since the prediction strategy in the LoD partitioning makes the points in the lower LoD layers have higher weights, it is necessary to define and recursively update the influence weight of each point based on the prediction residual and the distance between the predicted point and its neighbors, and finally obtain the bitstream of attribute information.

[0126] As shown in Figure 4, this application provides a method for decoding attribute information, executed by a decoding end, the method comprising:

[0127] Step 401: The decoding end decodes and dequantizes the data to be decoded to obtain the reconstruction transform coefficients corresponding to each node; the reconstruction transform coefficients are the reconstruction transform coefficients of the transform coefficients corresponding to the attribute information of each node; the reconstruction transform coefficients include: the first reconstruction transform coefficient corresponding to the luminance component of the transform coefficient, the second reconstruction residual transform coefficient corresponding to the first chrominance component of the transform coefficient, and the third reconstruction residual transform coefficient corresponding to the second chrominance component of the transform coefficient.

[0128] Step 402: The decoding end determines the second reconstruction transformation coefficient corresponding to the first chromaticity component based on the first reconstruction transformation coefficient and the second reconstruction residual transformation coefficient;

[0129] Step 403: The decoding end performs at least one of the following:

[0130] (1) Determine the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the second reconstruction transformation coefficient and the third reconstruction residual transformation coefficient;

[0131] (2) Determine the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the first reconstruction transformation coefficient and the third reconstruction residual transformation coefficient;

[0132] (3) Determine the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the first reconstruction transformation coefficient, the second reconstruction transformation coefficient and the third reconstruction residual transformation coefficient.

[0133] In this embodiment, the decoding end obtains the data to be decoded from the bitstream sent by the encoding end, decodes and dequantizes the data, and constructs a transform tree structure based on geometric reconstruction information. This allows the decoding end to obtain the reconstruction transform coefficients corresponding to multiple layers of nodes in the transform tree. These reconstruction transform coefficients are obtained by the encoding end through predictive encoding of the attribute information of each node. The decoding end then uses the obtained reconstruction transform coefficients to perform an inverse transform to obtain the reconstructed attribute information. Specifically, the first reconstruction transform coefficient can be considered the reconstruction information of the luminance component, the second reconstruction residual transform coefficient is the reconstruction residual information of the first chrominance component obtained by predictive encoding at the encoding end, and the third reconstruction residual transform coefficient is the reconstruction residual information of the second chrominance component obtained by predictive encoding at the encoding end.

[0134] The second reconstruction transform coefficient is the reconstruction information of the first chroma component obtained by the inverse transform at the decoding end, and the third reconstruction transform coefficient is the reconstruction information of the second chroma component obtained by the inverse transform at the decoding end.

[0135] The luminance component is the component of the Y channel, and the first chromaticity component and the second chromaticity component can be components of the Cb and Cr channels, respectively.

[0136] When the encoding end performs predictive encoding on the attribute information of each node, it first performs RAHT transformation on each node to obtain the transformation coefficients corresponding to the attribute information of each node, including the luminance component (the component of the Y channel), the first chrominance component (the component of the Cb channel), and the second chrominance component (the component of the Cr channel). Based on the correlation between the above components, the transformation coefficients of the first chrominance component are predicted and encoded using the reconstructed information of the luminance component (i.e., the first reconstructed transformation coefficients) to obtain the second residual transformation coefficients. Then, the second chrominance component is predicted and encoded using either the second reconstructed transformation coefficients corresponding to the first chrominance component or the first reconstructed transformation coefficients to obtain the third residual transformation coefficients. The encoding end transmits the first reconstructed transformation coefficients, the second residual transformation coefficients, and the third residual transformation coefficients to the bitstream. The decoding end then decodes the bitstream and performs inverse quantization to obtain the first reconstructed transformation coefficients, the second reconstructed residual transformation coefficients corresponding to the second residual transformation coefficients, and the third reconstructed residual transformation coefficients corresponding to the third residual transformation coefficients.

[0137] It should be noted that, since the method of calculating residuals is used when calculating the reconstruction information of the first chromaticity component and the second chromaticity component, the reconstruction information is named the second reconstruction residual transformation coefficient and the third reconstruction residual transformation coefficient. These are just exemplary names, and can be any other names that can represent the reconstruction information of the first chromaticity component and the second chromaticity component. No limitation is made here.

[0138] When performing the inverse transform, the decoding end can use the reconstructed information of the luminance component (the component of the Y channel) and the second reconstruction residual transform coefficients of the first chrominance component to determine the reconstructed information of the first chrominance component, i.e., the second reconstruction transform coefficients. After obtaining the first and second reconstruction transform coefficients, the decoding end has multiple methods to obtain the third reconstruction information corresponding to the second chrominance component:

[0139] Method 1: Based on the correlation between the first chromaticity component and the second chromaticity component, and based on the second reconstruction transform coefficient corresponding to the first chromaticity component and the third reconstruction residual transform coefficient corresponding to the second chromaticity component, determine the third reconstruction transform coefficient.

[0140] Method 2: Based on the correlation between the luminance component and the second chrominance component, the third reconstruction transformation coefficient is determined according to the first reconstruction transformation coefficient corresponding to the luminance component and the third reconstruction residual transformation coefficient.

[0141] Method 3: Based on the correlation between the luminance component and the second chrominance component, and the correlation between the first chrominance component and the second chrominance component, the third reconstruction coefficient is determined based on the first reconstruction transformation coefficient, the second reconstruction transformation coefficient, and the third reconstruction residual transformation coefficient.

[0142] The first reconstruction transform coefficient, the second reconstruction transform coefficient, and the third reconstruction transform coefficient are the reconstruction information of the attribute information of each node obtained by the RAHT inverse transform at the decoding end.

[0143] In embodiments of this application, the decoding end determines the reconstructed information of each attribute component based on the correlation between the various attribute components of a node. Specifically, based on the correlation between the luminance component and the first chrominance component, the reconstructed information of the first chrominance component is determined using the first reconstruction transform coefficients of the luminance component and the second reconstruction residual transform coefficients of the first chrominance component; the reconstructed information corresponding to the second chrominance component is determined based on the correlation between the luminance component and the second chrominance component, or based on the correlation between the first chrominance component and the second chrominance component. By considering the correlation between different components when reconstructing the attribute information of a node, the decoding end effectively reduces the bit rate and improves decoding efficiency.

[0144] As an optional embodiment, determining the second reconstruction transformation coefficient corresponding to the first chromaticity component based on the first reconstruction transformation coefficient and the second reconstruction residual transformation coefficient includes:

[0145] The second reconstruction transformation coefficients are determined based on the second reconstruction residual transformation coefficients and the prediction compensation for the first chromaticity component;

[0146] The prediction compensation of the first chromaticity component is determined based on the first reconstruction transform coefficient and the first parameter, wherein the first parameter is used to represent the linear relationship between the luminance component and the first chromaticity component.

[0147] In this embodiment, the prediction compensation for the first chroma component corresponds to the encoding loss incurred by the encoder when encoding the first chroma component. The prediction compensation for the first chroma component is s. YCb *Res Y__recon .

[0148] As an optional embodiment, determining the second reconstruction transform coefficients based on the second reconstructed residual transform coefficients and the prediction compensation for the first chromaticity component includes:

[0149] The second reconstruction transformation coefficient is obtained by summing the product of the first reconstruction transformation coefficient and the first parameter with the second reconstruction residual transformation coefficient.

[0150] The first parameter is used to represent the linear relationship between the luminance component and the first chrominance component.

[0151] In this embodiment, when calculating the second reconstructed transform coefficients, the decoding end first calculates the product of the first reconstructed transform coefficients and the first parameter, and then calculates the sum of the product and the second reconstructed residual transform coefficients. The result obtained is the second reconstructed transform coefficients. This process utilizes the correlation between the luminance component and the first chrominance component. The first parameter can represent the linear relationship between the luminance component and the first chrominance component, thus using the correlation between the two to calculate the second reconstructed transform coefficients.

[0152] For example: the first reconstruction transform coefficient is represented as: Res Y__recon The first parameter is represented as s YCb The second reconstruction residual transformation coefficient is expressed as: Res′ Cb__recon Then the second reconstruction transform coefficient Res Cb__recon It can be represented as: Res Cb__recon =Res′ Cb__recon +s YCb *Res Y__recon

[0153] As an optional embodiment, determining the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the second reconstruction transformation coefficient and the third reconstruction residual transformation coefficient includes:

[0154] The third reconstruction transformation coefficients are determined based on the third reconstruction residual transformation coefficients and the first prediction compensation for the second chromaticity component;

[0155] The prediction compensation of the second chromaticity component is determined based on the third parameter and the second reconstruction transform coefficient. The third parameter is used to represent the linear relationship between the first chromaticity component and the second chromaticity component.

[0156] In this embodiment, the first prediction compensation for the second chroma component is relative to the first encoding loss of the second chroma component at the encoding end, and the first prediction compensation is s. CbCr *Res Cb_recon .

[0157] As an optional embodiment, determining the third reconstruction transform coefficients based on the third reconstruction residual transform coefficients and the first prediction compensation for the second chromaticity component includes:

[0158] The third reconstruction transformation coefficient is obtained by summing the product of the second reconstruction transformation coefficient and the third parameter with the third reconstruction residual transformation coefficient.

[0159] The third parameter is used to represent the linear relationship between the first chromaticity component and the second chromaticity component.

[0160] This embodiment describes one method for determining the third reconstructed transform coefficients at the decoding end. It calculates the third reconstructed transform coefficients Res based on the correlation between the first and second chromaticity components. Cr_recon Res cr_recon =Res′ Cr_recon +s CbCr *Res Cb_recon

[0161] Among them, Res Cb_recon The second reconstruction transform coefficient, s CbCr It is the third parameter, Res′ Cr_recon These are the coefficients of the third reconstruction residual transformation.

[0162] As another optional embodiment, determining the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the first reconstruction transformation coefficient and the third reconstruction residual transformation coefficient includes:

[0163] The third reconstruction transformation coefficients are determined based on the third reconstruction residual transformation coefficients and the second prediction compensation for the second chromaticity component;

[0164] The second prediction compensation of the second chromaticity component is determined based on the second parameter and the first reconstruction transform coefficient. The second parameter is used to represent the linear relationship between the luminance component and the second chromaticity component.

[0165] In this embodiment, the second prediction compensation for the second chroma component is relative to the second coding loss of the second chroma component at the encoding end, and the second prediction compensation is s. YCr *Res Y__recon .

[0166] As another optional embodiment, determining the third reconstruction transformation coefficients based on the third reconstruction residual transformation coefficients and the second prediction compensation for the second chromaticity component includes:

[0167] The third reconstruction transformation coefficient is obtained by summing the product of the first reconstruction transformation coefficient and the second parameter with the third reconstruction residual transformation coefficient.

[0168] The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component.

[0169] This embodiment is another way for the decoder to determine the third reconstruction transform coefficients. Based on the correlation between the luminance component and the second chrominance component, the third reconstruction transform coefficients Res are calculated. Cr_recon Res Cr_recon =Res′ Cr__recon +s YCr *Res Y__recon

[0170] Among them, Res Y__recon It is the first reconstruction transform coefficient, s YCr It is the second parameter, Res′ Cr_recon These are the coefficients of the third reconstruction residual transformation.

[0171] As an optional embodiment, the decoding end, when the first condition is met, determines the third reconstruction transformation coefficient corresponding to the second chroma component based on the second reconstruction transformation coefficient and the third reconstruction residual transformation coefficient;

[0172] The first condition includes one of the following:

[0173] For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is not 0;

[0174] For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is 0;

[0175] The first threshold is obtained by decoding the bitstream.

[0176] As an optional embodiment, the decoding end, when the second condition is met, determines the third reconstruction transformation coefficient corresponding to the second chroma component based on the first reconstruction transformation coefficient and the third reconstruction residual transformation coefficient;

[0177] The second condition includes one of the following:

[0178] For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is 0;

[0179] For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is not 0;

[0180] The first threshold is obtained by decoding the bitstream.

[0181] In this embodiment, the decoding end performs a conditional judgment. If the first condition is met, the third reconstruction transform coefficient is calculated using the first method. If the second condition is met, the third reconstruction transform coefficient is calculated using the second method.

[0182] The first threshold can be a predefined value, or it can be a threshold for the current layer number. For example, the first threshold is 3.

[0183] For example: The first threshold for the number of levels (lvl) is numslayer. The decoder checks if the current level (lvl) is greater than numslayer.

[0184] a: If the third parameter s of the current node CbCr If the value is not 0, then the value Res is reconstructed using the transformation coefficients of Cb. Cb__recon The reconstructed values ​​of the transform coefficients for the Cr channel, i.e., the third reconstructed transform coefficients, are calculated as: Res Cr__recon =Res′ Cr__recon +s CbCr *Res Cb__recon

[0185] b: The third parameter s of the current node CbCr If the value is 0, then the transform coefficients Res are reconstructed using Y. Y__recon The reconstructed values ​​of the transform coefficients for the Cr channel, i.e., the third reconstructed transform coefficients, are calculated as: Res Cr_recon =Res′ Cr__recon +s YCr *Res Y__recon

[0186] If the current lvl layer is less than or equal to numslayer:

[0187] c: If the second parameter s of the current node YCr If the value is not 0, then the transform coefficients Res are reconstructed using Y. Y__recon The reconstructed values ​​of the transform coefficients for the Cr channel, i.e., the third reconstructed transform coefficients, are calculated as: Res Cr_recon =Res′ Cr__recon +s Ycr *Res Y__recon

[0188] d: The second parameter s of the current node YCr If the value is equal to 0, then the value Res is reconstructed using the Cb transform coefficients. Cb__recon The reconstructed values ​​of the transform coefficients for the Cr channel, i.e., the third reconstructed transform coefficients, are calculated as: Res Cr__recon =Res′ Cr__recon +s CbCr *Res Cb__recon

[0189] As another optional embodiment, determining the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the first reconstruction transformation coefficient, the second reconstruction transformation coefficient, and the third reconstruction residual transformation coefficient includes:

[0190] Based on the first prediction compensation (s) of the second chromaticity component CbCr *Res Cb__recon ), and the second prediction compensation for the second chromaticity component (s YCr *Res Y__recon The third reconstruction transform coefficients are determined by combining the third reconstruction residual transform coefficients with the third reconstruction residual transform coefficients.

[0191] The prediction compensation of the second chromaticity component is determined based on the third parameter and the second reconstruction transform coefficient, and the second prediction compensation of the second chromaticity component is determined based on the second parameter and the first reconstruction transform coefficient.

[0192] The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component, and the third parameter is used to represent the linear relationship between the first chrominance component and the second chrominance component.

[0193] As another optional embodiment, determining the third reconstruction transformation coefficient based on the first prediction compensation for the second chromaticity component, the second prediction compensation for the second chromaticity component, and the third reconstruction residual transformation coefficient includes:

[0194] The product of the second reconstruction transformation coefficient and the third parameter is summed with the third reconstruction residual transformation coefficient to obtain the first residual value of the third reconstruction transformation coefficient;

[0195] The third reconstruction transformation coefficient is obtained by summing the product of the first reconstruction transformation coefficient and the second parameter with the first residual value of the third reconstruction transformation coefficient.

[0196] The second parameter represents the linear relationship between the luminance component and the second chrominance component, and the third parameter represents the linear relationship between the first chrominance component and the second chrominance component.

[0197] This embodiment corresponds to the case where the decoder first uses the luminance component to predictively encode the first and second chrominance components, and then uses the reconstructed information of the first chrominance component to perform secondary encoding on the second chrominance component. This embodiment is the third way to calculate the third reconstruction transform coefficients. When the decoder calculates the third reconstruction transform coefficients, it calculates the first residual value of the third reconstruction transform coefficients based on the third parameter, the second reconstruction transform coefficients, and the third reconstruction residual transform coefficients. This process utilizes the correlation between the first and second chrominance components. Then, it calculates the third reconstruction transform coefficients using the first reconstruction transform coefficients, the first residual value, and the second parameter. This process utilizes the correlation between the luminance component and the second chrominance component.

[0198] For example: the first reconstruction transform coefficient is represented as: Res Y__recon The second reconstruction transform coefficient is expressed as: Res Cb__recon The third reconstruction residual transformation coefficient is expressed as: Res′ Cr__recon The first residual value of the third reconstruction transform coefficient is expressed as: Res″ Cr__recon The third coefficient is denoted as s. CbCr The second coefficient is denoted as s. YCr The quadratic residual value of the third reconstruction transform coefficient is the third reconstruction transform coefficient, denoted as Res. Cr_recon The third reconstruction transform coefficient is then calculated as follows: Res″ Cr__recon =Res′ Cr__recon +s CbCr *Res Cb__recon Res Cr_recon =Res″ Cr__recon +s YCr *Res Y__recon

[0199] As an optional embodiment, the method further includes:

[0200] Determine target parameters, which include at least one of the following: a first parameter for representing the linear relationship between the luminance component and the first chrominance component, a second parameter for representing the linear relationship between the luminance component and the second chrominance component, and a third parameter for representing the linear relationship between the first chrominance component and the second chrominance component.

[0201] In this embodiment, before calculating the reconstruction information of each component, the decoding end determines the first parameter, the second parameter, and / or the third parameter in the above calculation process.

[0202] The determination of the target parameter includes at least one of the following:

[0203] (1) Decode the bitstream to obtain the target parameters; in this case, the encoding end determines the target parameters when performing predictive encoding on the attribute information of the nodes, and writes the target parameters into the bitstream; the decoding end can obtain the parameters used by each layer of nodes by decoding the bitstream. Optionally, the decoding end can also use fixed values ​​that are preset for each layer or each node.

[0204] (2) For the transform tree corresponding to the point cloud, calculate the target parameters corresponding to the undecoded nodes based on the reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree. In this case, the decoding end needs to determine the target parameters itself. Specifically, it can determine the target parameters used by the undecoded nodes based on the decoding order and the reconstructed information of the decoded transform coefficients.

[0205] Optionally, the decoded transform coefficients within the same layer include one of the following:

[0206] All transform coefficients that have been decoded within the same layer;

[0207] The first m transform coefficients that have been decoded within the same layer, where m is greater than 1;

[0208] All transform coefficients of the first k decoded nodes within the same layer, where k is greater than 1.

[0209] In this embodiment, the target parameters used by undecoded nodes are determined using the reconstruction information of the already decoded transform coefficients. For nodes in the same layer, the target parameters used by undecoded nodes can be determined using all the already decoded transform coefficients; alternatively, the target parameters used by undecoded nodes can be determined using a subset of the already decoded transform coefficients (e.g., the first m transform coefficients in the decoding order, where m is greater than 1 and less than the total number of already decoded transform coefficients); or, the target parameters used by undecoded nodes can be determined using all the transform coefficients of a subset of the already decoded nodes (e.g., the first k nodes, where k is greater than 1 and less than the total number of already decoded nodes) in the decoding order of each node.

[0210] Optionally, calculating the target parameters corresponding to the undecoded nodes based on the decoded transform coefficients within the same layer of the transform tree includes:

[0211] Decode the bitstream to obtain the first threshold;

[0212] For layers in the transform tree whose number of layers is less than or equal to the first threshold, the target parameters corresponding to the undecoded nodes are calculated based on the decoded transform coefficients within the same layer.

[0213] In this embodiment, the decoding end can calculate the target parameters of nodes in only a subset of layers of the transform tree. For example, it can calculate the target parameters of nodes in layers whose layer number is less than or equal to a first threshold. The first threshold is, for example, 3. The first threshold can be written into the bitstream by the encoding end, and the decoding end can obtain the first threshold by decoding the bitstream. By calculating the target parameters only for a subset of layers that meet the conditions, the encoding and decoding efficiency can be improved.

[0214] As an optional embodiment, calculating the target parameters corresponding to the undecoded nodes based on the decoded transform coefficients within the same layer of the transform tree includes:

[0215] The first parameter is determined based on the first reconstructed transform coefficient and the second reconstructed transform coefficient corresponding to the decoded transform coefficients in the same layer of the transform tree;

[0216] The second parameter is determined based on the first reconstructed transform coefficient and the third reconstructed transform coefficient corresponding to the decoded transform coefficients in the same layer of the transform tree;

[0217] The third parameter is determined based on the first residual value of the second and third reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree; or, the third parameter is determined based on the second and third reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree.

[0218] In this embodiment, (1) corresponds to the first parameter s YCb The components involved in the fitting are:

[0219] The Y component transform coefficients, which are the previously decoded, quantized, and dequantized Y components, are the first reconstructed transform coefficients Res. Y__recon ;

[0220] The transform coefficients (i.e., Res′) of the previously decoded, quantized, and dequantized Cb components. Cb ) plus (s YCb *Y component transformation coefficients Res after dequantization Y__recon ), that is, the second reconstruction transform coefficient Res Cb__recon .

[0221] (2a) For the second parameter s YCr The components involved in the fitting are:

[0222] The Y component transform coefficients, which are the previously decoded, quantized, and inverse-quantized components, are the first reconstructed transform coefficients Res. Y__recon ;

[0223] The transform coefficients (i.e., Res) of the Cr component after previous decoding, quantization, and inverse quantization. Cr ") plus (s CbCr *Cb component transformation coefficients Res after dequantization cb_recon ) plus (s Ycr *Y component transformation coefficients Res after dequantization Y__recon ), that is, the third reconstruction transform coefficient Res cr__recon This method is used when the second chromaticity component is subjected to two residuals, i.e., when calculating the third reconstruction transform coefficients, the above-mentioned method three is used.

[0224] or,

[0225] (2b) For the second parameter s YCr The components involved in the fitting are:

[0226] The Y component transform coefficients, which are the previously decoded, quantized, and inverse-quantized components, are the first reconstructed transform coefficients Res. Y__recon ;

[0227] The transform coefficients (i.e., Res) of the Cr component after previous decoding, quantization, and inverse quantization. Cr ′) plus (s CbCr *Cb component transformation coefficients Res after dequantization Cb_recon ) or (s YCr *Y component transformation coefficients Res after dequantization Y__recon ), that is, the third reconstruction transform coefficient Res Cr__recon This method is for cases where a residual has been applied to the second chromaticity component, i.e., when calculating the third reconstruction transform coefficients, either method one or method two described above is used.

[0228] (3a) For the third parameter s CbCr The components involved in the fitting are:

[0229] The transform coefficients of the previously decoded, quantized, and inversely quantized Cb components are the second reconstructed transform coefficients Res. Cb__recon ;

[0230] The transform coefficients of the previously decoded, quantized, and inversely quantized Cr component plus (s) CbCr *Cb component transformation coefficients Res after dequantizationCb_recon This is the first residual of the third reconstructed transform coefficients. This method is for the case where a second residual is applied to the second chromaticity component, that is, when calculating the third reconstructed transform coefficients, the above-mentioned method three is used.

[0231] or,

[0232] (3b) For the third parameter s CbCr The components involved in the fitting are:

[0233] The transform coefficients of the previously decoded, quantized, and inversely quantized Cb components are the second reconstructed transform coefficients Res. Cb__recon ;

[0234] The transform coefficients of the previously decoded, quantized, and inversely quantized Cr component plus (s) CbCr *Cb component transformation coefficients Res after dequantization Cb_recon ) or (s YCr The *Y component transformation coefficients after inverse quantization* are the third reconstructed transformation coefficients. This method is for cases where a residual has been applied to the second chromaticity component; that is, when calculating the third reconstructed transformation coefficients, either method one or method two described above is used.

[0235] Optionally, calculating the target parameters corresponding to the undecoded nodes based on the decoded transform coefficients within the same layer of the transform tree includes:

[0236] The first value is obtained by summing the products of the reconstructed transform coefficients corresponding to the first component and the reconstructed transform coefficients corresponding to the second component of the decoded transform coefficients in the same layer.

[0237] The second value is obtained by summing the squares of the reconstructed transform coefficients corresponding to the first component of the decoded transform coefficients within the same layer.

[0238] Calculate the ratio of the first value to the second value to obtain the target parameter corresponding to the first component;

[0239] Wherein, the first component and the second component are any two of the luminance component, the first chromaticity component and the second chromaticity component.

[0240] Based on the decoded transform coefficients within the same layer of the transform tree, the formula for calculating the target parameters corresponding to the undecoded nodes is as follows:

[0241] in, This represents the reconstruction transform coefficient corresponding to the first component of node j; This represents the reconstruction transform coefficients corresponding to the second component. For example, if the first, second, and third parameters need to be calculated, then s is calculated three times respectively. lvl,j In the first calculation, let x1 = Y, x2 = Cb, and calculate the first parameter; in the second calculation, let x1 = Y, x2 = Cr, and calculate the second parameter; in the third calculation, let x1 = Cb, x2 = Cr, and calculate the third parameter.

[0242] After obtaining the first parameter, the second parameter, and the third parameter, the decoder can calculate the second reconstruction transform coefficients and the third reconstruction transform coefficients. After determining the first reconstruction transform coefficients, the second reconstruction transform coefficients, and the third reconstruction transform coefficients, the decoder determines whether the current node should perform prediction.

[0243] If no prediction is performed: the DC coefficient of the current node inherits the attribute reconstruction value of the parent node, and together with the first reconstruction transformation coefficient, the second reconstruction transformation coefficient and the third reconstruction transformation coefficient obtained by the above method, a RAHT inverse transformation is performed to obtain the attribute reconstruction value of each child node of the current node.

[0244] If prediction is performed, the DC coefficient of the current node inherits the attribute reconstruction value of the parent node and is subtracted from the predicted attribute value of the parent node to obtain the DC coefficient residual. Then, it is combined with the first reconstruction transformation coefficient, the second reconstruction transformation coefficient, and the third reconstruction transformation coefficient obtained by the above method to perform RAHT inverse transformation, to obtain the attribute reconstruction residual of each child node of the current node. Then, it is added to the attribute prediction value to obtain the final attribute reconstruction value. When traversing to the bottom layer, the reconstructed attribute values ​​of all nodes are obtained, thus completing the attribute decoding.

[0245] The steps for determining whether a node should make a prediction include:

[0246] If the current node is the root node, then no upsampling prediction is performed;

[0247] If the current node is not the root node, and the current node consists of 2*2*2 child nodes, determine whether it is necessary to predict the child nodes of the current node.

[0248] First, when the current node has only one occupied child node, no prediction is made;

[0249] Then, if the number of parent nodes of the current node (i.e. the number of grandparent neighbors of the current node's child nodes) is less than the threshold 1 (e.g., the threshold 1 = 2), no prediction is made;

[0250] If threshold 1 is met, then neighbors are searched for the child nodes of the current node. The neighbor search range includes: the current node, neighbor parent nodes that are coplanar and collinear with the child nodes of the current node, and neighbor child nodes that are coplanar and collinear with the child nodes of the current node. When the number of neighbor parent nodes found is less than threshold 2 (for example, threshold 2 = 6), no prediction is performed.

[0251] The following example illustrates the process of encoding and decoding the attribute information of nodes in an embodiment of this application.

[0252] For the encoding end:

[0253] First, let's take the calculation of the third reconstruction transform coefficients at the encoding end using the third method described above as an example:

[0254] Step 1: Reorder the point cloud and construct an N-level RAHT transformation tree using a bottom-up approach. The bottom layer contains all nodes, and the top layer is the root node layer, containing only one node.

[0255] Step 2: Based on the transformation tree structure, perform upsampling prediction and Region Adaptive Hierarchal Transform (RAHT) layer by layer from the root node down.

[0256] The method for determining whether the current node needs to be predicted has been described in the background-related technical solutions above, and will not be repeated here.

[0257] If no prediction is performed, the original attribute information of the current node's child nodes is directly transformed using the RAHT method to obtain the AC transformation coefficients. If prediction is performed, the difference between the original attribute values ​​and the predicted attribute values ​​is used to obtain the attribute prediction residuals. Then, the attribute prediction residuals are transformed using the RAHT method to obtain the AC transformation coefficient residuals.

[0258] Step 3: For lossy encoding of attributes, the color attribute is encoded using the YCbCr format. There is a certain correlation between the three components. Let Res... i (i∈{Y,Cb,Cr}) represent the transform coefficients / transform coefficient residuals to be encoded in the Y, Cb, and Cr channels, respectively. It can be observed that the transform coefficients of different components have a good approximate relationship:

[0259] First, the transform coefficients of the Y channel are encoded. After quantization, entropy encoding, and dequantization, the reconstructed Y channel transform coefficients Res are obtained. Y_recon (The first reconstruction transform coefficients), using Res Y_recon Further prediction processing of the transformation coefficients of the Cb and Cr channels yields Res Cb ′ and ResCr ′:

[0260] Res′ Cb =Res Cb -s YCb ·Res Y_recon

[0261] Res′ Cr =Res Cr -s YCr ·Res Y_recon

[0262] Among them, s YCb s is the first parameter YCr Res′ is the second parameter. Cr This is the first residual value of the third residual transform coefficient. The encoder will use Res′... Cb Res′ Cb Input bitstream.

[0263] Then for Res Cb Subsequent quantization, entropy encoding, and dequantization are performed to obtain the reconstructed transform coefficients Res. Cb__recon (i.e., the second reconstruction transform coefficients), using Res Cb__recon The transformation coefficients Res′ of the Cr channel again Cr Further prediction processing yields Res Cr "(i.e., the third residual transformation coefficient): Res" Cr =Res′ Cr -s CbCr ·Res Cb_recon

[0264] The encoding end will use Res Cr "Input bitstream."

[0265] For Res Cr "Subsequent quantization, entropy encoding, and dequantization are performed to obtain the reconstructed transform coefficients Res." Cr_recon (i.e., the third reconstruction transformation coefficient).

[0266] Here, s is a scalar value. When two channels are correlated, s can be positive or negative. In some cases, when the two channels may not be significantly correlated, s is 0.

[0267] There are several ways to determine the value of s, including but not limited to any of the following:

[0268] 1) You can set a fixed set of s values ​​for all nodes, or you can set a fixed set of s values ​​for each layer.

[0269] 2) The transformation tree constructed by RAHT has multiple layers. Traverse all layers and calculate s once for each layer. a The values ​​(a∈{0:YCb,1:YCr,2:CbCr}) represent the correlation coefficients between YCb, YCr and CbCr, respectively. They are stored in CrossCompPredCoeff[lvl][a] and sent to the bitstream.

[0270] Each s in the current layer a The calculation method can be:

[0271] For the current level 1 (LVL), calculate the AC transformation coefficients obtained by transforming the original attribute information of all nodes within the level, denoted as . and i represents the coefficient index order, and s of the current LVL layer is obtained using the following method. a :

[0272] Calculate s three times respectively:

[0273] In the first calculation, x1 = Y, x2 = Cb, the first parameter s is obtained. YCb ;

[0274] The second time, x1 = Y, x2 = Cr, the second parameter s is calculated. YCr ;

[0275] The third time, x1 = Cb, x2 = Cr, the third parameter s is calculated. CbCr .

[0276] Alternatively, only the parameters s of a portion of the transformation tree can be computed. a For example, only calculate s for layers with a number of layers less than or equal to 3. a .

[0277] 3) Traverse all layers. Suppose that the current node j of the current LVL layer consists of 2*2*2 child nodes. Each node can obtain multiple transform coefficients. When performing inter-component prediction, the transform coefficients of this node are calculated from the transform coefficients that have been encoded and reconstructed in the previous sequence.

[0278] You can calculate an s for each transformation coefficient, or you can group n nodes together and calculate only one s for each group (n can be 1 or an integer greater than 1).

[0279] Meanwhile, the range of encoded transform coefficients used to calculate s can be all transform coefficients already encoded in the same layer, the first m transform coefficients already encoded in the same layer, or all transform coefficients of the first k nodes already encoded in the same layer. Calculate s three times:

[0280] In the first calculation, x1 = Y, x2 = Cb, the first parameter s is obtained. YCb ;

[0281] The second time, x1 = Y, x2 = Cr, the second parameter s is calculated. YCr ;

[0282] The third time, x1 = Cb, x2 = Cr, the third parameter s is calculated. CbCr .

[0283] Alternatively, only the parameters s of a portion of the transformation tree can be computed. a For example, only calculate s for layers with a number of layers less than or equal to 3.

[0284] Regarding the method for calculating s above:

[0285] The fitting coefficients s between Y and Cb YCb In terms of calculation, the components involved in the fitting are as follows:

[0286] The Y-component transform coefficients, which are pre-encoded, quantized, and then inversely quantized, are the reconstructed Y-component transform coefficients Res. Y_recon ;

[0287] The transform coefficients (i.e., Res′) of the pre-encoded, quantized, and dequantized Cb components. Cb ) plus (s YCb *The Y component transform coefficients after inverse quantization are the reconstructed Cb transform coefficients Res. Cb__recon That is, the second reconstruction transformation coefficient.

[0288] The fitting coefficient s between Y and Cr YCr In terms of calculation, the components involved in the fitting are as follows:

[0289] The Y-component transform coefficients, which are pre-encoded, quantized, and then inversely quantized, are the reconstructed Y-component transform coefficients Res. Y_recon ;

[0290] The transform coefficients (i.e., Res″) of the Cr component after pre-encoded quantization and inverse quantization. Cr ) plus (s CbCr *The Cb component transformation coefficients after dequantization) plus (s YCr *The Y component transform coefficients after inverse quantization are the reconstructed Cr transform coefficients Res. Cr__recon That is, the third reconstruction transformation coefficient.

[0291] The fitting coefficient s between Cb and Cr YCr In terms of calculation, the components involved in the fitting are as follows:

[0292] The transform coefficients Res′ of the pre-encoded quantized and inverse-quantized Cb components Cb , which is the first residual of the reconstructed Cb transform coefficients;

[0293] Transform coefficients (Res″) of the Cr component after pre-encoded quantization and inverse quantization Cr ) plus (s CbCr *The Cb component transform coefficients after inverse quantization, which is the first residual Res′ of the reconstructed Cr transform coefficients. Cr .

[0294] In this method, s can be calculated from the encoded information, so s does not need to be passed in the bitstream.

[0295] In this embodiment, the correlation between color chroma channels is utilized, and the transformation coefficients of the Cb and Cr channels are predicted and encoded twice using the reconstructed transformation coefficients of the Y channel. Then, the transformation coefficients of the Cr channel are predicted and encoded again using the reconstructed transformation coefficients of the Cb channel, thereby improving the encoding efficiency.

[0296] II. Taking the calculation of the third residual transform coefficients at the encoding end using either the first or second method described above as an example:

[0297] First, the transform coefficients of the Y channel are encoded, and then quantized and dequantized to obtain the reconstructed Y channel transform coefficients (i.e., the first reconstructed transform coefficients) Res. Y_recon Further prediction processing is performed on the transform coefficients of the Cb channel to obtain the first residual transform coefficients Res. Cb ′: Res′ Cb =Res Cb -s YCb ·Res Y_recon

[0298] Then for Res Cb Perform subsequent quantization and dequantization (plus s) YCb ·Res Y_recon The second reconstruction transform coefficients Res were obtained. Cb__recon ;

[0299] Res, the reconstruction transform coefficients of the Y channel Y_recon Or Cb reconstruction transformation coefficients Res Cb__recon The third residual transform coefficient Res is obtained by predicting the transform coefficients of the Cr channel. Cr ′, specifically as follows:

[0300] First, a parameter numslayer (i.e., the first threshold) is set. This parameter is used to select the prediction mode of the Cr component corresponding to different layers. This parameter can be passed into the bitstream.

[0301] Calculate the linearity coefficient s between the transform coefficients of the Y channel and the transform coefficients of the Cr channel, respectively. YCr (Second parameter) and the linear coefficient s between the transformation coefficients of the Cb channel and the Cr channel. CbCr (Third parameter).

[0302] Perform the following judgment: If the current level is greater than numslayer:

[0303] If the current node's s CbCr If the value is not 0, then the transform coefficients Res are reconstructed using Cb. Cb__recon The Res channel's transformation coefficients are predicted and processed to obtain the Res channel. Cr ′: Res′ Cr =Res Cr -s CbCr ·Res Cb_recon

[0304] The current node's s CbCr If the value is 0, then the transform coefficients Res are reconstructed using Y. Y__recon The Res channel's transformation coefficients are predicted and processed to obtain the Res channel. Cr ′: Res′ Cr =Res Cr -s YCr ·Res Y_recon

[0305] If the current lvl layer is less than or equal to numslayer:

[0306] If the current node's s YCr If the value is not 0, then the transform coefficients Res are reconstructed using Y. Y__recon The Res channel's transformation coefficients are predicted and processed to obtain the Res channel. Cr ′: Res′ Cr =Res Cr -s YCr ·Res Y_recon

[0307] The current node's s YCr If the value is 0, then the transform coefficients Res are reconstructed using Cb. Cb__recon The Res channel's transformation coefficients are predicted and processed to obtain the Res channel. Cr ′: Res′ Cr =Res Cr -s CbCr ·Res Cb_recon

[0308] For Res Cr Subsequent quantization and entropy encoding are performed to obtain the third reconstructed transform coefficients Res. Cr__recon.

[0309] For the first parameter s YCb The second parameter s YCr And the third parameter s CbCr The fitting method is as follows:

[0310] 1) Fitting coefficients s between Y and Cb YCb In terms of calculation, the components involved in the fitting are as follows:

[0311] The Y component transform coefficients after the previous encoded quantization and inverse quantization are the reconstructed Y transform coefficients.

[0312] The transform coefficients of the pre-encoded, quantized, and inverse-quantized Cb components plus (s) YCb The Y component transformation coefficients after inverse quantization are the reconstructed Cb transformation coefficients.

[0313] 2) Fitting coefficients s between Y and Cr YCr In terms of calculation, the components involved in the fitting are as follows:

[0314] The Y component transform coefficients after the previous encoded quantization and inverse quantization are the reconstructed Y transform coefficients.

[0315] The transform coefficients of the Cr component after pre-encoded quantization and inverse quantization are added to (s) CbCr *Cb component transformation coefficients after dequantization) or (s YCr The Y component transformation coefficients after inverse quantization are the reconstructed Cr transformation coefficients.

[0316] 3) Fit coefficients s between Cb and Cr CbCr In terms of calculation, the components involved in the fitting are as follows:

[0317] The Cb component transform coefficients after the previous encoded quantization and inverse quantization are the reconstructed Cb transform coefficients.

[0318] The transform coefficients of the Cr component after pre-encoded quantization and inverse quantization are added to (s) CbCr *Cb component transformation coefficients after dequantization) or (s YCr The Y component transformation coefficients after inverse quantization are the reconstructed Cr transformation coefficients.

[0319] For the decoding end:

[0320] (A) For cases where the target parameters are obtained using either the first or second method described in the encoding section.

[0321] Step 1: Decode the CrossCompPredCoeff from the bitstream to obtain the s used in each layer. YCbs YCr ,s CbCr The value can be chosen from either the S-values, or a fixed set of S-values ​​can be assigned to each layer or each node by the encoder / decoder.

[0322] Step 2: Obtain the data to be decoded from the bitstream, and perform entropy decoding and dequantization on the data to be decoded to obtain the reconstructed transform coefficient values: Res Y_recon Res Cb__recon Res Cr__recon .

[0323] Step 3: Reorder the point cloud and construct an N-layer RAHT transformation tree using a bottom-up approach. The bottom layer contains all nodes, and the top layer is the root node layer, containing only one node.

[0324] Step 4: Based on the transformation tree structure, perform upsampling prediction and RAHT inverse transformation on each node layer by layer from the root node down.

[0325] For the current node in the current LVL layer, let the reconstructed residual values ​​of the transform coefficients obtained from decoding Y, Cb, and Cr be Res, respectively. Y__recon Res Cb__recon and Res Cr__recon .

[0326] The reconstructed value of the Y-transform coefficients participating in the inverse transform is: Res Y__recon

[0327] Reconstructed values ​​Res of Cb transform coefficients participating in the inverse transform Cb__recon (Second reconstruction transform coefficients) are: Res Cb__recon =Res′ Cb__recon +s YCb *Res Y__recon

[0328] Reconstructed values ​​Res of Cr transform coefficients participating in the inverse transform Cr_recon (Third reconstruction transformation coefficients) are:

[0329] Res″ Cr__recon =Res′ Cr__recon +s CbCr *Res Cb__recon

[0330] Res Cr_recon =Res″ Cr__recon +s YCr *Res Y__recon

[0331] Then, determine whether the current node should make a prediction:

[0332] If no prediction is performed: the DC coefficients of the current node inherit the attribute reconstruction values ​​of the parent node, and together with the final Y, Cb, Cr transformation AC coefficient reconstruction values ​​obtained by the above method, a RAHT inverse transformation is performed to obtain the attribute reconstruction values ​​of each child node of the current node.

[0333] If prediction is performed, the DC coefficient of the current node inherits the attribute reconstruction value of the parent node and is subtracted from the predicted attribute value of the parent node to obtain the DC coefficient residual. Then, together with the final Y, Cb, Cr transformation AC coefficient reconstruction value obtained by the above method, a RAHT inverse transformation is performed to obtain the attribute reconstruction residual of each child node of the current node. Then, it is added to the attribute prediction value to obtain the final attribute reconstruction value.

[0334] When the traversal reaches the bottom layer, the reconstructed attribute values ​​of all nodes are obtained, thus completing the attribute decoding.

[0335] In this method, since the encoding end determines the target parameters and then inputs the bitstream, the decoding end can obtain the target parameter values ​​by decoding.

[0336] (B1) For the case where the target parameters are obtained by the method described in the third section of the encoding end, and the encoding end performs a second residual calculation on the second chromaticity component, that is, the decoding end uses method three to calculate the third reconstruction coefficient.

[0337] Step 1: Obtain the data to be decoded from the bitstream, perform entropy decoding and dequantization on the data to be decoded to obtain the reconstructed values ​​of the transform coefficients, that is, obtain the first reconstructed transform coefficient, the second reconstructed residual transform coefficient, and the third reconstructed residual transform coefficient.

[0338] Step 2: Reorder the point cloud and construct an N-layer RAHT transformation tree using a bottom-up approach. The bottom layer contains all nodes, and the top layer is the root node layer, containing only one node.

[0339] Step 3: Based on the transformation tree structure, perform upsampling prediction and RAHT inverse transformation on each node layer by layer from the root node from top to bottom.

[0340] Suppose that the current node j in the current LVL layer consists of 2*2*2 child nodes. The transform coefficients of this node, when used for inter-component prediction, are calculated from the transform coefficients of the previously decoded and reconstructed nodes.

[0341] You can calculate an 's' for each transform coefficient, or you can group n nodes together and calculate only one 's' for each group (n can be 1 or an integer greater than 1). Furthermore, the range of decoded transform coefficients used to calculate 's' can be all the transform coefficients already decoded in the same layer, the first m transformed coefficients already decoded in the same layer, or all the transform coefficients of the first k decoded nodes.

[0342] The fitting coefficients s between Y and Cb YCb In terms of calculation, the components involved in the fitting are as follows:

[0343] The Y-component transform coefficients, which are decoded, quantized, and then inversely quantized, are the reconstructed Y-component transform coefficients.

[0344] The transform coefficients of the previously decoded, quantized, and inverse-quantized Cb components plus (s) YCb The Y component transformation coefficients after inverse quantization are the reconstructed Cb transformation coefficients.

[0345] The fitting coefficient s between Y and Cr YCr In terms of calculation, the components involved in the fitting are respectively:

[0346] The Y-component transform coefficients, which are decoded, quantized, and then inversely quantized, are the reconstructed Y-component transform coefficients.

[0347] The transform coefficients of the previously decoded, quantized, and inversely quantized Cr component plus (s) CbCr *The Cb component transformation coefficients after dequantization) plus (s YCr *The Y component transform coefficients after inverse quantization are the reconstructed Cr transform coefficients.

[0348] The fitting coefficient s between Cb and Cr YCr In terms of calculation, the components involved in the fitting are as follows:

[0349] The Cb component transform coefficients after previous decoding and inverse quantization are the first residuals of the reconstructed Cb transform coefficients.

[0350] The transform coefficients of the previously decoded, quantized, and inversely quantized Cr component plus (s) CbCr The Cb component transformation coefficients after inverse quantization are the first-order residuals of the reconstructed Cr transformation coefficients.

[0351] For the current node in the current LVL layer, let the reconstructed residual values ​​of the transform coefficients obtained from decoding Y, Cb, and Cr be Res, respectively. Y__recon Res Cb__recon and Res Cr__recon ,

[0352] The reconstructed value of the Y-transform coefficients participating in the inverse transform is: ResY__recon

[0353] Reconstructed values ​​Res of Cb transform coefficients participating in the inverse transform Cb__recon (Second reconstruction transform coefficients) are: Res Cb__recon =Res′ Cb__recon +s YCb *Res Y__recon

[0354] Reconstructed values ​​Res of Cr transform coefficients participating in the inverse transform Cr_recon "(Third reconstruction transform coefficient) is: Res" Cr__recon =Res′ Cr__recon +s CbCr *Res Cb__recon Res Cr_recon =Res″ Cr__recon ′+s YCr *Res Y__recon

[0355] (B2) For the case where the target parameters are obtained by using the method described in the third method at the encoding end, and the encoding end performs a residual calculation on the second chromaticity component, that is, the decoding end uses method one or method two to calculate the third reconstruction coefficient.

[0356] First, decode the bitstream to obtain the value of the numslayer parameter.

[0357] The final reconstructed value of the Y-transform coefficients participating in the inverse transform is: Res Y__recon

[0358] The final reconstructed value Res of the Cb transform coefficients participating in the inverse transform Cb__recon (Second reconstruction transform coefficients) are: Res Cb__recon =Res′ Cb__recon +s YCb *Res Y__recon

[0359] The final reconstructed value Res of the Cr transform coefficients participating in the inverse transform Cr_recon The (third reconstruction transform coefficients) are calculated as follows:

[0360] If the current lvl layer is greater than numslayer:

[0361] If the current node's s CbCr If the value is not 0, then the value Res is reconstructed using the Cb transform coefficients. Cb__recon Calculate the reconstructed values ​​of the transform coefficients for the Cr channel: Res Cr__recon =Res′ Cr__recon +s CbCr *Res Cb__recon

[0362] The current node's s CbCr If the value is 0, then the transform coefficients Res are reconstructed using Y. Y__recon Calculate the reconstructed values ​​of the transform coefficients for the Cr channel: Res Cr_recon =Res′ Cr__recon +s YCr *Res Y__recon

[0363] If the current lvl layer is less than or equal to numslayer:

[0364] If the current node's s YCr If the value is not 0, then the transform coefficients Res are reconstructed using Y. Y__recon Calculate the reconstructed values ​​of the transform coefficients for the Cr channel: Res Cr_recon =Res′ Cr__recon +s YCr *Res Y__recon

[0365] The current node's s YCr If the value is equal to 0, then the value Res is reconstructed using the Cb transform coefficients. Cb__recon Calculate the reconstructed values ​​of the transform coefficients for the Cr channel: Res Cr__recon =Res′ Cr__recon +s CbCr *Res Cb__recon

[0366] The following applies to (B1) and (B2) above:

[0367] Determine whether to perform a prediction at the current node:

[0368] If no prediction is performed: the DC coefficients of the current node inherit the attribute reconstruction values ​​of the parent node, and together with the final Y, Cb, Cr transformation AC coefficient reconstruction values ​​obtained by the above method, a RAHT inverse transformation is performed to obtain the attribute reconstruction values ​​of each child node of the current node.

[0369] If prediction is performed, the DC coefficient of the current node inherits the attribute reconstruction value of the parent node and is subtracted from the predicted attribute value of the parent node to obtain the DC coefficient residual. Then, together with the final Y, Cb, Cr transformation AC coefficient reconstruction value obtained by the above method, a RAHT inverse transformation is performed to obtain the attribute reconstruction residual of each child node of the current node. Then, it is added to the attribute prediction value to obtain the final attribute reconstruction value.

[0370] When the traversal reaches the bottom layer, the reconstructed attribute values ​​of all nodes are obtained, thus completing the attribute decoding.

[0371] In embodiments of this application, the decoding end determines the reconstructed information of each attribute component based on the correlation between the various attribute components of a node. Specifically, based on the correlation between the luminance component and the first chrominance component, the reconstructed information of the first chrominance component is determined using the first reconstruction transform coefficients of the luminance component and the second reconstruction residual transform coefficients of the first chrominance component; the reconstructed information corresponding to the second chrominance component is determined based on the correlation between the luminance component and the second chrominance component, or based on the correlation between the first chrominance component and the second chrominance component. By considering the correlation between different components when reconstructing the attribute information of a node, the decoding end effectively reduces the bit rate and improves decoding efficiency.

[0372] As shown in Figure 5, this application provides a method for encoding attribute information, executed by an encoding terminal, the method comprising:

[0373] Step 51: The encoding end performs Region Adaptive Hierarchical Transformation (RAHT) on each node to obtain the transformation coefficients corresponding to the attribute information of each node; the transformation coefficients include: luminance component, first chrominance component and second chrominance component;

[0374] Step 52: The encoding end uses the first reconstruction transform coefficients corresponding to the luminance component to perform predictive encoding on the first chrominance component to obtain the second residual transform coefficients corresponding to the first chrominance component.

[0375] Step 53: Determine the second reconstruction transformation coefficient corresponding to the first chromaticity component based on the first reconstruction transformation coefficient and the second residual transformation coefficient;

[0376] Step 54: The encoding end performs at least one of the following:

[0377] The second chromaticity component is predicted and encoded using the second reconstruction transform coefficients to obtain the third residual transform coefficients corresponding to the second chromaticity component.

[0378] The second chromaticity component is predicted and encoded using the first reconstruction transform coefficients to obtain the third residual transform coefficients corresponding to the second chromaticity component.

[0379] The second chromaticity component is predicted and encoded using the first reconstruction transform coefficients to obtain the first residual value of the third residual transform coefficients corresponding to the second chromaticity component; the first residual value is predicted and encoded using the second reconstruction transform coefficients to obtain the third residual transform coefficients.

[0380] In this embodiment, the encoding end reorders the point cloud and constructs an N-layer RAHT transform tree using a bottom-up approach. The bottom layer contains all nodes, and the top layer is the root node layer, containing only one node. Based on the transform tree structure, upsampling prediction and RAHT transform are performed layer by layer from the root node down to obtain the transform coefficients corresponding to the attribute information of each node, including the luminance component (the component of the Y channel), the first chrominance component (the component of the Cb channel), and the second chrominance component (the component of the Cr channel).

[0381] Based on the correlation between the components, the reconstruction information of the luminance component (i.e., the first reconstructed transform coefficients) and the transform coefficients of the first chrominance component are first used for prediction encoding to obtain the second residual transform coefficients Res′ corresponding to the first chrominance component. Cb Res′ Cb =Res Cb -s YCb ·Res Yrecon

[0382] The encoding end will convert the second residual transform coefficients Res ′ Cb Input bitstream.

[0383] The encoding end calculates the second reconstruction transform coefficient Res using the second residual transform coefficient and the first reconstruction residual transform coefficient. Cb__recon : Regarding Res Cb Perform quantization and dequantization (plus s) YCb ·Res Y_recon The reconstruction transformation coefficients Res were obtained. Cb__recon .

[0384] There are three ways for the encoding end to calculate the third residual transform coefficients corresponding to the second chromaticity component:

[0385] Method 1: Utilizing the correlation between the first and second chromaticity components, and using the second reconstruction transform coefficient Res Cb__recon The second chromaticity component is encoded to obtain the third residual transform coefficient Res′. Cr .

[0386] Method 2: Utilizing the correlation between the luminance component and the second chrominance component, and using the first reconstruction transform coefficient Res Yrecon The second chromaticity component is encoded to obtain the third residual transform coefficient Res′. Cr .

[0387] Method 3: Utilizing the correlation between the luminance component, the first chrominance component, and the second chrominance component, the second chrominance component is encoded to obtain the third residual transformation coefficient Res″. Cr .

[0388] It should be noted that, since the method of calculating residuals is used when calculating the reconstruction information of the first chromaticity component and the second chromaticity component, the reconstruction information is named the second reconstruction residual transformation coefficient and the third reconstruction residual transformation coefficient. These are just exemplary names, and can be any other names that can represent the reconstruction information of the first chromaticity component and the second chromaticity component. No limitation is made here.

[0389] In embodiments of this application, the encoding end uses the first reconstructed transform coefficients corresponding to the luminance component of the node attribute information to predict and encode the transform coefficients of the first chrominance component, thereby obtaining the second residual transform coefficients and the second reconstructed transform coefficients corresponding to the first chrominance component. Then, utilizing the correlation between the luminance component, the first chrominance component, and the second chrominance component, the third residual transform coefficients corresponding to the second chrominance component are calculated through various methods. By calculating the reconstructed information based on the correlation between each component and removing redundancy multiple times, the encoding efficiency can be improved.

[0390] As an optional embodiment, the step of using the first reconstruction transform coefficients corresponding to the luminance component to predictively encode the first chrominance component and obtain the second residual transform coefficients corresponding to the first chrominance component includes:

[0391] Using the first chromaticity component and the encoding loss of the first chromaticity component, the second residual transform coefficients corresponding to the first chromaticity component are determined;

[0392] The encoding loss of the first chroma component is determined based on a first parameter and a first reconstruction transform coefficient. The first parameter is used to represent the linear relationship between the luminance component and the first chroma component.

[0393] In this embodiment, the encoding loss of the first chroma component is s YCb ·Res Y_recon This corresponds to the encoding compensation of the first chroma component at the decoding end.

[0394] As an optional embodiment, determining the second residual transform coefficients corresponding to the first chroma component using the first chroma component and its encoding loss includes:

[0395] Calculate the difference between the first chromaticity component and the product of the first parameter and the first reconstructed transform coefficient to obtain the second residual transform coefficient corresponding to the first chromaticity component;

[0396] The first parameter is used to represent the linear relationship between the luminance component and the first chrominance component.

[0397] In this embodiment, the encoding end performs quantization, entropy encoding, and dequantization on the luminance component to obtain the first reconstruction transform coefficient Res. Y_recon ; Calculate the first chromaticity component Res Cb With the first parameter s YCb and the first reconstruction transformation coefficient Res Y_recon The difference between the products: Res′ Cb =Res Cb -s YCb ·Res Y_recon That is, the second residual transformation coefficient Res is obtained. ′ Cb .

[0398] For Res Cb Subsequent quantization, entropy encoding, and dequantization yield the second reconstructed transform coefficients Res corresponding to the first chromaticity component. Cb__recon For example: for Res Cb Subsequent quantization, entropy encoding, and dequantization are performed to obtain the second reconstructed residual transform coefficients Res. Cb__recon Res′ Cb__recon +s YCb ·Res Yrecon =Res Cb__recon The second reconstruction transformation coefficients can then be obtained.

[0399] As an optional implementation, the step of predictively encoding the second chromaticity component using the second reconstructed transform coefficients to obtain the third residual transform coefficients corresponding to the second chromaticity component includes:

[0400] Using the second chromaticity component and the first coding loss of the second chromaticity component, the third residual transform coefficient corresponding to the second chromaticity component is determined;

[0401] The first coding loss of the second chroma component is determined based on the third parameter and the second reconstruction transform coefficient, wherein the third parameter is used to represent the linear relationship between the first chroma component and the second chroma component.

[0402] In this embodiment, the first encoding loss of the second chroma component is s. CbCr ·Res Cb_recon This corresponds to the first prediction compensation for the second chroma component at the decoding end. The second coding loss of the second chroma component is s. YCr ·Res Y_recon This corresponds to the second prediction compensation of the second chroma component at the decoding end.

[0403] As an optional implementation, determining the third residual transform coefficients corresponding to the second chroma component using the second chroma component and the first coding loss of the second chroma component includes:

[0404] Calculate the difference between the product of the second chromaticity component and the third parameter and the second reconstruction transform coefficient to obtain the third residual transform coefficient corresponding to the second chromaticity component;

[0405] The third parameter is used to represent the linear relationship between the first chromaticity component and the second chromaticity component.

[0406] This embodiment is the first method for calculating the third residual transform coefficient Res′, which utilizes the correlation between the first and second chromaticity components to calculate the third residual transform coefficient Res′. Cr Res′ Cr =Res Cr -s CbCr ·Res Cb_recon

[0407] Among them, Res Cr It is the second chromaticity component, s CbCr It is the third parameter, Res Cb_recon These are the second reconstruction transformation coefficients.

[0408] As another optional embodiment, the step of using the first reconstructed transform coefficients to predict and encode the second chromaticity component to obtain the third residual transform coefficients corresponding to the second chromaticity component includes:

[0409] The third residual transform coefficients corresponding to the second chromaticity component are determined using the second chromaticity component and the second coding loss of the second chromaticity component.

[0410] The second coding loss of the second chromaticity component is determined based on the second parameter and the first reconstruction transform coefficient. The second parameter is used to represent the linear relationship between the luminance component and the second chromaticity component.

[0411] As another optional embodiment, determining the third residual transform coefficients corresponding to the second chroma component using the second chroma component and the second encoding loss of the second chroma component includes:

[0412] Calculate the difference between the product of the second chromaticity component and the second parameter and the first reconstructed transform coefficient to obtain the third residual transform coefficient corresponding to the second chromaticity component;

[0413] The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component.

[0414] This embodiment is a second method for calculating the third residual transform coefficient Res′, which utilizes the correlation between the luminance component and the second chrominance component to calculate the third residual transform coefficient Res′. Cr Res′ Cr =Res Cr -s YCr ·Res Y_recon

[0415] Among them, Res Cr It is the second chromaticity component, s YCr It is the second parameter, Res Y_recon These are the first reconstruction transform coefficients.

[0416] As an optional embodiment, when the first condition is met, the encoding end uses the second reconstruction transform coefficients to predict and encode the second chromaticity component to obtain the third residual transform coefficients corresponding to the second chromaticity component;

[0417] The first condition includes one of the following:

[0418] For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is not 0;

[0419] For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is 0.

[0420] Optionally, when the second condition is met, the encoding end uses the first reconstruction transform coefficients to predict and encode the second chromaticity component to obtain the third residual transform coefficients corresponding to the second chromaticity component.

[0421] The second condition includes one of the following:

[0422] For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is 0;

[0423] For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is not 0.

[0424] In this embodiment, the encoding end performs a conditional judgment. If the first condition is met, the third residual transformation coefficient is calculated using the first method described above. If the second condition is met, the third residual transformation coefficient is calculated using the second method described above.

[0425] The first threshold can be a predefined value, or it can be a threshold for the current layer number. For example, the first threshold is 3.

[0426] For example: The first threshold for the number of levels (lvl) is numslayer. The decoder checks if the current level (lvl) is greater than numslayer.

[0427] a: If the third statement of the current node is s CbCr If the value is not 0, then the transform coefficients Res are reconstructed using Cb. Cb__recon The Res channel's transformation coefficients are predicted and processed to obtain the Res channel. Cr ′: Res′ Cr =Res Cr -s CbCr ·Res Cb_recon

[0428] b: The current node's s CbCr If the value is 0, then the transform coefficients Res are reconstructed using Y. Y__recon The Res channel's transformation coefficients are predicted and processed to obtain the Res channel. Cr ′: Res′ Cr =Res Cr -s YCr ·Res Y_recon

[0429] If the current lvl layer is less than or equal to numslayer:

[0430] c: If the current node's s YCr If the value is not 0, then the transform coefficients Res are reconstructed using Y. Y__recon The Res channel's transformation coefficients are predicted and processed to obtain the Res channel. Cr ′: Res′ Cr =Res Cr -s YCr ·Res Y_recon

[0431] d: The current node's s YCr If the value is 0, then the transform coefficients Res are reconstructed using Cb. Cb__recon The Res channel's transformation coefficients are predicted and processed to obtain the Res channel. Cr ′: Res′ Cr =Res Cr -s CbCr ·Res Cb_recon

[0432] For Res Cr Subsequent quantization and entropy encoding yield the third reconstructed transform coefficients Res. Cr__recon .

[0433] As an optional embodiment, the step of using the first reconstructed transform coefficients to predict and encode the second chromaticity component to obtain the first residual value of the third residual transform coefficients corresponding to the second chromaticity component; and using the second reconstructed transform coefficients to predict and encode the first residual value to obtain the third residual transform coefficients, includes:

[0434] Based on the second chromaticity component and the second encoding loss of the second chromaticity component (s) YCr ·Res Y_recon ), determine the first residual value of the third residual transformation coefficient;

[0435] Based on the first residual value of the third residual transform coefficient and the second coding loss s of the second chroma component CbCr ·Res Cb_recon Determine the third residual transformation coefficients;

[0436] Wherein, the first coding loss of the second chroma component is determined according to the third parameter and the second reconstruction transform coefficient, and the second coding loss of the second chroma component is determined according to the second parameter and the first reconstruction transform coefficient;

[0437] The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component, and the third parameter is used to represent the linear relationship between the first chrominance component and the second chrominance component.

[0438] As an optional embodiment, determining the first residual value of the third residual transform coefficient based on the second chroma component and the second coding loss of the second chroma component includes:

[0439] Calculate the difference between the product of the second chromaticity component and the second parameter and the first reconstructed transform coefficient to obtain the first residual value of the third residual transform coefficient;

[0440] The step of determining the third residual transform coefficients based on the first residual value of the third residual transform coefficients and the second coding loss of the second chroma component includes:

[0441] The difference between the first residual value and the product of the third parameter and the second reconstruction transform coefficient is calculated to obtain the third residual transform coefficient;

[0442] The second parameter represents the linear relationship between the luminance component and the second chrominance component; the third parameter represents the linear relationship between the first chrominance component and the second chrominance component.

[0443] In this embodiment, after obtaining the first reconstruction transform coefficient and the second reconstruction transform coefficient, the third reconstruction transform coefficient is calculated: first, the second chromaticity component Res is calculated.Cr With the second parameter s YCr and the first reconstruction transformation coefficient Res Y_recon The difference of the products yields the first residual value Res′ of the third residual transform coefficients. Cr Res′ Cr =Res cr -s Ycr ·Res Y_recon

[0444] Then calculate the secondary residual: that is, calculate the primary residual value Res′ Cr With the third parameter s cbCr and the second reconstruction transformation coefficient Res Cb_recon The difference between the products: Res″ Cr =Res′ Cr -s Cbcr ·Res Cb_recon

[0445] In this embodiment, Res″ Cr This represents the third residual transformation coefficient.

[0446] Optionally, the method further includes: quantizing and entropy encoding the third residual transform coefficients to obtain the third reconstructed transform coefficients corresponding to the second chromaticity component.

[0447] In this embodiment, after obtaining the third residual transform coefficients, the encoding end can further obtain the third reconstructed transform coefficients corresponding to the second chromaticity component through quantization entropy encoding. Specifically, when calculating the third reconstructed transform coefficients using the third residual transform coefficients, based on the methods mentioned above for obtaining the third residual transform coefficients, the third residual transform coefficients are quantized and encoded, and then the subtracted portion in the formula is added in reverse to obtain the third reconstructed transform coefficients. This will not be elaborated further here.

[0448] As an optional embodiment, the method further includes:

[0449] Determine target parameters, which include at least one of the following: a first parameter for representing the linear relationship between the luminance component and the first chrominance component, a second parameter for representing the linear relationship between the luminance component and the second chrominance component, and a third parameter for representing the linear relationship between the first chrominance component and the second chrominance component.

[0450] In this embodiment, before calculating the reconstruction information of each component, the encoding end determines the first parameter, the second parameter, and / or the third parameter in the above calculation process.

[0451] Optionally, determining the target parameter includes at least one of the following:

[0452] (1) Determine the target parameters according to the preset values; a set of fixed parameter values ​​can be set for all nodes, or a set of fixed parameter values ​​can be set for each layer.

[0453] (2) For the transformation tree corresponding to the point cloud, calculate the target parameter based on the transformation coefficients corresponding to the attribute information of all nodes in the same layer of the transformation tree; in this case, the encoder can traverse all layers and calculate s once for each layer in one or more layers. a The values ​​(a∈{0:YCb,1:YCr,2:CbCr}) represent the correlation coefficients between YCb, YCr and CbCr, respectively. They are stored in CrossCompPredCoeff[lvl][a] and sent to the bitstream.

[0454] (3) For the transform tree corresponding to the point cloud, the target parameters corresponding to the uncoded nodes are calculated based on the encoded transform coefficients within the same layer of the transform tree. In this case, the transform coefficients of the nodes are used to perform inter-component prediction, which are calculated from the transform coefficients that have been encoded and reconstructed in the previous sequence.

[0455] As an optional embodiment, for the transformation tree corresponding to the point cloud, the target parameters are calculated based on the transformation coefficients corresponding to the attribute information of all nodes in the same layer of the transformation tree, including:

[0456] Determine the transformation coefficients corresponding to the attribute information of all nodes within the same layer of the transformation tree;

[0457] The first parameter corresponding to the layer is calculated using the luminance component and the first chrominance component in the transformation coefficients of all nodes in the same layer.

[0458] The second parameter corresponding to the layer is calculated using the luminance component and the second chrominance component in the transformation coefficients of all nodes in the same layer.

[0459] The third parameter corresponding to the layer is calculated using the first and second chromaticity components of the transformation coefficients of all nodes within the same layer.

[0460] In this embodiment, the transformation tree constructed by RAHT has multiple layers. Traversing all layers, s is calculated once for each of the one or more layers. a The values ​​(a∈{0: YCb, 1: YCr, 2: CbCr}) represent the correlation coefficients between YCb, YCr, and CbCr, respectively, and are stored in CrossCompPredCoeff[lvl][a] and sent to the bitstream. Each s in the current layer... a The calculation method can be:

[0461] Calculate s three times respectively:

[0462] In the first calculation, x1 = Y, x2 = Cb, the first parameter s is obtained. YCb ;

[0463] The second time, x1 = Y, x2 = Cr, the second parameter s is calculated. YCr ;

[0464] The third time, x1 = Cb, x2 = Cr, the third parameter s is calculated. CbCr .

[0465] Optionally, the encoded transform coefficients within the same layer include one of the following:

[0466] All transform coefficients already encoded within the same layer;

[0467] The first m transform coefficients encoded within the same layer, where m is greater than 1;

[0468] All transform coefficients of the first k encoded nodes within the same layer, where k is greater than 1.

[0469] In this embodiment, when using the reconstruction information of the already encoded transform coefficients to determine the target parameters used by the uncoded nodes, for nodes in the same layer, the target parameters used by the uncoded nodes can be determined using all the already encoded transform coefficients; alternatively, the target parameters used by the uncoded nodes can be determined using a subset of the already encoded transform coefficients (e.g., the first m transform coefficients in the encoding order, where m is greater than 1 and less than the total number of already encoded transform coefficients); or, the target parameters used by the uncoded nodes can be determined using all the transform coefficients of a subset of the already encoded nodes (e.g., the first k nodes, where k is greater than 1 and less than the total number of already encoded nodes) in the encoding order of each node.

[0470] Optionally, calculating the target parameters corresponding to uncoded nodes based on the encoded transform coefficients within the same layer of the transform tree includes:

[0471] For layers in the transform tree whose number of layers is less than or equal to the first threshold, the target parameters corresponding to the undecoded nodes are calculated based on the decoded transform coefficients within the same layer.

[0472] In this embodiment, the encoding end can calculate the target parameters of nodes in only a subset of layers of the transform tree. For example, it can calculate the target parameters of nodes in layers whose layer number is less than or equal to a first threshold. The first threshold is, for example, 3. The encoding end writes the first threshold into the bitstream, and the decoding end can obtain the first threshold by decoding the bitstream. By calculating the target parameters only for a subset of layers that meet the conditions, the encoding and decoding efficiency can be improved.

[0473] As an optional embodiment, calculating the target parameters corresponding to the uncoded nodes based on the encoded transform coefficients within the same layer of the transform tree includes:

[0474] The first parameter is determined based on the first reconstructed transform coefficient and the second reconstructed transform coefficient corresponding to the coded transform coefficients in the same layer of the transform tree;

[0475] The second parameter is determined based on the first reconstructed transform coefficient and the third reconstructed transform coefficient corresponding to the coded transform coefficients in the same layer of the transform tree;

[0476] The third parameter is determined based on the first residual value of the second and third reconstructed transform coefficients corresponding to the coded transform coefficients in the same layer of the transform tree, or the third parameter is determined based on the second and third reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree.

[0477] In this embodiment, (1) corresponds to the first parameter s YCb The components involved in the fitting are:

[0478] The Y component transform coefficients, which are pre-encoded, quantized, and dequantized, are the first reconstructed transform coefficients Res. Y__recon ;

[0479] The transform coefficients (i.e., Res′) of the pre-encoded, quantized, and dequantized Cb components. Cb ) plus (s YCb *Y component transformation coefficients Res after dequantization Y__recon ), that is, the second reconstruction transform coefficient Res Cb__recon .

[0480] (2a) For the second parameter s YCr The components involved in the fitting are:

[0481] The Y component transform coefficients, which are pre-encoded, quantized, and then inversely quantized, are the first reconstructed transform coefficients Res. Y__recon ;

[0482] The transform coefficients (i.e., Res) of the Cr component after pre-encoded quantization and inverse quantization. Cr ") plus (s CbCr *Cb component transformation coefficients Res after dequantization cb_recon ) plus (s YCr *Y component transformation coefficients Res after dequantization Y__recon ), that is, the third reconstruction transform coefficient Res Cr__recon This method is used when the second chromaticity component is subjected to two residuals, i.e., when calculating the third reconstruction transform coefficients, the above-mentioned method three is used.

[0483] or,

[0484] (2b) For the second parameter s YCr The components involved in the fitting are:

[0485] The Y component transform coefficients, which are pre-encoded, quantized, and then inversely quantized, are the first reconstructed transform coefficients Res. Y__recon ;

[0486] The transform coefficients (i.e., Res) of the Cr component after pre-encoded quantization and inverse quantization. Cr ′) plus (s CbCr *Cb component transformation coefficients Res after dequantization Cb_recon ) or (s YCr *Y component transformation coefficients Res after dequantization Y__recon ), that is, the third reconstruction transform coefficient Res Cr__recon This method is for cases where a residual has been applied to the second chromaticity component, i.e., when calculating the third reconstruction transform coefficients, either method one or method two described above is used.

[0487] (3a) For the third parameter s CbCr The components involved in the fitting are:

[0488] The transform coefficients of the Cb component, which have been encoded, quantized, and then dequantized, are the second reconstructed transform coefficients Res. Cb__recon ;

[0489] The transform coefficients of the Cr component after pre-encoded quantization and inverse quantization are added to (s) CbCr *Cb component transformation coefficients Res after dequantization Cb_recon This is the first residual of the third reconstructed transform coefficients. This method is for the case where a second residual is applied to the second chromaticity component, that is, when calculating the third reconstructed transform coefficients, the above-mentioned method three is used.

[0490] or,

[0491] (3b) For the third parameter s CbCr The components involved in the fitting are:

[0492] The transform coefficients of the Cb component, which have been encoded, quantized, and then dequantized, are the second reconstructed transform coefficients Res. Cb__recon ;

[0493] The transform coefficients of the Cr component after pre-encoded quantization and inverse quantization are added to (s) CbCr *Cb component transformation coefficients Res after dequantization Cb_recon ) or (s YCrThe *Y component transformation coefficients after inverse quantization* are the third reconstructed transformation coefficients. This method is for cases where a residual has been applied to the second chromaticity component; that is, when calculating the third reconstructed transformation coefficients, either method one or method two described above is used.

[0494] Optionally, calculating the target parameters corresponding to uncoded nodes based on the encoded transform coefficients within the same layer of the transform tree includes:

[0495] The third value is obtained by summing the products of the reconstructed transform coefficients corresponding to the first component and the reconstructed transform coefficients corresponding to the second component of the encoded transform coefficients in the same layer.

[0496] The fourth value is obtained by summing the squares of the reconstructed transform coefficients corresponding to the first component of the encoded transform coefficients within the same layer.

[0497] Calculate the ratio of the third value to the fourth value to obtain the target parameter corresponding to the first component;

[0498] Wherein, the first component and the second component are any two of the luminance component, the first chromaticity component and the second chromaticity component.

[0499] In this embodiment, the formula for calculating the target parameters corresponding to uncoded nodes based on the encoded transform coefficients within the same layer of the transform tree is as follows:

[0500] in, This represents the reconstruction transform coefficient corresponding to the first component of node j; This represents the reconstruction transform coefficients corresponding to the second component. For example, if the first, second, and third parameters need to be calculated, then s is calculated three times respectively. lvl,j In the first calculation, let x1 = Y, x2 = Cb, and calculate the first parameter; in the second calculation, let x1 = Y, x2 = Cr, and calculate the second parameter; in the third calculation, let x1 = Cb, x2 = Cr, and calculate the third parameter.

[0501] Optionally, the method further includes: inputting the first threshold into the bitstream. In this embodiment, the encoding end inputs the first threshold used in the judgment process into the bitstream, and the decoding end obtains the first threshold by decoding the bitstream.

[0502] The following example illustrates the process of encoding node attribute information:

[0503] For the encoding end:

[0504] First, let's take the calculation of the third residual transform coefficients at the encoding end using the third method described above as an example:

[0505] Step 1: Reorder the point cloud and construct an N-level RAHT transformation tree using a bottom-up approach. The bottom layer contains all nodes, and the top layer is the root node layer, containing only one node.

[0506] Step 2: Based on the transformation tree structure, perform upsampling prediction and Region Adaptive Hierarchal Transform (RAHT) layer by layer from the root node down.

[0507] The method for determining whether the current node needs to be predicted has been described in the background-related technical solutions above, and will not be repeated here.

[0508] If no prediction is performed, the original attribute information of the current node's child nodes is directly transformed using the RAHT method to obtain the AC transformation coefficients. If prediction is performed, the difference between the original attribute values ​​and the predicted attribute values ​​is used to obtain the attribute prediction residuals. Then, the attribute prediction residuals are transformed using the RAHT method to obtain the AC transformation coefficient residuals.

[0509] Step 3: For lossy encoding of attributes, the color attribute is encoded using the YCbCr format. There is a certain correlation between the three components. Let Res... i (i∈{Y,Cb,Cr}) represent the transform coefficients / transform coefficient residuals to be encoded in the Y, Cb, and Cr channels, respectively. It can be observed that the transform coefficients of different components have a good approximate relationship:

[0510] First, the transform coefficients of the Y channel are encoded. After quantization, entropy encoding, and dequantization, the reconstructed Y channel transform coefficients Res are obtained. Y_recon (The first reconstruction transform coefficients), using Res Y_recon Further prediction processing of the transformation coefficients of the Cb and Cr channels yields Res Cb ′ and Res Cr ′: Res′ Cb =Res Cb -s YCb ·Res Y_recon Res′ Cr =Res Cr -s YCr ·Res Y_recon

[0511] Among them, s YCb s is the first parameter YCr Res is the second parameter. ′ Cr It is the first residual value of the third reconstruction residual transformation coefficient.

[0512] Then for Res Cb Subsequent quantization, entropy encoding, and dequantization are performed to obtain the reconstructed transform coefficients Res. Cb__recon (The second reconstructed residual transformation coefficients), using Res Cb__recon The transformation coefficients Res of the Cr channel again ′ Cr Further prediction processing yields Res Cr ": Res" Cr =Res′ Cr -s CbCr ·Res Cb_recon

[0513] For Res Cr "Subsequent quantization, entropy encoding, and dequantization are performed to obtain the reconstructed transform coefficients Res." Cr_recon (The third reconstruction residual transformation coefficient).

[0514] Here, s is a scalar value. When two channels are correlated, s can be positive or negative. In some cases, when the two channels may not be significantly correlated, s is 0.

[0515] There are several ways to determine the value of s, including but not limited to any of the following:

[0516] 1) You can set a fixed set of s values ​​for all nodes, or you can set a fixed set of s values ​​for each layer.

[0517] 2) The transformation tree constructed by RAHT has multiple layers. Traverse all layers and calculate s once for each layer. a The values ​​(a∈{0:YCb,1:YCr,2:CbCr}) represent the correlation coefficients between YCb, YCr and CbCr, respectively. They are stored in CrossCompPredCoeff[lvl][a] and sent to the bitstream.

[0518] Each s in the current layer a The calculation method can be:

[0519] For the current level 1 (LVL), calculate the AC transformation coefficients obtained by transforming the original attribute information of all nodes within the level, denoted as . and i represents the coefficient index order, and s of the current LVL layer is obtained using the following method. a :

[0520] Calculate s three times respectively:

[0521] In the first calculation, x1 = Y, x2 = Cb, the first parameter s is obtained. YCb ;

[0522] The second time, x1 = Y, x2 = Cr, the second parameter s is calculated. YCr ;

[0523] The third time, x1 = Cb, x2 = Cr, the third parameter s is calculated. CbCr .

[0524] Alternatively, only the parameters s of a portion of the transformation tree can be computed. a For example, only calculate s for layers with a number of layers less than or equal to 3. a .

[0525] 3) Traverse all layers. Suppose that the current node j of the current LVL layer consists of 2*2*2 child nodes. Each node can obtain multiple transform coefficients. When performing inter-component prediction, the transform coefficients of this node are calculated from the transform coefficients that have been encoded and reconstructed in the previous sequence.

[0526] You can calculate an s for each transformation coefficient, or you can group n nodes together and calculate only one s for each group (n can be 1 or an integer greater than 1).

[0527] Meanwhile, the range of encoded transform coefficients used to calculate s can be all transform coefficients already encoded in the same layer, the first m transform coefficients already encoded in the same layer, or all transform coefficients of the first k nodes already encoded in the same layer. Calculate s three times:

[0528] In the first calculation, x1 = Y, x2 = Cb, the first parameter s is obtained. YCb ;

[0529] The second time, x1 = Y, x2 = Cr, the second parameter s is calculated. YCr ;

[0530] The third time, x1 = Cb, x2 = Cr, the third parameter s is calculated. CbCr .

[0531] Alternatively, only the parameters s of a portion of the transformation tree can be computed. a For example, only calculate s for layers with a number of layers less than or equal to 3.

[0532] Regarding the method for calculating s above:

[0533] The fitting coefficients s between Y and Cb YCb In terms of calculation, the components involved in the fitting are as follows:

[0534] The Y-component transform coefficients, which are pre-encoded, quantized, and then inversely quantized, are the reconstructed Y-component transform coefficients Res. Y_recon ;

[0535] The transform coefficients (i.e., Res′) of the pre-encoded, quantized, and dequantized Cb components. Cb ) plus (s YCb *The Y component transform coefficients after inverse quantization are the reconstructed Cb transform coefficients Res. Cb__recon That is, the second reconstruction transformation coefficient.

[0536] The fitting coefficient s between Y and Cr YCr In terms of calculation, the components involved in the fitting are as follows:

[0537] The Y-component transform coefficients, which are pre-encoded, quantized, and then inversely quantized, are the reconstructed Y-component transform coefficients Res. Y_recon ;

[0538] The transform coefficients (i.e., Res″) of the Cr component after pre-encoded quantization and inverse quantization. Cr ) plus (s CbCr *The Cb component transformation coefficients after dequantization) plus (s YCr *The Y component transform coefficients after inverse quantization are the reconstructed Cr transform coefficients Res. Cr__recon That is, the third reconstruction transformation coefficient.

[0539] The fitting coefficient s between Cb and Cr YCr In terms of calculation, the components involved in the fitting are as follows:

[0540] The transform coefficients Res′ of the pre-encoded quantized and inverse-quantized Cb components Cb , which is the first residual of the reconstructed Cb transform coefficients;

[0541] Transform coefficients (Res″) of the Cr component after pre-encoded quantization and inverse quantization Cr ) plus (s CbCr *The Cb component transform coefficients after inverse quantization, which is the first residual Res′ of the reconstructed Cr transform coefficients. Cr .

[0542] In this method, s can be calculated from the encoded information, so s does not need to be passed in the bitstream.

[0543] II. Taking the calculation of the third residual transform coefficients at the encoding end according to the first or second method described above as an example:

[0544] First, the transform coefficients of the Y channel are encoded, and then quantized and dequantized to obtain the reconstructed Y channel transform coefficients (i.e., the first reconstructed transform coefficients) Res. Y_recon Further prediction processing is performed on the transform coefficients of the Cb channel to obtain the first residual transform coefficients Res. Cb ′: Res′Cb =Res Cb -s YCb ·Res Y_recon

[0545] Then for Res Cb Perform subsequent quantization and dequantization (plus s) YCb ·Res Y_recon The second reconstruction transform coefficients Res were obtained. Cb__recon ;

[0546] Res, the reconstruction transform coefficients of the Y channel Y_recon Or Cb reconstruction transformation coefficients Res Cb__recon The third residual transform coefficient Res is obtained by predicting the transform coefficients of the Cr channel. Cr ′, specifically as follows:

[0547] First, a parameter numslayer (i.e., the first threshold) is set. This parameter is used to select the prediction mode of the Cr component corresponding to different layers. This parameter can be passed into the bitstream.

[0548] Calculate the linearity coefficient s between the transform coefficients of the Y channel and the transform coefficients of the Cr channel, respectively. YCr (Second parameter) and the linear coefficient s between the transformation coefficients of the Cb channel and the Cr channel. CbCr (Third parameter).

[0549] Perform the following judgment: If the current level is greater than numslayer:

[0550] If the current node's s CbCr If the value is not 0, then the transform coefficients Res are reconstructed using Cb. Cb__recon The Res channel's transformation coefficients are predicted and processed to obtain the Res channel. Cr ′: Res′ Cr =Res Cr -s CbCr ·Res Cb_recon

[0551] The current node's s CbCr If the value is 0, then the transform coefficients Res are reconstructed using Y. Y__recon The Res channel's transformation coefficients are predicted and processed to obtain the Res channel. Cr ′: Res′ Cr =Res Cr -s YCr ·Res Y_recon

[0552] If the current lvl layer is less than or equal to numslayer:

[0553] If the current node's s YCr If the value is not 0, then the transform coefficients Res are reconstructed using Y. Y__recon The Res channel's transformation coefficients are predicted and processed to obtain the Res channel. Cr ′: Res′ Cr =Res Cr -s YCr ·Res Y_recon

[0554] The current node's s YCr If the value is 0, then the transform coefficients Res are reconstructed using Cb. Cb__recon The Res channel's transformation coefficients are predicted and processed to obtain the Res channel. Cr ′: Res′ Cr =Res Cr -s CbCr ·Res Cb_recon

[0555] For Res Cr Subsequent quantization and entropy encoding are performed to obtain the third reconstructed transform coefficients Res. Cr_recon .

[0556] For the first parameter s YCb The second parameter s YCr And the third parameter s CbCr The fitting method is as follows:

[0557] 1) Fitting coefficients s between Y and Cb YCb In terms of calculation, the components involved in the fitting are as follows:

[0558] The Y component transform coefficients after the previous encoded quantization and inverse quantization are the reconstructed Y transform coefficients.

[0559] The transform coefficients of the pre-encoded, quantized, and inverse-quantized Cb components plus (s) YCb The Y component transformation coefficients after inverse quantization are the reconstructed Cb transformation coefficients.

[0560] 2) Fitting coefficients s between Y and Cr YCr In terms of calculation, the components involved in the fitting are as follows:

[0561] The Y component transform coefficients after the previous encoded quantization and inverse quantization are the reconstructed Y transform coefficients.

[0562] The transform coefficients of the Cr component after pre-encoded quantization and inverse quantization are added to (s) CbCr *Cb component transformation coefficients after dequantization) or (s YCr The Y component transformation coefficients after inverse quantization are the reconstructed Cr transformation coefficients.

[0563] 3) Fit coefficients s between Cb and Cr CbCr In terms of calculation, the components involved in the fitting are as follows:

[0564] The Cb component transform coefficients after the previous encoded quantization and inverse quantization are the reconstructed Cb transform coefficients.

[0565] The transform coefficients of the Cr component after pre-encoded quantization and inverse quantization are added to (s) CbCr *Cb component transformation coefficients after dequantization) or (s YCr The Y component transformation coefficients after inverse quantization are the reconstructed Cr transformation coefficients.

[0566] In this embodiment, the correlation between color and chroma channels is used to calculate the reconstruction transformation coefficients of each component. By removing redundancy between components, the coding efficiency can be improved.

[0567] In the embodiments of this application, the encoding end first uses the correlation between luminance and the two chrominance components to remove redundancy between components once, and then uses the correlation of the CbCr channel to remove redundancy between components once more; or, it first uses the correlation between Y and Cb components to remove redundancy between Y and Cb components once, and then uses the correlation of the CbCr channel to remove redundancy between CbCr components once more; this can effectively reduce the bitstream.

[0568] In embodiments of this application, the encoding end uses the first reconstructed transform coefficients corresponding to the luminance component of the node attribute information to predict and encode the transform coefficients of the first chrominance component, thereby obtaining the second residual transform coefficients and the second reconstructed transform coefficients corresponding to the first chrominance component. Then, utilizing the correlation between the luminance component, the first chrominance component, and the second chrominance component, the third residual transform coefficients corresponding to the second chrominance component are calculated through various methods. By calculating the reconstructed information based on the correlation between each component and removing redundancy multiple times, the encoding efficiency can be improved.

[0569] The attribute information decoding and encoding method provided in this application can be executed by a geometric reconstruction device. This application uses an attribute information decoding and encoding device executing the attribute information decoding and encoding method as an example to illustrate the attribute information decoding and encoding device provided in this application.

[0570] As shown in Figure 6, this application embodiment provides an attribute information decoding device 600, applied at a decoding end, the device comprising:

[0571] The first decoding module 610 is used to decode and dequantize the data to be decoded to obtain the reconstruction transform coefficients corresponding to each node; the reconstruction transform coefficients are the reconstruction transform coefficients of the transform coefficients corresponding to the attribute information of each node; the reconstruction transform coefficients include: the first reconstruction transform coefficient corresponding to the luminance component of the transform coefficient, the second reconstruction residual transform coefficient corresponding to the first chrominance component of the transform coefficient, and the third reconstruction residual transform coefficient corresponding to the second chrominance component of the transform coefficient.

[0572] The first determining module 620 is used to determine the second reconstruction transformation coefficient corresponding to the first chromaticity component based on the first reconstruction transformation coefficient and the second reconstruction residual transformation coefficient.

[0573] The first processing module 630 is configured to perform at least one of the following at the decoding end:

[0574] Based on the second reconstruction transformation coefficient and the third reconstruction residual transformation coefficient, determine the third reconstruction transformation coefficient corresponding to the second chromaticity component;

[0575] Based on the first reconstruction transformation coefficient and the third reconstruction residual transformation coefficient, determine the third reconstruction transformation coefficient corresponding to the second chromaticity component;

[0576] The third reconstruction transformation coefficient corresponding to the second chromaticity component is determined based on the first reconstruction transformation coefficient, the second reconstruction transformation coefficient, and the third reconstruction residual transformation coefficient.

[0577] Optionally, the first determining module is specifically used for:

[0578] The step of determining the second reconstruction transformation coefficient corresponding to the first chromaticity component based on the first reconstruction transformation coefficient and the second reconstruction residual transformation coefficient includes:

[0579] The second reconstruction transformation coefficients are determined based on the second reconstruction residual transformation coefficients and the prediction compensation for the first chromaticity component;

[0580] The prediction compensation of the first chromaticity component is determined based on the first reconstruction transform coefficient and the first parameter, wherein the first parameter is used to represent the linear relationship between the luminance component and the first chromaticity component.

[0581] Optionally, the first determining module is specifically used for:

[0582] The second reconstruction transformation coefficient is obtained by summing the product of the first reconstruction transformation coefficient and the first parameter with the second reconstruction residual transformation coefficient.

[0583] The first parameter is used to represent the linear relationship between the luminance component and the first chrominance component.

[0584] Optionally, the first processing module is specifically used for:

[0585] The third reconstruction transformation coefficients are determined based on the third reconstruction residual transformation coefficients and the first prediction compensation for the second chromaticity component;

[0586] The prediction compensation of the second chromaticity component is determined based on the third parameter and the second reconstruction transform coefficient. The third parameter is used to represent the linear relationship between the first chromaticity component and the second chromaticity component.

[0587] Optionally, the first processing module is specifically used for:

[0588] The third reconstruction transformation coefficient is obtained by summing the product of the second reconstruction transformation coefficient and the third parameter with the third reconstruction residual transformation coefficient.

[0589] The third parameter is used to represent the linear relationship between the first chromaticity component and the second chromaticity component.

[0590] Optionally, the first processing module is specifically used for:

[0591] The third reconstruction transformation coefficients are determined based on the third reconstruction residual transformation coefficients and the second prediction compensation for the second chromaticity component;

[0592] The second prediction compensation of the second chromaticity component is determined based on the second parameter and the first reconstruction transform coefficient. The second parameter is used to represent the linear relationship between the luminance component and the second chromaticity component.

[0593] Optionally, the first processing module is specifically used for:

[0594] The third reconstruction transformation coefficient is obtained by summing the product of the first reconstruction transformation coefficient and the second parameter with the third reconstruction residual transformation coefficient.

[0595] The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component.

[0596] Optionally, if the first condition is met, the decoding end determines the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the second reconstruction transformation coefficient and the third reconstruction residual transformation coefficient.

[0597] The first condition includes one of the following:

[0598] For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is not 0;

[0599] For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is 0;

[0600] The first threshold is obtained by decoding the bitstream.

[0601] Optionally, if the second condition is met, the decoding end determines the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the first reconstruction transformation coefficient and the third reconstruction residual transformation coefficient.

[0602] The second condition includes one of the following:

[0603] For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is 0;

[0604] For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is not 0;

[0605] The first threshold is obtained by decoding the bitstream.

[0606] Optionally, the first processing module is specifically used for:

[0607] The third reconstruction transformation coefficient is determined based on the first prediction compensation for the second chromaticity component, the second prediction compensation for the second chromaticity component, and the third reconstruction residual transformation coefficient.

[0608] The prediction compensation of the second chromaticity component is determined based on the third parameter and the second reconstruction transform coefficient, and the second prediction compensation of the second chromaticity component is determined based on the second parameter and the first reconstruction transform coefficient.

[0609] The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component, and the third parameter is used to represent the linear relationship between the first chrominance component and the second chrominance component.

[0610] Optionally, the first processing module is specifically used for:

[0611] The product of the second reconstruction transformation coefficient and the third parameter is summed with the third reconstruction residual transformation coefficient to obtain the first residual value of the third reconstruction transformation coefficient;

[0612] The third reconstruction transformation coefficient is obtained by summing the product of the first reconstruction transformation coefficient and the second parameter with the first residual value of the third reconstruction transformation coefficient.

[0613] The second parameter represents the linear relationship between the luminance component and the second chrominance component, and the third parameter represents the linear relationship between the first chrominance component and the second chrominance component.

[0614] Optionally, the device further includes:

[0615] The second determining module is used to determine target parameters, the target parameters including at least one of the following: a first parameter for representing the linear relationship between the luminance component and the first chrominance component, a second parameter for representing the linear relationship between the luminance component and the second chrominance component, and a third parameter for representing the linear relationship between the first chrominance component and the second chrominance component.

[0616] Optionally, the second determining module is specifically used for:

[0617] Decode the bitstream to obtain the target parameters;

[0618] For the transform tree corresponding to the point cloud, the target parameters corresponding to the undecoded nodes are calculated based on the reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree.

[0619] Optionally, the decoded transform coefficients within the same layer include one of the following:

[0620] All transform coefficients that have been decoded within the same layer;

[0621] The first m transform coefficients that have been decoded within the same layer, where m is greater than 1;

[0622] All transform coefficients of the first k decoded nodes within the same layer, where k is greater than 1.

[0623] Optionally, the second determining unit is specifically configured to perform at least one of the following:

[0624] The first parameter is determined based on the first reconstructed transform coefficient and the second reconstructed transform coefficient corresponding to the decoded transform coefficients in the same layer of the transform tree;

[0625] The second parameter is determined based on the first reconstructed transform coefficient and the third reconstructed transform coefficient corresponding to the decoded transform coefficients in the same layer of the transform tree;

[0626] The third parameter is determined based on the first residual value of the second and third reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree; or, the third parameter is determined based on the second and third reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree.

[0627] Optionally, the second determining module is specifically used for:

[0628] Decode the bitstream to obtain the first threshold;

[0629] For layers in the transform tree whose number of layers is less than or equal to the first threshold, the target parameters corresponding to the undecoded nodes are calculated based on the decoded transform coefficients within the same layer.

[0630] Optionally, the second determining module is specifically used for:

[0631] The first value is obtained by summing the products of the reconstructed transform coefficients corresponding to the first component and the reconstructed transform coefficients corresponding to the second component of the decoded transform coefficients in the same layer.

[0632] The second value is obtained by summing the squares of the reconstructed transform coefficients corresponding to the first component of the decoded transform coefficients within the same layer.

[0633] Calculate the ratio of the first value to the second value to obtain the target parameter corresponding to the first component;

[0634] Wherein, the first component and the second component are any two of the luminance component, the first chromaticity component and the second chromaticity component.

[0635] In embodiments of this application, the decoding end determines the reconstructed information of each attribute component based on the correlation between the various attribute components of a node. Specifically, based on the correlation between the luminance component and the first chrominance component, the reconstructed information of the first chrominance component is determined using the first reconstruction transform coefficients of the luminance component and the second reconstruction residual transform coefficients of the first chrominance component; the reconstructed information corresponding to the second chrominance component is determined based on the correlation between the luminance component and the second chrominance component, or based on the correlation between the first chrominance component and the second chrominance component. By considering the correlation between different components when reconstructing the attribute information of a node, the decoding end effectively reduces the bit rate and improves decoding efficiency.

[0636] The attribute information decoding device provided in this application embodiment can implement the various processes implemented in the method embodiment of FIG4 and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0637] As shown in Figure 7, this application embodiment also provides an attribute information encoding device 700, applied at an encoding end, the device comprising:

[0638] The transformation module 710 is used to perform Region Adaptive Hierarchical Transformation (RAHT) on each node to obtain the transformation coefficients corresponding to the attribute information of each node; the transformation coefficients include: luminance component, first chrominance component and second chrominance component.

[0639] The first encoding module 720 is used to predict and encode the first chromaticity component using the first reconstruction transform coefficients corresponding to the luminance component, and obtain the second residual transform coefficients corresponding to the first chromaticity component.

[0640] The third determining module 730 is used to determine the second reconstructing transformation coefficient corresponding to the first chromaticity component based on the first reconstructing transformation coefficient and the second residual transformation coefficient.

[0641] The second processing module 740 is configured to perform at least one of the following:

[0642] The second chromaticity component is predicted and encoded using the second reconstruction transform coefficients to obtain the third residual transform coefficients corresponding to the second chromaticity component.

[0643] The second chromaticity component is predicted and encoded using the first reconstruction transform coefficients to obtain the third residual transform coefficients corresponding to the second chromaticity component.

[0644] The second chromaticity component is predicted and encoded using the first reconstruction transform coefficients to obtain the first residual value of the third residual transform coefficients corresponding to the second chromaticity component; the first residual value is predicted and encoded using the second reconstruction transform coefficients to obtain the third residual transform coefficients.

[0645] Optionally, the first encoding module is specifically used for:

[0646] Using the first chromaticity component and the encoding loss of the first chromaticity component, the second residual transform coefficients corresponding to the first chromaticity component are determined;

[0647] The encoding loss of the first chroma component is determined based on a first parameter and a first reconstruction transform coefficient. The first parameter is used to represent the linear relationship between the luminance component and the first chroma component.

[0648] Optionally, the first encoding module is specifically used for:

[0649] Calculate the difference between the first chromaticity component and the product of the first parameter and the first reconstructed transform coefficient to obtain the second residual transform coefficient corresponding to the first chromaticity component;

[0650] The first parameter is used to represent the linear relationship between the luminance component and the first chrominance component.

[0651] Optionally, the second processing module is specifically used for:

[0652] Using the second chromaticity component and the first coding loss of the second chromaticity component, the third residual transform coefficient corresponding to the second chromaticity component is determined;

[0653] The first coding loss of the second chroma component is determined based on the third parameter and the second reconstruction transform coefficient, wherein the third parameter is used to represent the linear relationship between the first chroma component and the second chroma component.

[0654] Optionally, the second processing module is specifically used for:

[0655] Calculate the difference between the product of the second chromaticity component and the third parameter and the second reconstruction transform coefficient to obtain the third residual transform coefficient corresponding to the second chromaticity component;

[0656] The third parameter is used to represent the linear relationship between the first chromaticity component and the second chromaticity component.

[0657] Optionally, the second processing module is specifically used for:

[0658] The third residual transform coefficients corresponding to the second chromaticity component are determined using the second chromaticity component and the second coding loss of the second chromaticity component.

[0659] The second coding loss of the second chromaticity component is determined based on the second parameter and the first reconstruction transform coefficient. The second parameter is used to represent the linear relationship between the luminance component and the second chromaticity component.

[0660] Optionally, the second processing module is specifically used for:

[0661] Calculate the difference between the product of the second chromaticity component and the second parameter and the first reconstructed transform coefficient to obtain the third residual transform coefficient corresponding to the second chromaticity component;

[0662] The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component.

[0663] Optionally, if the first condition is met, the encoding end uses the second reconstruction transform coefficients to predict and encode the second chromaticity component to obtain the third residual transform coefficients corresponding to the second chromaticity component.

[0664] The first condition includes one of the following:

[0665] For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is not 0;

[0666] For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is 0.

[0667] Optionally, if the second condition is met, the encoding end uses the first reconstruction transform coefficients to predict and encode the second chromaticity component to obtain the third residual transform coefficients corresponding to the second chromaticity component.

[0668] The second condition includes one of the following:

[0669] For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is 0;

[0670] For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is not 0.

[0671] Optionally, the second processing module is specifically used for:

[0672] The first residual value of the third residual transform coefficient is determined based on the second chromaticity component and the second encoding loss of the second chromaticity component.

[0673] The third residual transform coefficients are determined based on the first residual value of the third residual transform coefficients and the second coding loss of the second chroma component;

[0674] Wherein, the first coding loss of the second chroma component is determined according to the third parameter and the second reconstruction transform coefficient, and the second coding loss of the second chroma component is determined according to the second parameter and the first reconstruction transform coefficient;

[0675] The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component, and the third parameter is used to represent the linear relationship between the first chrominance component and the second chrominance component.

[0676] Optionally, the second processing module is specifically used for:

[0677] Calculate the difference between the product of the second chromaticity component and the second parameter and the first reconstructed transform coefficient to obtain the first residual value of the third residual transform coefficient;

[0678] The difference between the first residual value and the product of the third parameter and the second reconstruction transform coefficient is calculated to obtain the third residual transform coefficient;

[0679] The second parameter represents the linear relationship between the luminance component and the second chrominance component; the third parameter represents the linear relationship between the first chrominance component and the second chrominance component.

[0680] Optionally, the device further includes:

[0681] The second encoding module is used to quantize and entropy encode the third residual transform coefficients to obtain the third reconstructed transform coefficients corresponding to the second chromaticity component.

[0682] Optionally, the device further includes:

[0683] The fourth determining module is used to determine target parameters, the target parameters including at least one of the following: a first parameter for representing the linear relationship between the luminance component and the first chrominance component, a second parameter for representing the linear relationship between the luminance component and the second chrominance component, and a third parameter for representing the linear relationship between the first chrominance component and the second chrominance component.

[0684] Optionally, the fourth determining module is configured to perform at least one of the following:

[0685] The target parameters are determined based on preset values;

[0686] For the transformation tree corresponding to the point cloud, the target parameters are calculated based on the transformation coefficients corresponding to the attribute information of all nodes in the same layer of the transformation tree.

[0687] For the transformation tree corresponding to the point cloud, the target parameters corresponding to the uncoded nodes are calculated based on the encoded transformation coefficients within the same layer of the transformation tree.

[0688] Optionally, the fourth determining module is specifically used for:

[0689] Determine the transformation coefficients corresponding to the attribute information of all nodes within the same layer of the transformation tree;

[0690] The first parameter corresponding to the layer is calculated using the luminance component and the first chrominance component in the transformation coefficients of all nodes in the same layer.

[0691] The second parameter corresponding to the layer is calculated using the luminance component and the second chrominance component in the transformation coefficients of all nodes in the same layer.

[0692] The third parameter corresponding to the layer is calculated using the first and second chromaticity components of the transformation coefficients of all nodes within the same layer.

[0693] Optionally, the encoded transform coefficients within the same layer include one of the following:

[0694] All transform coefficients already encoded within the same layer;

[0695] The first m transform coefficients encoded within the same layer, where m is greater than 1;

[0696] All transform coefficients of the first k encoded nodes within the same layer, where k is greater than 1.

[0697] Optionally, the fourth determining module is specifically used to perform at least one of the following:

[0698] The first parameter is determined based on the first reconstructed transform coefficient and the second reconstructed transform coefficient corresponding to the coded transform coefficients in the same layer of the transform tree;

[0699] The second parameter is determined based on the first reconstructed transform coefficient and the third reconstructed transform coefficient corresponding to the coded transform coefficients in the same layer of the transform tree;

[0700] The third parameter is determined based on the first residual value of the second and third reconstructed transform coefficients corresponding to the encoded transform coefficients in the same layer of the transform tree; or, the third parameter is determined based on the second and third reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree.

[0701] Optionally, the fourth determining module is specifically used for:

[0702] For layers in the transform tree whose number of layers is less than or equal to the first threshold, the target parameters corresponding to the undecoded nodes are calculated based on the decoded transform coefficients within the same layer.

[0703] Optionally, the fourth determining module is specifically used for:

[0704] The third value is obtained by summing the products of the reconstructed transform coefficients corresponding to the first component and the reconstructed transform coefficients corresponding to the second component of the encoded transform coefficients in the same layer.

[0705] The fourth value is obtained by summing the squares of the reconstructed transform coefficients corresponding to the first component of the encoded transform coefficients within the same layer.

[0706] Calculate the ratio of the third value to the fourth value to obtain the target parameter corresponding to the first component;

[0707] Wherein, the first component and the second component are any two of the luminance component, the first chromaticity component and the second chromaticity component.

[0708] Optionally, the device further includes:

[0709] The third encoding module is used to input the first threshold into the bitstream.

[0710] In embodiments of this application, the encoding end uses the first reconstructed transform coefficients corresponding to the luminance component of the node attribute information to predict and encode the transform coefficients of the first chrominance component, thereby obtaining the second residual transform coefficients and the second reconstructed transform coefficients corresponding to the first chrominance component. Then, utilizing the correlation between the luminance component, the first chrominance component, and the second chrominance component, the third residual transform coefficients corresponding to the second chrominance component are calculated through various methods. By calculating the reconstructed information based on the correlation between each component and removing redundancy multiple times, the encoding efficiency can be improved.

[0711] The attribute information encoding device provided in this application embodiment can implement the various processes implemented in the method embodiment of FIG5 and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0712] As shown in Figure 8, this application embodiment also provides an electronic device 800, including a processor 801 and a memory 802. The memory 802 stores programs or instructions that can run on the processor 801. For example, when the electronic device 800 is a decoding device, the program or instructions executed by the processor 801 implement the various steps of the above-mentioned attribute information decoding method embodiment and achieve the same technical effect. When the electronic device 800 is an encoding device, the program or instructions executed by the processor 801 implement the various steps of the above-mentioned attribute information encoding method embodiment and achieve the same technical effect. To avoid repetition, this will not be described again here. Optionally, the memory 802 can be the memory 102 or memory 113 in the embodiment shown in Figure 1, and the processor 601 can implement the functions of the encoder 200 or decoder 300 in the embodiments shown in Figures 1-3.

[0713] This application also provides an electronic device, including: a memory configured to store video data; and a processing circuit configured to implement the various steps of the decoding and encoding method embodiments of the attribute information described above. Optionally, the memory may be memory 102 or memory 113 in the embodiment shown in FIG1, and the processing circuit may implement the functions of encoder 200 or decoder 300 in the embodiments shown in FIG1-3.

[0714] This application also provides an electronic device, including a processor and a communication interface. The communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the steps in the method embodiments shown in FIG4 or FIG5. This device embodiment corresponds to the above method embodiment, and all implementation processes and methods of the above method embodiments can be applied to this terminal embodiment and can achieve the same technical effect.

[0715] The aforementioned electronic devices can be terminals or other devices besides terminals, such as servers, network attached storage (NAS), etc.

[0716] The terminal can be a mobile phone, tablet computer, laptop computer, notebook computer, personal digital assistant (PDA), handheld computer, netbook, ultra-mobile personal computer (UMPC), mobile internet device (MID), augmented reality (AR), virtual reality (VR) device, mixed reality (MR) device, robot, wearable device, flight vehicle, vehicle user equipment (VUE), shipboard device, pedestrian user equipment (PUE), smart home (home devices with wireless communication capabilities, such as refrigerators, televisions, washing machines, or furniture), game console, personal computer (PC), ATM or self-service machine, etc. Wearable devices include: smartwatches, smart bracelets, smart earphones, smart glasses, smart jewelry (smart bracelets, smart chains, smart rings, smart necklaces, smart anklets, smart anklets, etc.), smart wristbands, smart clothing, etc. Among these, in-vehicle devices can also be referred to as in-vehicle terminals, in-vehicle controllers, in-vehicle modules, in-vehicle components, in-vehicle chips, or in-vehicle units, etc. It should be noted that the embodiments in this application do not limit the specific type of terminal.

[0717] A server can be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server. A cloud server can provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), or cloud computing services based on big data and artificial intelligence platforms.

[0718] For example, the aforementioned electronic device may include, but is not limited to, the type of source device 100 or destination device 110 shown in FIG1.

[0719] Taking an electronic device as an example, Figure 9 is a schematic diagram of the hardware structure of a terminal that implements an embodiment of this application.

[0720] The terminal 900 includes, but is not limited to, at least some of the following components: radio frequency unit 901, network module 902, audio output unit 903, input unit 904, sensor 905, display unit 906, user input unit 907, interface unit 908, memory 909, and processor 910.

[0721] Those skilled in the art will understand that the terminal 900 may also include a power supply (such as a battery) for powering various components. The power supply can be logically connected to the processor 910 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The terminal structure shown in Figure 9 does not constitute a limitation on the terminal. The terminal may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0722] It should be understood that, in this embodiment, the input unit 904 may include a graphics processing unit (GPU) 9041 and a microphone 9042. The GPU 9041 processes image data of static images or videos obtained by an image acquisition device (such as a camera) in video acquisition mode or image acquisition mode, or it may process the obtained point cloud data. The display unit 906 may include a display panel 9061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, etc. The user input unit 907 includes at least one of a touch panel 9071 and other input devices 9072. The touch panel 9071 is also called a touch screen. The touch panel 9071 may include two parts: a touch detection device and a touch controller. Other input devices 9072 may include, but are not limited to, a physical keyboard, function keys (such as volume control buttons, power buttons, etc.), a trackball, a mouse, and a joystick, which will not be described in detail here.

[0723] In this embodiment, after receiving downlink data from the network-side device, the radio frequency unit 901 can transmit it to the processor 910 for processing; in addition, the radio frequency unit 901 can send uplink data to the network-side device. Typically, the radio frequency unit 901 includes, but is not limited to, antennas, amplifiers, transceivers, couplers, low-noise amplifiers, duplexers, etc.

[0724] The memory 909 can be used to store software programs or instructions, as well as various data. The memory 909 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 1309 may include volatile memory or non-volatile memory. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 909 in the embodiments of this application includes, but is not limited to, these and any other suitable types of memory.

[0725] Processor 910 may include one or more processing units; optionally, processor 910 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into processor 910.

[0726] Wherein, when the terminal is a decoding device:

[0727] The processor 910 is used to: decode and dequantize the data to be decoded to obtain the reconstruction transform coefficients corresponding to each node; the reconstruction transform coefficients are the reconstruction transform coefficients of the transform coefficients corresponding to the attribute information of each node; the reconstruction transform coefficients include: a first reconstruction transform coefficient corresponding to the luminance component of the transform coefficient, a second reconstruction residual transform coefficient corresponding to the first chrominance component of the transform coefficient, and a third reconstruction residual transform coefficient corresponding to the second chrominance component of the transform coefficient.

[0728] Based on the first reconstruction transformation coefficient and the second reconstruction residual transformation coefficient, determine the second reconstruction transformation coefficient corresponding to the first chromaticity component;

[0729] Perform at least one of the following:

[0730] Based on the second reconstruction transformation coefficient and the third reconstruction residual transformation coefficient, determine the third reconstruction transformation coefficient corresponding to the second chromaticity component;

[0731] Based on the first reconstruction transformation coefficient and the third reconstruction residual transformation coefficient, determine the third reconstruction transformation coefficient corresponding to the second chromaticity component;

[0732] The third reconstruction transformation coefficient corresponding to the second chromaticity component is determined based on the first reconstruction transformation coefficient, the second reconstruction transformation coefficient, and the third reconstruction residual transformation coefficient.

[0733] Optionally, the processor determines the second reconstruction transformation coefficients corresponding to the first chromaticity component based on the first reconstruction transformation coefficients and the second reconstruction residual transformation coefficients, including:

[0734] The second reconstruction transformation coefficients are determined based on the second reconstruction residual transformation coefficients and the prediction compensation for the first chromaticity component;

[0735] The prediction compensation of the first chromaticity component is determined based on the first reconstruction transform coefficient and the first parameter, wherein the first parameter is used to represent the linear relationship between the luminance component and the first chromaticity component.

[0736] Optionally, determining the second reconstruction transform coefficients based on the second reconstruction residual transform coefficients and the prediction compensation for the first chromaticity component includes:

[0737] The second reconstruction transformation coefficient is obtained by summing the product of the first reconstruction transformation coefficient and the first parameter with the second reconstruction residual transformation coefficient.

[0738] The first parameter is used to represent the linear relationship between the luminance component and the first chrominance component.

[0739] Optionally, the processor determines the third reconstruction transform coefficients corresponding to the second chromaticity component based on the second reconstruction transform coefficients and the third reconstruction residual transform coefficients, including:

[0740] The third reconstruction transformation coefficients are determined based on the third reconstruction residual transformation coefficients and the first prediction compensation for the second chromaticity component;

[0741] The prediction compensation of the second chromaticity component is determined based on the third parameter and the second reconstruction transform coefficient. The third parameter is used to represent the linear relationship between the first chromaticity component and the second chromaticity component.

[0742] Optionally, determining the third reconstruction transform coefficients based on the third reconstruction residual transform coefficients and the first prediction compensation for the second chromaticity component includes:

[0743] The third reconstruction transformation coefficient is obtained by summing the product of the second reconstruction transformation coefficient and the third parameter with the third reconstruction residual transformation coefficient.

[0744] The third parameter is used to represent the linear relationship between the first chromaticity component and the second chromaticity component.

[0745] Optionally, the processor determines the third reconstruction transform coefficients corresponding to the second chromaticity component based on the first reconstruction transform coefficients and the third reconstruction residual transform coefficients, including:

[0746] The third reconstruction transformation coefficients are determined based on the third reconstruction residual transformation coefficients and the second prediction compensation for the second chromaticity component;

[0747] The second prediction compensation of the second chromaticity component is determined based on the second parameter and the first reconstruction transform coefficient. The second parameter is used to represent the linear relationship between the luminance component and the second chromaticity component.

[0748] Optionally, the third reconstruction transform coefficients are determined based on the third reconstruction residual transform coefficients and the second prediction compensation for the second chromaticity component, including:

[0749] The third reconstruction transformation coefficient is obtained by summing the product of the first reconstruction transformation coefficient and the second parameter with the third reconstruction residual transformation coefficient.

[0750] The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component.

[0751] Optionally, if the first condition is met, the decoding end determines the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the second reconstruction transformation coefficient and the third reconstruction residual transformation coefficient.

[0752] The first condition includes one of the following:

[0753] For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is not 0;

[0754] For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is 0;

[0755] The first threshold is obtained by decoding the bitstream.

[0756] Optionally, if the second condition is met, the decoding end determines the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the first reconstruction transformation coefficient and the third reconstruction residual transformation coefficient.

[0757] The second condition includes one of the following:

[0758] For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is 0;

[0759] For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is not 0;

[0760] The first threshold is obtained by decoding the bitstream.

[0761] Optionally, the processor determines the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the first reconstruction transformation coefficient, the second reconstruction transformation coefficient, and the third reconstruction residual transformation coefficient, including:

[0762] The third reconstruction transformation coefficient is determined based on the first prediction compensation for the second chromaticity component, the second prediction compensation for the second chromaticity component, and the third reconstruction residual transformation coefficient.

[0763] The prediction compensation of the second chromaticity component is determined based on the third parameter and the second reconstruction transform coefficient, and the second prediction compensation of the second chromaticity component is determined based on the second parameter and the first reconstruction transform coefficient.

[0764] The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component, and the third parameter is used to represent the linear relationship between the first chrominance component and the second chrominance component.

[0765] Optionally, the third reconstruction transformation coefficient is determined based on the first prediction compensation for the second chromaticity component, the second prediction compensation for the second chromaticity component, and the third reconstruction residual transformation coefficient, including:

[0766] The product of the second reconstruction transformation coefficient and the third parameter is summed with the third reconstruction residual transformation coefficient to obtain the first residual value of the third reconstruction transformation coefficient;

[0767] The third reconstruction transformation coefficient is obtained by summing the product of the first reconstruction transformation coefficient and the second parameter with the first residual value of the third reconstruction transformation coefficient.

[0768] The second parameter represents the linear relationship between the luminance component and the second chrominance component, and the third parameter represents the linear relationship between the first chrominance component and the second chrominance component.

[0769] Optionally, the processor is further configured to:

[0770] Determine target parameters, which include at least one of the following: a first parameter for representing the linear relationship between the luminance component and the first chrominance component, a second parameter for representing the linear relationship between the luminance component and the second chrominance component, and a third parameter for representing the linear relationship between the first chrominance component and the second chrominance component.

[0771] Optionally, the processor determines the target parameters, including at least one of the following:

[0772] Decode the bitstream to obtain the target parameters;

[0773] For the transform tree corresponding to the point cloud, the target parameters corresponding to the undecoded nodes are calculated based on the reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree.

[0774] Optionally, the decoded transform coefficients within the same layer include one of the following:

[0775] All transform coefficients that have been decoded within the same layer;

[0776] The first m transform coefficients that have been decoded within the same layer, where m is greater than 1;

[0777] All transform coefficients of the first k decoded nodes within the same layer, where k is greater than 1.

[0778] Optionally, the processor calculates the target parameters corresponding to the undecoded nodes based on the decoded transform coefficients within the same layer of the transform tree, including at least one of the following:

[0779] The first parameter is determined based on the first reconstructed transform coefficient and the second reconstructed transform coefficient corresponding to the decoded transform coefficients in the same layer of the transform tree;

[0780] The second parameter is determined based on the first reconstructed transform coefficient and the third reconstructed transform coefficient corresponding to the decoded transform coefficients in the same layer of the transform tree;

[0781] The third parameter is determined based on the first residual value of the second and third reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree; or, the third parameter is determined based on the second and third reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree.

[0782] Optionally, the processor calculates the target parameters corresponding to the undecoded nodes based on the decoded transform coefficients within the same layer of the transform tree, including:

[0783] Decode the bitstream to obtain the first threshold;

[0784] For layers in the transform tree whose number of layers is less than or equal to the first threshold, the target parameters corresponding to the undecoded nodes are calculated based on the decoded transform coefficients within the same layer.

[0785] Optionally, the processor calculates the target parameters corresponding to the undecoded nodes based on the decoded transform coefficients within the same layer of the transform tree, including:

[0786] The first value is obtained by summing the products of the reconstructed transform coefficients corresponding to the first component and the reconstructed transform coefficients corresponding to the second component of the decoded transform coefficients in the same layer.

[0787] The second value is obtained by summing the squares of the reconstructed transform coefficients corresponding to the first component of the decoded transform coefficients within the same layer.

[0788] Calculate the ratio of the first value to the second value to obtain the target parameter corresponding to the first component;

[0789] Wherein, the first component and the second component are any two of the luminance component, the first chromaticity component and the second chromaticity component.

[0790] Wherein, when the terminal is an encoding device:

[0791] The processor 910 performs Region Adaptive Hierarchical Transformation (RAHT) on each node to obtain the transformation coefficients corresponding to the attribute information of each node; the transformation coefficients include: luminance component, first chrominance component and second chrominance component.

[0792] Using the first reconstruction transform coefficients corresponding to the luminance component, the first chrominance component is predicted and encoded to obtain the second residual transform coefficients corresponding to the first chrominance component.

[0793] Based on the first reconstruction transform coefficient and the second residual transform coefficient, determine the second reconstruction transform coefficient corresponding to the first chromaticity component;

[0794] Perform at least one of the following:

[0795] The second chromaticity component is predicted and encoded using the second reconstruction transform coefficients to obtain the third residual transform coefficients corresponding to the second chromaticity component.

[0796] The second chromaticity component is predicted and encoded using the first reconstruction transform coefficients to obtain the third residual transform coefficients corresponding to the second chromaticity component.

[0797] The second chromaticity component is predicted and encoded using the first reconstruction transform coefficients to obtain the first residual value of the third residual transform coefficients corresponding to the second chromaticity component; the first residual value is predicted and encoded using the second reconstruction transform coefficients to obtain the third residual transform coefficients.

[0798] Optionally, the processor uses the first reconstruction transform coefficients corresponding to the luminance component to perform predictive encoding on the first chrominance component to obtain the second residual transform coefficients corresponding to the first chrominance component, including:

[0799] Using the first chromaticity component and the encoding loss of the first chromaticity component, the second residual transform coefficients corresponding to the first chromaticity component are determined;

[0800] The encoding loss of the first chroma component is determined based on a first parameter and a first reconstruction transform coefficient. The first parameter is used to represent the linear relationship between the luminance component and the first chroma component.

[0801] Optionally, determining the second residual transform coefficients corresponding to the first chroma component using the first chroma component and its encoding loss includes:

[0802] Calculate the difference between the first chromaticity component and the product of the first parameter and the first reconstructed transform coefficient to obtain the second residual transform coefficient corresponding to the first chromaticity component;

[0803] The first parameter is used to represent the linear relationship between the luminance component and the first chrominance component.

[0804] Optionally, the processor uses the second reconstructed transform coefficients to predictively encode the second chroma component to obtain the third residual transform coefficients corresponding to the second chroma component, including:

[0805] Using the second chromaticity component and the first coding loss of the second chromaticity component, the third residual transform coefficient corresponding to the second chromaticity component is determined;

[0806] The first coding loss of the second chroma component is determined based on the third parameter and the second reconstruction transform coefficient, wherein the third parameter is used to represent the linear relationship between the first chroma component and the second chroma component.

[0807] Optionally, determining the third residual transform coefficients corresponding to the second chroma component using the second chroma component and the first coding loss of the second chroma component includes:

[0808] Calculate the difference between the product of the second chromaticity component and the third parameter and the second reconstruction transform coefficient to obtain the third residual transform coefficient corresponding to the second chromaticity component;

[0809] The third parameter is used to represent the linear relationship between the first chromaticity component and the second chromaticity component.

[0810] Optionally, the processor uses the first reconstructed transform coefficients to predictively encode the second chroma component to obtain the third residual transform coefficients corresponding to the second chroma component, including:

[0811] The third residual transform coefficients corresponding to the second chromaticity component are determined using the second chromaticity component and the second coding loss of the second chromaticity component.

[0812] The second coding loss of the second chromaticity component is determined based on the second parameter and the first reconstruction transform coefficient. The second parameter is used to represent the linear relationship between the luminance component and the second chromaticity component.

[0813] Optionally, determining the third residual transform coefficients corresponding to the second chroma component using the second chroma component and the second coding loss of the second chroma component includes:

[0814] Calculate the difference between the product of the second chromaticity component and the second parameter and the first reconstructed transform coefficient to obtain the third residual transform coefficient corresponding to the second chromaticity component;

[0815] The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component.

[0816] Optionally, when the first condition is met, the processor encoding end uses the second reconstruction transform coefficients to predictively encode the second chroma component to obtain the third residual transform coefficients corresponding to the second chroma component.

[0817] The first condition includes one of the following:

[0818] For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is not 0;

[0819] For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is 0.

[0820] Optionally, when the second condition is met, the processor encoding end uses the first reconstruction transform coefficients to predict and encode the second chromaticity component to obtain the third residual transform coefficients corresponding to the second chromaticity component.

[0821] The second condition includes one of the following:

[0822] For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is 0;

[0823] For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is not 0.

[0824] Optionally, the processor uses the first reconstructed transform coefficients to predictively encode the second chroma component to obtain the first residual value of the third residual transform coefficients corresponding to the second chroma component; and uses the second reconstructed transform coefficients to predictively encode the first residual value to obtain the third residual transform coefficients, including:

[0825] The first residual value of the third residual transform coefficient is determined based on the second chromaticity component and the second encoding loss of the second chromaticity component.

[0826] The third residual transform coefficients are determined based on the first residual value of the third residual transform coefficients and the second coding loss of the second chroma component;

[0827] Wherein, the first coding loss of the second chroma component is determined according to the third parameter and the second reconstruction transform coefficient, and the second coding loss of the second chroma component is determined according to the second parameter and the first reconstruction transform coefficient;

[0828] The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component, and the third parameter is used to represent the linear relationship between the first chrominance component and the second chrominance component.

[0829] Optionally, determining the first residual value of the third residual transform coefficient based on the second chroma component and the second coding loss of the second chroma component includes:

[0830] Calculate the difference between the product of the second chromaticity component and the second parameter and the first reconstructed transform coefficient to obtain the first residual value of the third residual transform coefficient;

[0831] The step of determining the third residual transform coefficients based on the first residual value of the third residual transform coefficients and the second coding loss of the second chroma component includes:

[0832] The difference between the first residual value and the product of the third parameter and the second reconstruction transform coefficient is calculated to obtain the third residual transform coefficient;

[0833] The second parameter represents the linear relationship between the luminance component and the second chrominance component; the third parameter represents the linear relationship between the first chrominance component and the second chrominance component.

[0834] Optionally, the processor is further configured to:

[0835] The third residual transform coefficients are quantized and entropy encoded to obtain the third reconstructed transform coefficients corresponding to the second chromaticity component.

[0836] Optionally, the processor is further configured to:

[0837] Determine target parameters, which include at least one of the following: a first parameter for representing the linear relationship between the luminance component and the first chrominance component, a second parameter for representing the linear relationship between the luminance component and the second chrominance component, and a third parameter for representing the linear relationship between the first chrominance component and the second chrominance component.

[0838] Optionally, the processor determines the target parameters, including at least one of the following:

[0839] The target parameters are determined based on preset values;

[0840] For the transformation tree corresponding to the point cloud, the target parameters are calculated based on the transformation coefficients corresponding to the attribute information of all nodes in the same layer of the transformation tree.

[0841] For the transformation tree corresponding to the point cloud, the target parameters corresponding to the uncoded nodes are calculated based on the encoded transformation coefficients within the same layer of the transformation tree.

[0842] Optionally, for the transformation tree corresponding to the point cloud, the target parameters are calculated based on the transformation coefficients corresponding to the attribute information of all nodes in the same layer of the transformation tree, including:

[0843] Determine the transformation coefficients corresponding to the attribute information of all nodes within the same layer of the transformation tree;

[0844] The first parameter corresponding to the layer is calculated using the luminance component and the first chrominance component in the transformation coefficients of all nodes in the same layer.

[0845] The second parameter corresponding to the layer is calculated using the luminance component and the second chrominance component in the transformation coefficients of all nodes in the same layer.

[0846] The third parameter corresponding to the layer is calculated using the first and second chromaticity components of the transformation coefficients of all nodes within the same layer.

[0847] Optionally, the encoded transform coefficients within the same layer include one of the following:

[0848] All transform coefficients already encoded within the same layer;

[0849] The first m transform coefficients encoded within the same layer, where m is greater than 1;

[0850] All transform coefficients of the first k encoded nodes within the same layer, where k is greater than 1.

[0851] Optionally, the processor calculates the target parameters corresponding to the uncoded nodes based on the encoded transform coefficients within the same layer of the transform tree, including at least one of the following:

[0852] The first parameter is determined based on the first reconstructed transform coefficient and the second reconstructed transform coefficient corresponding to the coded transform coefficients in the same layer of the transform tree;

[0853] The second parameter is determined based on the first reconstructed transform coefficient and the third reconstructed transform coefficient corresponding to the coded transform coefficients in the same layer of the transform tree;

[0854] The third parameter is determined based on the first residual value of the second and third reconstructed transform coefficients corresponding to the encoded transform coefficients in the same layer of the transform tree; or, the third parameter is determined based on the second and third reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree.

[0855] Optionally, the processor calculates the target parameters corresponding to the uncoded nodes based on the encoded transform coefficients within the same layer of the transform tree, including:

[0856] For layers in the transform tree whose number of layers is less than or equal to the first threshold, the target parameters corresponding to the undecoded nodes are calculated based on the decoded transform coefficients within the same layer.

[0857] Optionally, the processor calculates the target parameters corresponding to the uncoded nodes based on the encoded transform coefficients within the same layer of the transform tree, including:

[0858] The third value is obtained by summing the products of the reconstructed transform coefficients corresponding to the first component and the reconstructed transform coefficients corresponding to the second component of the encoded transform coefficients in the same layer.

[0859] The fourth value is obtained by summing the squares of the reconstructed transform coefficients corresponding to the first component of the encoded transform coefficients within the same layer.

[0860] Calculate the ratio of the third value to the fourth value to obtain the target parameter corresponding to the first component;

[0861] Wherein, the first component and the second component are any two of the luminance component, the first chromaticity component and the second chromaticity component.

[0862] Optionally, the processor is further configured to:

[0863] The first threshold is passed into the bitstream.

[0864] In embodiments of this application, the encoding end uses the first reconstructed transform coefficients corresponding to the luminance component of the node attribute information to predict and encode the transform coefficients of the first chrominance component, thereby obtaining the second residual transform coefficients and the second reconstructed transform coefficients corresponding to the first chrominance component. Then, utilizing the correlation between the luminance component, the first chrominance component, and the second chrominance component, the third residual transform coefficients corresponding to the second chrominance component are calculated through various methods. By calculating the reconstructed information based on the correlation between each component and removing redundancy multiple times, the encoding efficiency can be improved.

[0865] It is understood that the implementation process of each implementation method mentioned in this embodiment can refer to the relevant description of the geometric reconstruction method in the method embodiment and achieve the same or corresponding technical effect. To avoid repetition, it will not be described again here.

[0866] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described geometric reconstruction method embodiments and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0867] The processor mentioned above is the processor in the terminal described in the above embodiments. The readable storage medium includes computer-readable storage media, such as ROM, RAM, magnetic disk, or optical disk. In some examples, the readable storage medium may be a non-transient readable storage medium.

[0868] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-mentioned attribute information decoding and encoding method embodiments, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0869] It should be understood that the chips mentioned in the embodiments of this application may include system-on-a-chip (also known as system chip, chip system, or system-on-a-chip) or discrete display chips, etc.

[0870] This application also provides a computer program / program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the above-described method embodiments for decoding and encoding attribute information, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0871] This application embodiment also provides an encoding / decoding system, including: an encoding end device and a decoding end device. The encoding end device can be used to execute the steps of the encoding method for attribute information of the encoding end as described above, and the decoding end device can be used to execute the steps of the decoding method for attribute information of the decoding end as described above.

[0872] This application also provides a computer program product, including computer instructions. When the computer instructions are executed by a processor, they implement the steps of the above-mentioned attribute information decoding method or the steps of the above-mentioned attribute information encoding method, and can achieve the same technical effect. To avoid repetition, they will not be described again here.

[0873] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0874] From the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of computer software products plus necessary general-purpose hardware platforms, and of course, they can also be implemented by hardware. The computer software product is stored in a storage medium (such as ROM, RAM, magnetic disk, optical disk, etc.) and includes several instructions to cause the terminal or network-side device to execute the methods described in the various embodiments of this application.

[0875] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other implementations under the guidance of this application without departing from the spirit and scope of the claims. All of these implementations are within the protection scope of this application.

Claims

1. A method for decoding attribute information, comprising: The decoding end decodes and dequantizes the data to be decoded to obtain the reconstruction transform coefficients corresponding to each node; The reconstructed transformation coefficients are the reconstructed transformation coefficients corresponding to the attribute information of each node. The reconstructed transformation coefficients include: a first reconstructed transformation coefficient corresponding to the luminance component of the transformation coefficients, a second reconstructed residual transformation coefficient corresponding to the first chrominance component of the transformation coefficients, and a third reconstructed residual transformation coefficient corresponding to the second chrominance component of the transformation coefficients; The decoding end determines the second reconstruction transformation coefficient corresponding to the first chromaticity component based on the first reconstruction transformation coefficient and the second reconstruction residual transformation coefficient; The decoding end performs at least one of the following: Based on the second reconstruction transformation coefficient and the third reconstruction residual transformation coefficient, determine the third reconstruction transformation coefficient corresponding to the second chromaticity component; Based on the first reconstruction transformation coefficient and the third reconstruction residual transformation coefficient, determine the third reconstruction transformation coefficient corresponding to the second chromaticity component; The third reconstruction transformation coefficient corresponding to the second chromaticity component is determined based on the first reconstruction transformation coefficient, the second reconstruction transformation coefficient, and the third reconstruction residual transformation coefficient.

2. The method according to claim 1, wherein, The step of determining the second reconstruction transformation coefficient corresponding to the first chromaticity component based on the first reconstruction transformation coefficient and the second reconstruction residual transformation coefficient includes: The second reconstruction transformation coefficients are determined based on the second reconstruction residual transformation coefficients and the prediction compensation for the first chromaticity component; The prediction compensation of the first chromaticity component is determined based on the first reconstruction transform coefficient and the first parameter, wherein the first parameter is used to represent the linear relationship between the luminance component and the first chromaticity component.

3. The method according to claim 2, wherein, The step of determining the second reconstruction transformation coefficients based on the second reconstruction residual transformation coefficients and the prediction compensation for the first chromaticity component includes: The second reconstruction transformation coefficient is obtained by summing the product of the first reconstruction transformation coefficient and the first parameter with the second reconstruction residual transformation coefficient.

4. The method according to claim 1, wherein, The step of determining the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the second reconstruction transformation coefficient and the third reconstruction residual transformation coefficient includes: The third reconstruction transformation coefficients are determined based on the third reconstruction residual transformation coefficients and the first prediction compensation for the second chromaticity component; The prediction compensation of the second chromaticity component is determined based on the third parameter and the second reconstruction transform coefficient. The third parameter is used to represent the linear relationship between the first chromaticity component and the second chromaticity component.

5. The method according to claim 4, wherein, The step of determining the third reconstruction transformation coefficients based on the third reconstruction residual transformation coefficients and the first prediction compensation for the second chromaticity component includes: The third reconstruction transformation coefficient is obtained by summing the product of the second reconstruction transformation coefficient and the third parameter with the third reconstruction residual transformation coefficient.

6. The method according to claim 1, wherein, The step of determining the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the first reconstruction transformation coefficient and the third reconstruction residual transformation coefficient includes: The third reconstruction transformation coefficients are determined based on the third reconstruction residual transformation coefficients and the second prediction compensation for the second chromaticity component; The second prediction compensation of the second chromaticity component is determined based on the second parameter and the first reconstruction transform coefficient. The second parameter is used to represent the linear relationship between the luminance component and the second chromaticity component.

7. The method according to claim 6, wherein, The step of determining the third reconstruction transformation coefficients based on the third reconstruction residual transformation coefficients and the second prediction compensation for the second chromaticity component includes: The third reconstruction transformation coefficient is obtained by summing the product of the first reconstruction transformation coefficient and the second parameter with the third reconstruction residual transformation coefficient.

8. The method according to claim 1, 4, or 5, wherein, Under the condition that the first condition is met, the decoding end determines the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the second reconstruction transformation coefficient and the third reconstruction residual transformation coefficient. The first condition includes one of the following: For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is not 0; For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is 0; The first threshold is obtained by decoding the bitstream.

9. The method according to claim 1, 6, or 7, wherein, When the second condition is met, the decoding end determines the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the first reconstruction transformation coefficient and the third reconstruction residual transformation coefficient. The second condition includes one of the following: For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is 0; For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is not 0; The first threshold is obtained by decoding the bitstream.

10. The method according to claim 1, wherein, Based on the first reconstruction transform coefficient, the second reconstruction transform coefficient, and the third reconstruction residual transform coefficient, the third reconstruction transform coefficient is determined, including: The third reconstruction transformation coefficient is determined based on the first prediction compensation for the second chromaticity component, the second prediction compensation for the second chromaticity component, and the third reconstruction residual transformation coefficient. The prediction compensation of the second chromaticity component is determined based on the third parameter and the second reconstruction transform coefficient, and the second prediction compensation of the second chromaticity component is determined based on the second parameter and the first reconstruction transform coefficient. The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component, and the third parameter is used to represent the linear relationship between the first chrominance component and the second chrominance component.

11. The method according to claim 10, wherein, The third reconstruction transformation coefficients are determined based on the first prediction compensation for the second chromaticity component, the second prediction compensation for the second chromaticity component, and the third reconstruction residual transformation coefficients, including: The product of the second reconstruction transformation coefficient and the third parameter is summed with the third reconstruction residual transformation coefficient to obtain the first residual value of the third reconstruction transformation coefficient; The third reconstruction transformation coefficient is obtained by summing the product of the first reconstruction transformation coefficient and the second parameter with the first residual value of the third reconstruction transformation coefficient. The second parameter represents the linear relationship between the luminance component and the second chrominance component, and the third parameter represents the linear relationship between the first chrominance component and the second chrominance component.

12. The method according to any one of claims 1 to 11, wherein, The method further includes: Determine target parameters, which include at least one of the following: a first parameter for representing the linear relationship between the luminance component and the first chrominance component, a second parameter for representing the linear relationship between the luminance component and the second chrominance component, and a third parameter for representing the linear relationship between the first chrominance component and the second chrominance component.

13. The method according to claim 12, wherein, The determination of the target parameter includes at least one of the following: Decode the bitstream to obtain the target parameters; For the transform tree corresponding to the point cloud, the target parameters corresponding to the undecoded nodes are calculated based on the reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree.

14. The method according to claim 13, wherein, The decoded transform coefficients within the same layer include one of the following: All transform coefficients that have been decoded within the same layer; The first m transform coefficients that have been decoded within the same layer, where m is greater than 1; All transform coefficients of the first k decoded nodes within the same layer, where k is greater than 1.

15. The method according to claim 13 or 14, wherein, The step of calculating the target parameters corresponding to the undecoded nodes based on the decoded transform coefficients within the same layer of the transform tree includes at least one of the following: The first parameter is determined based on the first reconstructed transform coefficient and the second reconstructed transform coefficient corresponding to the decoded transform coefficients in the same layer of the transform tree; The second parameter is determined based on the first reconstructed transform coefficient and the third reconstructed transform coefficient corresponding to the decoded transform coefficients in the same layer of the transform tree; The third parameter is determined based on the first residual value of the second and third reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree; or, the third parameter is determined based on the second and third reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree.

16. The method according to any one of claims 13 to 15, wherein, The step of calculating the target parameters corresponding to the undecoded nodes based on the decoded transform coefficients within the same layer of the transform tree includes: Decode the bitstream to obtain the first threshold; For layers in the transform tree whose number of layers is less than or equal to the first threshold, the target parameters corresponding to the undecoded nodes are calculated based on the decoded transform coefficients within the same layer.

17. The method according to any one of claims 13 to 16, wherein, The step of calculating the target parameters corresponding to the undecoded nodes based on the decoded transform coefficients within the same layer of the transform tree includes: The first value is obtained by summing the products of the reconstructed transform coefficients corresponding to the first component and the reconstructed transform coefficients corresponding to the second component of the decoded transform coefficients in the same layer. The second value is obtained by summing the squares of the reconstructed transform coefficients corresponding to the first component of the decoded transform coefficients within the same layer. Calculate the ratio of the first value to the second value to obtain the target parameter corresponding to the first component; Wherein, the first component and the second component are any two of the luminance component, the first chromaticity component and the second chromaticity component.

18. A method for encoding attribute information, comprising: The encoding end performs Region Adaptive Hierarchical Transformation (RAHT) on each node to obtain the transformation coefficients corresponding to the attribute information of each node. The transformation coefficients include: a luminance component, a first chromaticity component, and a second chromaticity component; The encoding end uses the first reconstruction transform coefficients corresponding to the luminance component to predict and encode the first chrominance component, thereby obtaining the second residual transform coefficients corresponding to the first chrominance component. Based on the first reconstruction transform coefficient and the second residual transform coefficient, determine the second reconstruction transform coefficient corresponding to the first chromaticity component; The encoding end performs at least one of the following: The second chromaticity component is predicted and encoded using the second reconstruction transform coefficients to obtain the third residual transform coefficients corresponding to the second chromaticity component. The second chromaticity component is predicted and encoded using the first reconstruction transform coefficients to obtain the third residual transform coefficients corresponding to the second chromaticity component. The second chromaticity component is predicted and encoded using the first reconstruction transform coefficients to obtain the first residual value of the third residual transform coefficients corresponding to the second chromaticity component; the first residual value is predicted and encoded using the second reconstruction transform coefficients to obtain the third residual transform coefficients.

19. The method according to claim 18, wherein, The step of using the first reconstruction transform coefficients corresponding to the luminance component to predict and encode the first chrominance component, and obtaining the second residual transform coefficients corresponding to the first chrominance component, includes: Using the first chromaticity component and the encoding loss of the first chromaticity component, the second residual transform coefficients corresponding to the first chromaticity component are determined; The encoding loss of the first chroma component is determined based on a first parameter and a first reconstruction transform coefficient. The first parameter is used to represent the linear relationship between the luminance component and the first chroma component.

20. The method according to claim 19, wherein, The step of determining the second residual transform coefficients corresponding to the first chroma component using the first chroma component and its encoding loss includes: The difference between the first chromaticity component and the product of the first parameter and the first reconstructed transform coefficient is calculated to obtain the second residual transform coefficient corresponding to the first chromaticity component.

21. The method according to claim 18, wherein, The step of using the second reconstruction transform coefficients to predict and encode the second chromaticity component to obtain the third residual transform coefficients corresponding to the second chromaticity component includes: Using the second chromaticity component and the first coding loss of the second chromaticity component, the third residual transform coefficient corresponding to the second chromaticity component is determined; The first coding loss of the second chroma component is determined based on the third parameter and the second reconstruction transform coefficient, wherein the third parameter is used to represent the linear relationship between the first chroma component and the second chroma component.

22. The method according to claim 21, wherein, The step of determining the third residual transform coefficients corresponding to the second chroma component using the second chroma component and the first encoding loss of the second chroma component includes: The difference between the product of the second chromaticity component and the third parameter and the second reconstruction transform coefficient is calculated to obtain the third residual transform coefficient corresponding to the second chromaticity component.

23. The method according to claim 18, wherein, The step of using the first reconstructed transform coefficients to predict and encode the second chromaticity component to obtain the third residual transform coefficients corresponding to the second chromaticity component includes: The third residual transform coefficients corresponding to the second chromaticity component are determined using the second chromaticity component and the second coding loss of the second chromaticity component. The second coding loss of the second chromaticity component is determined based on the second parameter and the first reconstruction transform coefficient. The second parameter is used to represent the linear relationship between the luminance component and the second chromaticity component.

24. The method according to claim 23, wherein, The step of determining the third residual transform coefficients corresponding to the second chroma component using the second chroma component and the second encoding loss of the second chroma component includes: The difference between the second chromaticity component and the product of the second parameter and the first reconstruction transform coefficient is calculated to obtain the third residual transform coefficient corresponding to the second chromaticity component.

25. The method according to claim 18, 21, or 22, wherein, When the first condition is met, the encoding end uses the second reconstruction transform coefficients to predict and encode the second chromaticity component to obtain the third residual transform coefficients corresponding to the second chromaticity component. The first condition includes one of the following: For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is not 0; For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is 0.

26. The method according to claim 18, 23, or 24, wherein, When the second condition is met, the encoding end uses the first reconstruction transform coefficients to predict and encode the second chromaticity component to obtain the third residual transform coefficients corresponding to the second chromaticity component. The second condition includes one of the following: For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is 0; For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is not 0.

27. The method according to claim 18, wherein, The first reconstruction transform coefficient is used to predict and encode the second chromaticity component to obtain the first residual value of the third residual transform coefficient corresponding to the second chromaticity component. The third residual transform coefficients are obtained by predicting and encoding the first residual value using the second reconstruction transform coefficients, including: The first residual value of the third residual transform coefficient is determined based on the second chromaticity component and the second encoding loss of the second chromaticity component. The third residual transform coefficients are determined based on the first residual value of the third residual transform coefficients and the second coding loss of the second chroma component; Wherein, the first coding loss of the second chroma component is determined according to the third parameter and the second reconstruction transform coefficient, and the second coding loss of the second chroma component is determined according to the second parameter and the first reconstruction transform coefficient; The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component, and the third parameter is used to represent the linear relationship between the first chrominance component and the second chrominance component.

28. The method according to claim 27, wherein, The step of determining the first residual value of the third residual transform coefficient based on the second chroma component and the second encoding loss of the second chroma component includes: Calculate the difference between the product of the second chromaticity component and the second parameter and the first reconstructed transform coefficient to obtain the first residual value of the third residual transform coefficient; The step of determining the third residual transform coefficients based on the first residual value of the third residual transform coefficients and the second coding loss of the second chroma component includes: The difference between the first residual value and the product of the third parameter and the second reconstruction transformation coefficient is calculated to obtain the third residual transformation coefficient.

29. The method according to any one of claims 18, 21 to 28, wherein, The method further includes: The third residual transform coefficients are quantized and entropy encoded to obtain the third reconstructed transform coefficients corresponding to the second chromaticity component.

30. The method according to any one of claims 18 to 29, wherein, The method further includes: Determine target parameters, which include at least one of the following: a first parameter for representing the linear relationship between the luminance component and the first chrominance component, a second parameter for representing the linear relationship between the luminance component and the second chrominance component, and a third parameter for representing the linear relationship between the first chrominance component and the second chrominance component.

31. The method according to claim 30, wherein, The determination of the target parameter includes at least one of the following: The target parameters are determined based on preset values; For the transformation tree corresponding to the point cloud, the target parameters are calculated based on the transformation coefficients corresponding to the attribute information of all nodes in the same layer of the transformation tree. For the transformation tree corresponding to the point cloud, the target parameters corresponding to the uncoded nodes are calculated based on the encoded transformation coefficients within the same layer of the transformation tree.

32. The method according to claim 31, wherein, For the transformation tree corresponding to the point cloud, the target parameters are calculated based on the transformation coefficients corresponding to the attribute information of all nodes in the same layer of the transformation tree, including: Determine the transformation coefficients corresponding to the attribute information of all nodes within the same layer of the transformation tree; The first parameter corresponding to the layer is calculated using the luminance component and the first chrominance component in the transformation coefficients of all nodes in the same layer. The second parameter corresponding to the layer is calculated using the luminance component and the second chrominance component in the transformation coefficients of all nodes in the same layer. The third parameter corresponding to the layer is calculated using the first and second chromaticity components of the transformation coefficients of all nodes within the same layer.

33. The method according to claim 31, wherein, The encoded transform coefficients within the same layer include one of the following: All transform coefficients already encoded within the same layer; The first m transform coefficients encoded within the same layer, where m is greater than 1; All transform coefficients of the first k encoded nodes within the same layer, where k is greater than 1.

34. The method according to claim 31 or 33, wherein, The step of calculating the target parameters corresponding to uncoded nodes based on the encoded transform coefficients within the same layer of the transform tree includes at least one of the following: The first parameter is determined based on the first reconstructed transform coefficient and the second reconstructed transform coefficient corresponding to the coded transform coefficients in the same layer of the transform tree; The second parameter is determined based on the first reconstructed transform coefficient and the third reconstructed transform coefficient corresponding to the coded transform coefficients in the same layer of the transform tree; The third parameter is determined based on the first residual value of the second and third reconstructed transform coefficients corresponding to the encoded transform coefficients in the same layer of the transform tree; or, the third parameter is determined based on the second and third reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree.

35. The method according to claim 31, 33, or 34, wherein, The step of calculating the target parameters corresponding to uncoded nodes based on the encoded transform coefficients within the same layer of the transform tree includes: For layers in the transform tree whose number of layers is less than or equal to the first threshold, the target parameters corresponding to the undecoded nodes are calculated based on the decoded transform coefficients within the same layer.

36. The method according to any one of claims 31, 33 to 34, wherein, The step of calculating the target parameters corresponding to uncoded nodes based on the encoded transform coefficients within the same layer of the transform tree includes: The third value is obtained by summing the products of the reconstructed transform coefficients corresponding to the first component and the reconstructed transform coefficients corresponding to the second component of the encoded transform coefficients in the same layer. The fourth value is obtained by summing the squares of the reconstructed transform coefficients corresponding to the first component of the encoded transform coefficients within the same layer. Calculate the ratio of the third value to the fourth value to obtain the target parameter corresponding to the first component; Wherein, the first component and the second component are any two of the luminance component, the first chromaticity component and the second chromaticity component.

37. The method according to claim 25, 26, or 35, wherein, The method further includes: The first threshold is passed into the bitstream.

38. A device for decoding attribute information, comprising: The first decoding module is used to decode and dequantize the data to be decoded, and obtain the reconstruction transform coefficients corresponding to each node. The reconstructed transformation coefficients are the reconstructed transformation coefficients corresponding to the attribute information of each node. The reconstructed transformation coefficients include: a first reconstructed transformation coefficient corresponding to the luminance component of the transformation coefficients, a second reconstructed residual transformation coefficient corresponding to the first chrominance component of the transformation coefficients, and a third reconstructed residual transformation coefficient corresponding to the second chrominance component of the transformation coefficients; The first determining module is used to determine the second reconstruction transformation coefficient corresponding to the first chromaticity component based on the first reconstruction transformation coefficient and the second reconstruction residual transformation coefficient. A first processing module is configured to perform at least one of the following at the decoding end: Based on the second reconstruction transformation coefficient and the third reconstruction residual transformation coefficient, determine the third reconstruction transformation coefficient corresponding to the second chromaticity component; Based on the first reconstruction transformation coefficient and the third reconstruction residual transformation coefficient, determine the third reconstruction transformation coefficient corresponding to the second chromaticity component; The third reconstruction transformation coefficient corresponding to the second chromaticity component is determined based on the first reconstruction transformation coefficient, the second reconstruction transformation coefficient, and the third reconstruction residual transformation coefficient.

39. The apparatus according to claim 38, wherein, The first determining module is specifically used for: The step of determining the second reconstruction transformation coefficient corresponding to the first chromaticity component based on the first reconstruction transformation coefficient and the second reconstruction residual transformation coefficient includes: The second reconstruction transformation coefficients are determined based on the second reconstruction residual transformation coefficients and the prediction compensation for the first chromaticity component; The prediction compensation of the first chromaticity component is determined based on the first reconstruction transform coefficient and the first parameter, wherein the first parameter is used to represent the linear relationship between the luminance component and the first chromaticity component.

40. The apparatus according to claim 39, wherein, The first determining module is specifically used for: The second reconstruction transformation coefficient is obtained by summing the product of the first reconstruction transformation coefficient and the first parameter with the second reconstruction residual transformation coefficient.

41. The apparatus according to claim 38, wherein, The first processing module is specifically used for: The third reconstruction transformation coefficients are determined based on the third reconstruction residual transformation coefficients and the first prediction compensation for the second chromaticity component; The prediction compensation of the second chromaticity component is determined based on the third parameter and the second reconstruction transform coefficient. The third parameter is used to represent the linear relationship between the first chromaticity component and the second chromaticity component.

42. The apparatus according to claim 41, wherein, The first processing module is specifically used for: The third reconstruction transformation coefficient is obtained by summing the product of the second reconstruction transformation coefficient and the third parameter with the third reconstruction residual transformation coefficient.

43. The apparatus according to claim 38, wherein, The first processing module is specifically used for: The third reconstruction transformation coefficients are determined based on the third reconstruction residual transformation coefficients and the second prediction compensation for the second chromaticity component; The second prediction compensation of the second chromaticity component is determined based on the second parameter and the first reconstruction transform coefficient. The second parameter is used to represent the linear relationship between the luminance component and the second chromaticity component.

44. The apparatus according to claim 43, wherein, The first processing module is specifically used for: The third reconstruction transformation coefficient is obtained by summing the product of the first reconstruction transformation coefficient and the second parameter with the third reconstruction residual transformation coefficient.

45. The apparatus according to claim 38, 41, or 42, wherein, Under the condition that the first condition is met, the decoding end determines the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the second reconstruction transformation coefficient and the third reconstruction residual transformation coefficient. The first condition includes one of the following: For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is not 0; For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is 0; The first threshold is obtained by decoding the bitstream.

46. ​​The apparatus according to claim 38, 43, or 44, wherein, Under the condition that the second condition is met, the decoding end determines the third reconstruction transformation coefficient corresponding to the second chromaticity component based on the first reconstruction transformation coefficient and the third reconstruction residual transformation coefficient. The second condition includes one of the following: For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is 0; For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is not 0; The first threshold is obtained by decoding the bitstream.

47. The apparatus according to claim 38, wherein, The first processing module is specifically used for: The third reconstruction transformation coefficient is determined based on the first prediction compensation for the second chromaticity component, the second prediction compensation for the second chromaticity component, and the third reconstruction residual transformation coefficient. The prediction compensation of the second chromaticity component is determined based on the third parameter and the second reconstruction transform coefficient, and the second prediction compensation of the second chromaticity component is determined based on the second parameter and the first reconstruction transform coefficient. The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component, and the third parameter is used to represent the linear relationship between the first chrominance component and the second chrominance component.

48. The apparatus according to claim 47, wherein, The first processing module is specifically used for: The product of the second reconstruction transformation coefficient and the third parameter is summed with the third reconstruction residual transformation coefficient to obtain the first residual value of the third reconstruction transformation coefficient; The third reconstruction transformation coefficient is obtained by summing the product of the first reconstruction transformation coefficient and the second parameter with the first residual value of the third reconstruction transformation coefficient. The second parameter represents the linear relationship between the luminance component and the second chrominance component, and the third parameter represents the linear relationship between the first chrominance component and the second chrominance component.

49. The apparatus according to any one of claims 38 to 48, wherein, The device further includes: The second determining module is used to determine target parameters, the target parameters including at least one of the following: a first parameter for representing the linear relationship between the luminance component and the first chrominance component, a second parameter for representing the linear relationship between the luminance component and the second chrominance component, and a third parameter for representing the linear relationship between the first chrominance component and the second chrominance component.

50. The apparatus according to claim 49, wherein, The second determining module is specifically used for: Decode the bitstream to obtain the target parameters; For the transform tree corresponding to the point cloud, the target parameters corresponding to the undecoded nodes are calculated based on the reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree.

51. The apparatus according to claim 50, wherein, The decoded transform coefficients within the same layer include one of the following: All transform coefficients that have been decoded within the same layer; The first m transform coefficients that have been decoded within the same layer, where m is greater than 1; All transform coefficients of the first k decoded nodes within the same layer, where k is greater than 1.

52. The apparatus according to claim 50 or 51, wherein, The second determining unit is specifically used to perform at least one of the following: The first parameter is determined based on the first reconstructed transform coefficient and the second reconstructed transform coefficient corresponding to the decoded transform coefficients in the same layer of the transform tree; The second parameter is determined based on the first reconstructed transform coefficient and the third reconstructed transform coefficient corresponding to the decoded transform coefficients in the same layer of the transform tree; The third parameter is determined based on the first residual value of the second and third reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree; or, the third parameter is determined based on the second and third reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree.

53. The apparatus according to any one of claims 50 or 52, wherein, The second determining module is specifically used for: Decode the bitstream to obtain the first threshold; For layers in the transform tree whose number of layers is less than or equal to the first threshold, the target parameters corresponding to the undecoded nodes are calculated based on the decoded transform coefficients within the same layer.

54. The apparatus according to any one of claims 50 or 53, wherein, The second determining module is specifically used for: The first value is obtained by summing the products of the reconstructed transform coefficients corresponding to the first component and the reconstructed transform coefficients corresponding to the second component of the decoded transform coefficients in the same layer. The second value is obtained by summing the squares of the reconstructed transform coefficients corresponding to the first component of the decoded transform coefficients within the same layer. Calculate the ratio of the first value to the second value to obtain the target parameter corresponding to the first component; Wherein, the first component and the second component are any two of the luminance component, the first chromaticity component and the second chromaticity component.

55. An encoding device for attribute information, comprising: The transformation module is used to perform Region Adaptive Hierarchical Transformation (RAHT) on each node to obtain the transformation coefficients corresponding to the attribute information of each node. The transformation coefficients include: a luminance component, a first chromaticity component, and a second chromaticity component; The first encoding module is used to predict and encode the first chromaticity component using the first reconstruction transform coefficients corresponding to the luminance component, and obtain the second residual transform coefficients corresponding to the first chromaticity component. The third determining module is used to determine the second reconstruction transform coefficient corresponding to the first chromaticity component based on the first reconstruction transform coefficient and the second residual transform coefficient. The second processing module is configured to perform at least one of the following: The second chromaticity component is predicted and encoded using the second reconstruction transform coefficients to obtain the third residual transform coefficients corresponding to the second chromaticity component. The second chromaticity component is predicted and encoded using the first reconstruction transform coefficients to obtain the third residual transform coefficients corresponding to the second chromaticity component. The second chromaticity component is predicted and encoded using the first reconstruction transform coefficients to obtain the first residual value of the third residual transform coefficients corresponding to the second chromaticity component; the first residual value is predicted and encoded using the second reconstruction transform coefficients to obtain the third residual transform coefficients.

56. The apparatus according to claim 55, wherein, The first encoding module is specifically used for: Using the first chromaticity component and the encoding loss of the first chromaticity component, the second residual transform coefficients corresponding to the first chromaticity component are determined; The encoding loss of the first chroma component is determined based on a first parameter and a first reconstruction transform coefficient. The first parameter is used to represent the linear relationship between the luminance component and the first chroma component.

57. The apparatus according to claim 56, wherein, The first encoding module is specifically used for: The difference between the first chromaticity component and the product of the first parameter and the first reconstructed transform coefficient is calculated to obtain the second residual transform coefficient corresponding to the first chromaticity component.

58. The apparatus according to claim 55, wherein, The second processing module is specifically used for: Using the second chromaticity component and the first coding loss of the second chromaticity component, the third residual transform coefficient corresponding to the second chromaticity component is determined; The first coding loss of the second chroma component is determined based on the third parameter and the second reconstruction transform coefficient, wherein the third parameter is used to represent the linear relationship between the first chroma component and the second chroma component.

59. The apparatus according to claim 58, wherein, The second processing module is specifically used for: The difference between the product of the second chromaticity component and the third parameter and the second reconstruction transform coefficient is calculated to obtain the third residual transform coefficient corresponding to the second chromaticity component.

60. The apparatus according to claim 55, wherein, The second processing module is specifically used for: The third residual transform coefficients corresponding to the second chromaticity component are determined using the second chromaticity component and the second coding loss of the second chromaticity component. The second coding loss of the second chromaticity component is determined based on the second parameter and the first reconstruction transform coefficient. The second parameter is used to represent the linear relationship between the luminance component and the second chromaticity component.

61. The apparatus according to claim 60, wherein, The second processing module is specifically used for: The difference between the second chromaticity component and the product of the second parameter and the first reconstruction transform coefficient is calculated to obtain the third residual transform coefficient corresponding to the second chromaticity component.

62. The apparatus according to claim 55, 58, or 59, wherein, Under the condition that the first condition is met, the encoding end uses the second reconstruction transform coefficients to predict and encode the second chromaticity component to obtain the third residual transform coefficients corresponding to the second chromaticity component. The first condition includes one of the following: For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is not 0; For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is 0.

63. The apparatus according to claim 55, 60, or 61, wherein, When the second condition is met, the encoding end uses the first reconstruction transform coefficients to predict and encode the second chromaticity component to obtain the third residual transform coefficients corresponding to the second chromaticity component. The second condition includes one of the following: For the transformation tree corresponding to the point cloud, the current node is in a layer number greater than the first threshold and the third parameter is 0; For the transformation tree corresponding to the point cloud, the layer number of the current node is less than or equal to the first threshold, and the second parameter is not 0.

64. The apparatus according to claim 55, wherein, The second processing module is specifically used for: The first residual value of the third residual transform coefficient is determined based on the second chromaticity component and the second encoding loss of the second chromaticity component. The third residual transform coefficients are determined based on the first residual value of the third residual transform coefficients and the second coding loss of the second chroma component; Wherein, the first coding loss of the second chroma component is determined according to the third parameter and the second reconstruction transform coefficient, and the second coding loss of the second chroma component is determined according to the second parameter and the first reconstruction transform coefficient; The second parameter is used to represent the linear relationship between the luminance component and the second chrominance component, and the third parameter is used to represent the linear relationship between the first chrominance component and the second chrominance component.

65. The apparatus according to claim 64, wherein, The second processing module is specifically used for: Calculate the difference between the product of the second chromaticity component and the second parameter and the first reconstructed transform coefficient to obtain the first residual value of the third residual transform coefficient; The difference between the first residual value and the product of the third parameter and the second reconstruction transform coefficient is calculated to obtain the third residual transform coefficient; The second parameter represents the linear relationship between the luminance component and the second chrominance component; the third parameter represents the linear relationship between the first chrominance component and the second chrominance component.

66. The apparatus according to any one of claims 55, 58 to 65, wherein, The device further includes: The second encoding module is used to quantize and entropy encode the third residual transform coefficients to obtain the third reconstructed transform coefficients corresponding to the second chromaticity component.

67. The apparatus according to any one of claims 55 to 66, wherein, The device further includes: The fourth determining module is used to determine target parameters, the target parameters including at least one of the following: a first parameter for representing the linear relationship between the luminance component and the first chrominance component, a second parameter for representing the linear relationship between the luminance component and the second chrominance component, and a third parameter for representing the linear relationship between the first chrominance component and the second chrominance component.

68. The apparatus according to claim 67, wherein, The fourth determining module is used to perform at least one of the following: The target parameters are determined based on preset values; For the transformation tree corresponding to the point cloud, the target parameters are calculated based on the transformation coefficients corresponding to the attribute information of all nodes in the same layer of the transformation tree. For the transformation tree corresponding to the point cloud, the target parameters corresponding to the uncoded nodes are calculated based on the encoded transformation coefficients within the same layer of the transformation tree.

69. The apparatus according to claim 68, wherein, The fourth determining module is specifically used for: Determine the transformation coefficients corresponding to the attribute information of all nodes within the same layer of the transformation tree; The first parameter corresponding to the layer is calculated using the luminance component and the first chrominance component in the transformation coefficients of all nodes in the same layer. The second parameter corresponding to the layer is calculated using the luminance component and the second chrominance component in the transformation coefficients of all nodes in the same layer. The third parameter corresponding to the layer is calculated using the first and second chromaticity components of the transformation coefficients of all nodes within the same layer.

70. The apparatus according to claim 68, wherein, The encoded transform coefficients within the same layer include one of the following: All transform coefficients already encoded within the same layer; The first m transform coefficients encoded within the same layer, where m is greater than 1; All transform coefficients of the first k encoded nodes within the same layer, where k is greater than 1.

71. The apparatus according to claim 68 or 70, wherein, The fourth determining module is specifically used to perform at least one of the following: The first parameter is determined based on the first reconstructed transform coefficient and the second reconstructed transform coefficient corresponding to the coded transform coefficients in the same layer of the transform tree; The second parameter is determined based on the first reconstructed transform coefficient and the third reconstructed transform coefficient corresponding to the coded transform coefficients in the same layer of the transform tree; The third parameter is determined based on the first residual value of the second and third reconstructed transform coefficients corresponding to the encoded transform coefficients in the same layer of the transform tree; or, the third parameter is determined based on the second and third reconstructed transform coefficients corresponding to the decoded transform coefficients in the same layer of the transform tree.

72. The apparatus according to claim 68, 70, or 71, wherein, The fourth determining module is specifically used for: For layers in the transform tree whose number of layers is less than or equal to the first threshold, the target parameters corresponding to the undecoded nodes are calculated based on the decoded transform coefficients within the same layer.

73. The apparatus according to claim 68, 70, or 71, wherein, The fourth determining module is specifically used for: The third value is obtained by summing the products of the reconstructed transform coefficients corresponding to the first component and the reconstructed transform coefficients corresponding to the second component of the encoded transform coefficients in the same layer. The fourth value is obtained by summing the squares of the reconstructed transform coefficients corresponding to the first component of the encoded transform coefficients within the same layer. Calculate the ratio of the third value to the fourth value to obtain the target parameter corresponding to the first component; Wherein, the first component and the second component are any two of the luminance component, the first chromaticity component and the second chromaticity component.

74. The apparatus according to claim 62, 63, or 72, wherein, The device further includes: The third encoding module is used to input the first threshold into the bitstream.

75. An electronic device comprising a processor and a memory, the memory storing a program or instructions executable on the processor, the program or instructions, when executed by the processor, implementing the steps of a method for decoding attribute information as claimed in any one of claims 1 to 17, or implementing the steps of a method for encoding attribute information as claimed in claims 18 to 37.

76. A readable storage medium storing a program or instructions that, when executed by a processor, implement the steps of the method for decoding attribute information as claimed in any one of claims 1 to 17, or the steps of the method for encoding attribute information as claimed in claims 18 to 37.

77. A chip comprising a processor and a communication interface coupled to the processor, the processor being configured to run a program or instructions to implement the steps of the method as claimed in any one of claims 1 to 17, or to implement the steps of the method as claimed in claims 18 to 37.

78. A computer program product comprising computer instructions that, when executed by a processor, implement the steps of the method as claimed in any one of claims 1 to 17, or implement the steps of the method as claimed in claims 18 to 37.

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