WO2023173237A1 - Encoding method, decoding method, bit stream, encoder, decoder, and storage medium - Google Patents

Abstract

Embodiments of the present application disclose an encoding method, a decoding method, a bit stream, an encoder, a decoder, and a storage medium. The decoding method is applied to a decoder, and comprises: determining an index number corresponding to a current node and an initial reference set (S701); on the basis of the parity characteristic of the index number, determining a target position corresponding to the current node in the initial reference set (S702); and after decoding the current node according to the initial reference set, placing the current node at the target position to obtain a target reference set (S703). In this way, the target reference set comprising the current node is constructed on the basis of the parity characteristic of the index number, the accuracy of point cloud attribute prediction can be improved by means of the target reference set, and the point cloud attribute encoding and decoding performance can be improved.

Description

Coding and decoding methods, code streams, encoders, decoders and storage media Technical field

The embodiments of the present application relate to the field of point cloud compression technology, and in particular, to a coding and decoding method, a code stream, an encoder, a decoder, and a storage medium.

Background technique

In the point cloud compression (Audio Video Standard-Point Cloud Compression, AVS-PCC) encoding and decoding framework provided based on the audio and video coding standard, the geometric information and attribute information of the point cloud are encoded separately. After the geometric encoding is completed, the geometric information is reconstructed, and the encoding of attribute information will depend on the reconstructed geometric information. Among them, attribute information encoding is mainly aimed at encoding color information, converting it into a YUV color space that is more in line with human visual characteristics, and then performing attribute encoding on the preprocessed attribute information, and finally generating a binary attribute code stream.

At present, in the attribute encoding process of the Point Cloud Compression Reference Platform (Point Cloud Reference Model, PCRM), it mainly uses the global search method or the spatial relationship search method to achieve attribute prediction of the current node. However, existing global search methods and spatial relationship search methods have some flaws, which lead to inaccurate reference range construction for determining prediction nodes and reduce the accuracy of attribute prediction.

Contents of the invention

Embodiments of the present application provide a coding and decoding method, a code stream, an encoder, a decoder, and a storage medium, which can improve the prediction accuracy of point cloud attributes and improve the coding and decoding performance of point cloud attributes.

The technical solutions of the embodiments of this application can be implemented as follows:

In the first aspect, embodiments of the present application provide a decoding method, which is applied to a decoder. The method includes:

Determine the index number corresponding to the current node and the initial reference set;

Based on the parity characteristics of the index sequence number, determine the target position corresponding to the current node in the initial reference set;

After decoding the current node according to the initial reference set, the current node is placed at the target position to obtain the target reference set.

In the second aspect, embodiments of the present application provide an encoding method, which is applied to an encoder. The method includes:

Determine the index number corresponding to the current node and the initial reference set;

Based on the parity characteristics of the index sequence number, determine the target position corresponding to the current node in the initial reference set;

After encoding the current node according to the initial reference set, the current node is placed at the target position to obtain the target reference set.

In the third aspect, embodiments of the present application provide a code stream, which is generated by bit encoding based on the information to be encoded; wherein the information to be encoded at least includes: the attribute residual value corresponding to the current node.

In a fourth aspect, embodiments of the present application provide an encoder, which includes a first determination unit and a coding unit; wherein,

The first determination unit is configured to determine the index sequence number corresponding to the current node and the initial reference set; and determine the target position corresponding to the current node in the initial reference set based on the parity characteristics of the index sequence number;

The encoding unit is configured to, after encoding the current node according to the initial reference set, place the current node at the target position to obtain the target reference set.

In a fifth aspect, embodiments of the present application provide an encoder, which includes a first memory and a first processor; wherein,

a first memory for storing a computer program capable of running on the first processor;

The first processor is used to perform the method of the second aspect when running the computer program.

In a sixth aspect, embodiments of the present application provide a decoder, which includes a second determination unit and a decoding unit; wherein,

The second determination unit is configured to determine the index sequence number corresponding to the current node and the initial reference set; and determine the target position corresponding to the current node in the initial reference set based on the parity characteristics of the index sequence number;

The decoding unit is configured to decode the current node according to the initial reference set, and then place the current node at the target position to obtain the target reference set.

In a seventh aspect, embodiments of the present application provide a decoder, which includes a second memory and a second processor; wherein,

a second memory for storing a computer program capable of running on the second processor;

The second processor is used to execute the method of the first aspect when running the computer program.

In an eighth aspect, embodiments of the present application provide a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed, the method of the first aspect is implemented, or the method of the second aspect is implemented. .

Embodiments of the present application provide a coding and decoding method, a code stream, an encoder, a decoder and a storage medium. At the coding end, the index number corresponding to the current node and the initial reference set are determined; based on the parity characteristics of the index number, the current node is determined The corresponding target position in the initial reference set; after encoding the current node according to the initial reference set, place the current node at the target position to obtain the target reference set. At the decoding end, determine the index sequence number corresponding to the current node and the initial reference set; based on the parity characteristics of the index sequence number, determine the target position corresponding to the current node in the initial reference set; after decoding the current node according to the initial reference set, the current node The node is placed at the target location to obtain the target reference set. In this way, a target reference set including the current node is constructed based on the parity characteristics of the index sequence number, and the target reference set is used to predict point cloud attributes, which can improve the prediction accuracy of point cloud attributes and improve the encoding and decoding performance of point cloud attributes. .

Description of the drawings

Figure 1A is a schematic diagram of a three-dimensional point cloud image provided by an embodiment of the present application;

Figure 1B is a partially enlarged schematic diagram of a three-dimensional point cloud image provided by an embodiment of the present application;

Figure 2A is a schematic diagram of point cloud images at different viewing angles provided by an embodiment of the present application;

Figure 2B is a schematic diagram of the data storage format corresponding to Figure 2A provided by an embodiment of the present application;

Figure 3 is a schematic diagram of a point cloud encoding and decoding network architecture provided by an embodiment of the present application;

Figure 4 is a schematic structural diagram of a point cloud encoder provided by an embodiment of the present application;

Figure 5 is a schematic structural diagram of a point cloud decoder provided by an embodiment of the present application;

Figure 6A is a schematic diagram of the distribution of current nodes and coplanar nodes provided by an embodiment of the present application;

Figure 6B is a schematic diagram of the distribution of current nodes and collinear nodes provided by an embodiment of the present application;

Figure 6C is a schematic diagram of the distribution of current nodes and common nodes provided by an embodiment of the present application;

Figure 7 is a schematic flow chart of a decoding method provided by an embodiment of the present application;

Figures 8A to 8H are schematic diagrams of eight modes corresponding to the current node orientation provided by the embodiment of the present application;

Figures 9A to 9H are schematic diagrams of the distribution of coplanar, collinear, and co-point neighbor blocks corresponding to a current node in eight modes provided by an embodiment of the present application;

Figure 10 is a schematic flow chart of an encoding method provided by an embodiment of the present application;

Figure 11 is a schematic flowchart of a reference range determination provided by an embodiment of the present application;

Figure 12 is a schematic structural diagram of an encoder provided by an embodiment of the present application;

Figure 13 is a schematic diagram of the specific hardware structure of an encoder provided by an embodiment of the present application;

Figure 14 is a schematic structural diagram of a decoder provided by an embodiment of the present application;

Figure 15 is a schematic diagram of the specific hardware structure of a decoder provided by an embodiment of the present application.

Detailed ways

In order to understand the characteristics and technical content of the embodiments of the present application in more detail, the implementation of the embodiments of the present application will be described in detail below with reference to the accompanying drawings. The attached drawings are for reference only and are not intended to limit the embodiments of the present application.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or a different subset of all possible embodiments, and Can be combined with each other without conflict.

It should also be pointed out that the terms "first\second\third" involved in the embodiments of this application are only used to distinguish similar objects and do not represent a specific ordering of objects. It is understandable that "first\second\ The third "specific order or sequence may be interchanged where permitted, so that the embodiments of the application described herein can be implemented in an order other than that illustrated or described herein.

Point Cloud is a three-dimensional representation of the surface of an object. Through collection equipment such as photoelectric radar, lidar, laser scanner, and multi-view camera, the point cloud (data) of the surface of the object can be collected.

Point cloud is a set of discrete points randomly distributed in space that expresses the spatial structure and surface properties of a three-dimensional object or scene. Figure 1A shows a three-dimensional point cloud image and Figure 1B shows a partial enlargement of the three-dimensional point cloud image. It can be seen that the point cloud surface is composed of densely distributed points.

Two-dimensional images have information expressed in each pixel and are distributed regularly, so there is no need to record additional position information; however, the distribution of points in the point cloud in the three-dimensional space is random and irregular, so each point needs to be recorded Only the position of the point in space can completely express a point cloud. Similar to two-dimensional images, each position in the collection process has corresponding attribute information, usually RGB color values, and the color values reflect the color of the object; for point clouds, the attribute information corresponding to each point is in addition to color information. , and the more common one is the reflectance value, which reflects the surface material of the object. Therefore, points in the point cloud can include point location information and point attribute information. For example, the position information of the point may be the three-dimensional coordinate information (x, y, z) of the point. The position information of a point can also be called the geometric information of the point. For example, the attribute information of a point may include color information (three-dimensional color information) and/or reflectance (one-dimensional reflectance information r), and so on. For example, color information can be information on any color space. For example, the color information may be RGB information. Among them, R represents red (Red, R), G represents green (Green, G), and B represents blue (Blue, B). For another example, the color information may be brightness and chrominance (YCbCr, YUV) information. Among them, Y represents brightness (Luma), Cb(U) represents blue color difference, and Cr(V) represents red color difference.

According to the point cloud obtained based on the principle of laser measurement, the points in the point cloud can include the three-dimensional coordinate information of the point and the reflectivity value of the point. For another example, in a point cloud obtained according to the principle of photogrammetry, the points in the point cloud may include the three-dimensional coordinate information of the point and the three-dimensional color information of the point. For another example, a point cloud is obtained by combining the principles of laser measurement and photogrammetry. The points in the point cloud may include the three-dimensional coordinate information of the point, the reflectivity value of the point, and the three-dimensional color information of the point.

Figure 2A and Figure 2B show a point cloud image and its corresponding data storage format. Among them, Figure 2A provides six viewing angles of the point cloud image. Figure 2B is composed of the file header information part and the data part. The header information includes the data format, data representation type, total number of point cloud points, and the content represented by the point cloud. . For example, the point cloud is in ".ply" format and is represented by ASCII code. The total number of points is 207242. Each point has three-dimensional coordinate information (x, y, z) and three-dimensional color information (r, g, b).

Point clouds can be divided into:

Static point cloud: that is, the object is stationary and the device that obtains the point cloud is also stationary;

Dynamic point cloud: The object is moving, but the device that obtains the point cloud is stationary;

Dynamically acquire point clouds: The device that acquires point clouds is in motion.

For example, point clouds are divided into two categories according to their uses:

Category 1: Machine perception point cloud, which can be used in scenarios such as autonomous navigation systems, real-time inspection systems, geographic information systems, visual sorting robots, and rescue and disaster relief robots;

Category 2: Human eye perception point cloud, which can be used in point cloud application scenarios such as digital cultural heritage, free-viewpoint broadcasting, three-dimensional immersive communication, and three-dimensional immersive interaction.

Point clouds can flexibly and conveniently express the spatial structure and surface properties of three-dimensional objects or scenes, and because point clouds are obtained by directly sampling real objects, they can provide a strong sense of reality while ensuring accuracy, so they are widely used and their scope Including virtual reality games, computer-aided design, geographic information systems, automatic navigation systems, digital cultural heritage, free-viewpoint broadcasting, three-dimensional immersive telepresence, three-dimensional reconstruction of biological tissues and organs, etc.

Point cloud collection mainly has the following methods: computer generation, 3D laser scanning, 3D photogrammetry, etc. Computers can generate point clouds of virtual three-dimensional objects and scenes; 3D laser scanning can obtain point clouds of static real-world three-dimensional objects or scenes, and can obtain millions of point clouds per second; 3D photogrammetry can obtain dynamic real-world three-dimensional objects or scenes Point clouds can obtain tens of millions of point clouds per second. These technologies reduce the cost and time period of point cloud data acquisition and improve the accuracy of the data. Changes in the way of obtaining point cloud data have made it possible to obtain large amounts of point cloud data. With the growth of application requirements, the processing of massive 3D point cloud data has encountered bottlenecks limited by storage space and transmission bandwidth.

For example, taking a point cloud video with a frame rate of 30 frames per second (fps), the number of points in each frame of the point cloud is 700,000, and each point has coordinate information xyz (float) and color information RGB (uchar), Then the data volume of 10s point cloud video is approximately 0.7 million×(4Byte×3+1Byte×3)×30fps×10s=3.15GB, where 1Byte is 8bit, and the YUV sampling format is 4:2:0, and the frame rate The data volume of 1280×720 2D video at 24fps for 10s is about 1280×720×12bit×24fps×10s≈0.33GB, and the data volume of two-view 3D video for 10s is about 0.33×2=0.66GB. It can be seen that the data volume of point cloud video far exceeds the data volume of 2D video and 3D video of the same length. Therefore, in order to better realize data management, save server storage space, and reduce transmission traffic and transmission time between the server and the client, point cloud compression has become a key issue to promote the development of the point cloud industry.

In other words, since the point cloud is a collection of massive points, storing the point cloud will not only consume a lot of memory, but is also not conducive to transmission. There is not such a large bandwidth to support the direct transmission of the point cloud at the network layer without compression. Therefore, , the point cloud needs to be compressed.

Currently, the point cloud coding framework that can compress point clouds can be the Geometry-based Point Cloud Compression (G-PCC) codec framework provided by the Moving Picture Experts Group (MPEG) Or the Video-based Point Cloud Compression (V-PCC) codec framework, or the AVS-PCC codec framework provided by AVS. The G-PCC encoding and decoding framework can be used to compress the first type of static point cloud and the third type of dynamic point cloud, and the V-PCC encoding and decoding framework can be used to compress the second type of dynamic point cloud. The G-PCC encoding and decoding framework is also called point cloud codec TMC13, and the V-PCC encoding and decoding framework is also called point cloud codec TMC2.

The embodiment of the present application provides a network architecture of a point cloud encoding and decoding system that includes a decoding method and an encoding method. Figure 3 is a schematic diagram of the network architecture of a point cloud encoding and decoding system provided by an embodiment of the present application. As shown in FIG. 3 , the network architecture includes one or more electronic devices 13 to 1N and a communication network 01 , wherein the electronic devices 13 to 1N can perform video interaction through the communication network 01 . During the implementation process, electronic devices may be various types of devices with point cloud encoding and decoding functions. For example, the electronic devices may include mobile phones, tablet computers, personal computers, personal digital assistants, navigators, digital phones, and video phones. , televisions, sensing equipment, servers, etc., are not limited by the embodiments of this application. Among them, the decoder or encoder in the embodiment of the present application can be the above-mentioned electronic device.

Among them, the electronic device in the embodiment of the present application has a point cloud encoding and decoding function, and generally includes a point cloud encoder (ie, encoder) and a point cloud decoder (ie, decoder).

The following uses the AVS-PCC encoding and decoding framework as an example to illustrate the point cloud compression technology.

It can be understood that point cloud compression generally adopts the method of compressing point cloud geometric information and attribute information separately. On the encoding side, the point cloud geometric information is first encoded in the geometry encoder, and then the reconstructed geometric information is input into the attribute encoder as additional information. , assists in the compression of point cloud attributes; on the decoding end, the point cloud geometric information is first decoded in the geometry decoder, and then the decoded geometric information is input into the attribute decoder as additional information to assist in the compression of point cloud attributes. The entire codec consists of pre-processing/post-processing, geometry encoding/decoding, and attribute encoding/decoding.

The embodiment of the present application provides a point cloud encoder. Figure 4 shows the framework of the point cloud compression reference platform PCRM provided by AVS. The point cloud encoder 11 includes a geometric encoder: a coordinate translation unit 111 and a coordinate quantization unit. 112. Octree construction unit 113, geometric entropy encoder 114, geometric reconstruction unit 115. Attribute encoder: attribute recoloring unit 116, color space transform unit 117, first attribute prediction unit 118, quantization unit 119 and attribute entropy encoder 1110.

For PCRM, in the geometric encoding part of the coding end, the original geometric information is first preprocessed, the geometric origin is normalized to the minimum position in the point cloud space through the coordinate translation unit 111, and the geometric information is transferred from the float to the point cloud space through the coordinate quantization unit 112. The points are converted into shapes to facilitate subsequent regularization processing; then the regularized geometric information is geometrically encoded, and the octree structure is used in the octree construction unit 113 to recursively divide the point cloud space, dividing the current node each time into eight sub-blocks of the same size, and determine the occupied codeword status of each sub-block. When the sub-block does not contain points, it is recorded as empty, otherwise it is recorded as non-empty. The occupancy of all blocks is recorded at the last level of recursive division. The codeword information is geometrically encoded; on the one hand, the geometric information expressed through the octree structure is input to the geometric entropy encoder 114 to form a geometric code stream; on the other hand, the geometric reconstruction process is performed in the geometric reconstruction unit 115. The reconstructed geometry The information is input to the attribute encoder as additional information.

In the attribute encoding part, the original attribute information is first preprocessed. Since the geometric information changes after the geometric encoding, the attribute value is reassigned to each point after the geometric encoding through the attribute recoloring unit 116 to realize the attribute Repaint. In addition, if the attribute information being processed is color information, the original color information needs to be transformed into a color space through the color space transformation unit 117 to convert it into a YUV color space that is more in line with the visual characteristics of the human eye; and then predicted through the first attribute Unit 118 performs attribute encoding on the preprocessed attribute information. At first, the point cloud needs to be reordered. The reordering method is Morton code, so the traversal order of attribute encoding is Morton order. The attribute prediction method in PCRM is a single point prediction based on Morton order, that is, going back one point from the current point to be encoded (current node) according to Morton order, and the node found is the prediction reference point of the current point to be encoded, and then The attribute reconstruction value of the prediction reference point is used as the attribute prediction value, and the attribute residual value is the difference between the attribute original value and the attribute prediction value of the current point to be encoded; finally, the attribute residual value is quantized through the quantization unit 119, and The quantized residual information is input to the attribute entropy encoder 1110 to form an attribute code stream.

The embodiment of the present application also provides a point cloud decoder. Figure 5 shows the framework of the point cloud compression reference platform PCRM provided by AVS. The point cloud decoder 12 includes a geometric decoder: a geometric entropy decoder 121, Octree reconstruction unit 122, coordinate inverse quantization unit 123, and coordinate inverse translation unit 124. Attribute decoder: attribute entropy decoder 125, inverse quantization unit 126, second attribute prediction unit 127 and color space inverse transform unit 128.

On the decoding end, geometry and attributes are also decoded separately. In the geometry decoding part, the geometry code stream is first entropy decoded through the geometric entropy decoder 121 to obtain the geometric information of each node, and then the octree structure is constructed through the octree reconstruction unit 122 in the same way as the geometry encoding, combined with The decoded geometry reconstructs the geometric information expressed through the octree structure after coordinate transformation. On the one hand, the information is coordinate inverse quantized through the coordinate inverse quantization unit 123 and inversely translated through the coordinate inverse translation unit 124 to obtain the decoded geometry information. On the other hand, it is input to the attribute decoder as additional information. In the attribute decoding part, the Morton order is constructed in the same way as the encoding end. First, the attribute code stream is entropy decoded through the attribute entropy decoder 125 to obtain the quantized residual information; then inverse quantization is performed through the inverse quantization unit 126. Obtain the attribute residual value; similarly, in the same manner as attribute encoding, obtain the attribute prediction value of the current to-be-decoded point through the second attribute prediction unit 127, and then add the attribute prediction value and the attribute residual value to recover The attribute reconstruction value of the current point to be decoded (for example, YUV attribute value); finally, the decoding attribute information is obtained through the inverse color space transformation of the color space inverse transformation unit 128 .

It can also be understood that for the AVS-PCC encoding and decoding framework, the general test conditions are as follows:

(1) There are 4 types of test conditions:

Condition 1: The geometric position is limited and lossy, and the attributes are lossy;

Condition 2: The geometric position is lossless and the attributes are lossy;

Condition 3: The geometric position is lossless, and the attributes are limited and lossy;

Condition 4: The geometric position is lossless and the attributes are lossless.

(2) The universal test sequence includes five categories: Cat1A, Cat1B, Cat1C, Cat2-frame and Cat3. Among them, Cat1A and Cat2-frame point clouds only contain reflectivity attribute information, Cat1B and Cat3 point clouds only contain color attribute information, and Cat1C point clouds contain both color and reflectance attribute information.

(3) Implementation methods: 2 types in total, distinguished by the algorithm used for attribute compression.

Embodiment 1: Prediction branch, attribute compression adopts prediction-based method;

Embodiment 2: Transform branch, attribute compression adopts a transformation-based method, including two transformation algorithms: one is the wavelet transform algorithm, and the other is the k-element discrete cosine transform (Discrete Cosine Transform, DCT) transformation algorithm.

(4) For the attribute coding part in point cloud compression, specifically the intra-frame prediction part, here the current node is mainly predicted with reference to its adjacent nodes, and the attribute residual is calculated based on the attribute prediction value and the original attribute value of the current node. After the difference, the attribute residual value is transmitted to the decoder through quantization, transformation and other processes; after receiving and parsing the code stream, the decoder obtains the attribute residual value through inverse transformation and inverse quantization steps, and the decoder predicts it through the same process Obtain the attribute prediction value, superimpose the attribute prediction value and the attribute residual value to obtain the attribute reconstruction value corresponding to the current node.

Among them, the same operation is performed on both the encoding end and the decoding end to determine the attribute prediction value. The specific attribute prediction process mainly includes the following two types:

The first is a global search method based on encoding and decoding order. Assuming that the current node is Pi, the encoded/decoded reference nodes are (P0, P1,...,Pi-1).

If i=0, then {128, 128, 128} is directly used as the predicted value without searching;

If i=1, then P0 is used as the prediction node;

If i=2, then P0 and P1 are used as prediction nodes;

If i>=3, then if i<maxNumOfNeighbours, then searchRange=i, otherwise searchRange=maxNumOfNeighbours (where maxNumOfNeighbours is a specific value, such as 128).

In this way, the searchRange points before the current node in Hilbert order, such as (Pi-searchRange,...,Pi-2,Pi-1), are searched forward one by one in Hilbert order to find the closest distance to the current node. The k points of are used as the prediction nodes of the current node. The specific process is as follows:

(a) When processing the first three nodes of the current node in Hilbert order, insert these three nodes into the prediction point set in order, and after each node is inserted, the points in the prediction point set must be The distance between (xi-j,yi-j,zi-j) and the current node (xi,yi,zi), sort the points in the predicted point set in ascending order, so that the distance between the three points after sorting satisfies d1 <=d2<=d3. Among them, the distance d is calculated using the Manhattan distance calculation method, which is defined as:

d＝|xi-xi-j|+|yi-yi-j|+|zi-zi-j| (1)

(b) Continue to search forward for the jth point. When the number of points in the predicted point set is equal to 3, if the distance between the jth point and the current node is dj=d3, then the jth point is added to the equidistant point set. ;

If the distance between the jth point and the current node is dj<d3, then the point corresponding to d3 is moved out of the prediction point set, and the j point is added to the prediction point set. After adding the new point, the point in the prediction point set is compared with the current node again. distance between each other, sort the points in the predicted point set in ascending order, and then compare the reordered d3 with the distance dtemp of the removed point. If dtemp=d3, add the removed point to the equidistant point set. , otherwise the equidistant point set will be cleared;

(c) Until the point Pi-searchRange is searched, the 3 closest points are finally obtained as prediction nodes, and up to 13 equidistant points.

The second type is a search method based on spatial relationships. Using the geometric relationship between nodes (i.e., spatial relationship), the geometric coplanar, collinear, and common point nodes of the current node are used as prediction nodes. At the same time, the condition that the prediction node needs to meet is that the encoding/decoding has been completed before the current node. , and then set the weight value to the reciprocal of the geometric Manhattan distance between the predicted node and the current node, that is, the weight of coplanar nodes is 1, the weight of collinear nodes is 1/2, and the weight of common nodes is 1/3, and the weight of all predicted nodes is calculated. The weighted average of the attribute reconstruction values is the attribute prediction value corresponding to the current node (especially, for the first node encoded, there is no reference node for prediction, and its attribute prediction value can be directly set to 0).

Simply put, the two conditions that need to be met are: (a) It meets the coplanar, collinear, and co-point relationship with the current node; (b) Encoding/decoding has been completed before the current node.

Exemplarily, FIG. 6A shows a schematic distribution diagram of a current node and its coplanar nodes provided by an embodiment of the present application, and FIG. 6B shows a schematic distribution diagram of a current node and its coplanar nodes provided by an embodiment of the present application. FIG. 6C shows a schematic distribution diagram of a current node and its common nodes provided by an embodiment of the present application. As shown in Figure 6A-Figure 6C, assume that the sequence number of the current node O is 7, with a total of 6 faces, 12 edges, and 8 points. Among them, in Figure 6A, the coplanar nodes are 3, 5, 6, 14, 21, and 35; in Figure 6B, the colinear nodes are 1, 2, 4, 10, 12, 17, 20, 28, 33, 34, 42, and 49; in Figure 6C, the common nodes are 0, 8, 16, 24, 32, 40, 48, and 56.

Among all these coplanar nodes, collinear nodes, and common point nodes, regardless of the position of the current node, nodes that may satisfy the condition of "encoding/decoding completed before the current node" include: coplanar nodes 3, 5, 6, Collinear nodes 1, 2, 4, 10, 12, 17, 20, 33, 34, common nodes 0, 8, 16, 24, 32, 40, 48; therefore, the predicted nodes will be at coplanar nodes 3, 5 , 6, collinear nodes 1, 2, 4, 10, 12, 17, 20, 33, 34, generated among common nodes 0, 8, 16, 24, 32, 40, 48.

However, although the search method based on spatial relationships can quickly locate nodes near the current node, it may not necessarily be able to find the prediction node closest to the current node, so it cannot maximize the accuracy of intra-frame prediction.

Based on this, embodiments of the present application provide a coding and decoding method. At the coding end, the index sequence number corresponding to the current node and the initial reference set are determined; based on the parity characteristics of the index sequence number, the target position corresponding to the current node in the initial reference set is determined. ;After encoding the current node according to the initial reference set, place the current node at the target position to obtain the target reference set. At the decoding end, determine the index sequence number corresponding to the current node and the initial reference set; based on the parity characteristics of the index sequence number, determine the target position corresponding to the current node in the initial reference set; after decoding the current node according to the initial reference set, the current node The node is placed at the target location to obtain the target reference set. In this way, a target reference set including the current node is constructed based on the parity characteristics of the index sequence number, and the target reference set is used to predict point cloud attributes, which can improve the prediction accuracy of point cloud attributes and improve the encoding and decoding performance of point cloud attributes. .

Each embodiment of the present application will be described in detail below with reference to the accompanying drawings.

In an embodiment of the present application, see FIG. 7 , which shows a schematic flowchart of a decoding method provided by an embodiment of the present application. As shown in Figure 7, the method may include:

S701: Determine the index sequence number and initial reference set corresponding to the current node.

It should be noted that the decoding method described in the embodiment of the present application specifically refers to a point cloud decoding method, and more specifically, an intra-frame prediction method of point cloud attributes, which is used to construct a reference range for determining prediction nodes. This method can be applied to point cloud decoders (also simply called "decoders").

It should also be noted that in this embodiment of the present application, the point cloud to be processed includes at least one node. Among them, for a node in the point cloud to be processed, when decoding the node, it can be used as a node to be decoded in the point cloud to be processed, and there are multiple decoded nodes around the node. Here, the current node is the node to be decoded that currently needs to be decoded among the at least one node.

Further, in the embodiment of this application, for each node in the point cloud to be processed, it corresponds to a geometric information and an attribute information; wherein, the geometric information represents the spatial relationship of the point, and the attribute information represents the attribute information of the point. .

Here, the attribute information may be color components, reflectivity or other attributes, which are not specifically limited in the embodiments of this application. Wherein, when the attribute information is a color component, it can specifically be color information in any color space. For example, the attribute information may be color information in the RGB space, color information in the YUV space, color information in the YCbCr space, etc., which are not specifically limited in the embodiments of the present application.

It should also be noted that in this embodiment of the present application, the decoder can arrange the at least one node according to a preset decoding order in order to determine the index number corresponding to each node. In this way, according to the index number corresponding to each node, the decoder can process each node in the point cloud to be processed according to the preset decoding order.

In some embodiments, the preset decoding order may be one of the following: point cloud original order, Morton order, Hilbert order, etc., which is not specifically limited in the embodiments of this application.

It can be understood that the initial reference set represents the initial reference range for each node to search for prediction nodes, and the reference nodes within this range are all decoded nodes before the current node. Specifically, assuming that the index number of the current node is i, then the nodes with index numbers 0 to i-1 are all decoded nodes, and the initial reference set is determined based on these decoded nodes.

In some embodiments, the initial reference set is composed of N decoded reference nodes; the method may also include:

If the index number of the current node is greater than or equal to 0 and less than the preset constant value, then it is determined that the value of N is equal to the index number of the current node;

If the index number of the current node is greater than or equal to the preset constant value, it is determined that the value of N is equal to the preset constant value.

It should be noted that in this embodiment of the present application, the maximum value of the initial reference set for each node to search for prediction nodes is a fixed value, which can be represented by a preset constant value. In other words, the preset constant value represents the maximum number of reference nodes included in the initial reference set. For example, the preset constant value may be 128, but this is not specifically limited.

It should also be noted that, in the embodiment of the present application, N is an integer greater than or equal to 0 and less than or equal to a preset constant value. If N is equal to 0, then the initial reference set is an empty set; if N is not equal to 0, then the initial reference set is a non-empty set.

In a specific embodiment, assuming that the preset constant value is 128 and the initial reference set is composed of N decoded reference nodes, then when the current node is the 0th to 127th node, that is, the index number i of the current node =0~127, at this time N=i; otherwise, N=128.

S702: Based on the parity characteristics of the index sequence number, determine the target position corresponding to the current node in the initial reference set.

S703: After decoding the current node according to the initial reference set, place the current node at the target position to obtain the target reference set.

It should be noted that, in this embodiment of the present application, the target reference set represents the initial reference set corresponding to the next node in the preset decoding order of the current node.

It should also be noted that in some embodiments, after decoding the current node according to the initial reference set, placing the current node at the target location may include:

When the index number of the current node is greater than or equal to 0 and less than the preset constant value, directly place the current node at the target position in the initial reference set;

When the index number of the current node is greater than or equal to the preset constant value, the current node is used to replace the reference node at the target position.

Here, in this embodiment of the present application, the method may also include: when the index number of the current node is greater than or equal to 0 and less than a preset constant value, after decoding the current node according to the initial reference set, decoding the current node The nodes are placed in the initial reference set according to the preset decoding order to obtain the target reference set.

That is to say, for the case where the index number of the current node is greater than or equal to 0 and less than the preset constant value, after completing the decoding process of the current node, the current node can be placed in the initial reference set according to the preset decoding order, or The target position can also be determined based on the parity characteristics of the index number, and then the current node is directly placed at the corresponding target position in the initial reference set to obtain the target reference set; for the index number of the current node is greater than or equal to the preset constant value In this case, after completing the decoding process of the current node, the target position corresponding to the current node in the initial reference set is determined based on the parity characteristics of the index sequence number, and then the current node is used to replace the reference node at the target position to obtain the target reference set. .

In some embodiments, decoding the current node according to the initial reference set may include:

Parse the code stream and determine the attribute residual value corresponding to the current node;

According to the initial reference set, determine the attribute prediction value corresponding to the current node;

Based on the attribute residual value and attribute prediction value, the attribute reconstruction value corresponding to the current node is determined.

It should be noted that in this embodiment of the present application, after obtaining the code stream, the decoder can parse the attribute residual value corresponding to the current node from the code stream. Among them, the attribute residual value parsed in the code stream is the residual value after inverse transformation and inverse quantization.

It should also be noted that in the embodiment of the present application, determining the attribute reconstruction value corresponding to the current node based on the attribute residual value and the attribute predicted value may include: performing an addition calculation on the attribute residual value and the attribute predicted value, Get the attribute reconstruction value corresponding to the current node.

It should also be noted that in this embodiment of the present application, determining the attribute prediction value corresponding to the current node based on the initial reference set may include: if the index number of the current node is equal to 0, then determining that the initial reference set is an empty set, The preset attribute value is directly determined as the attribute prediction value corresponding to the current node; if the index number of the current node is not equal to 0, the initial reference set is determined to be a non-empty set, and at least one prediction node is determined from the initial reference set, based on at least one The prediction node determines the attribute prediction value corresponding to the current node.

That is to say, if the initial reference set is an empty set, there is no prediction node at this time, and the attribute prediction value corresponding to the current node can be directly set to the preset attribute value. For example, for the color attribute, the preset attribute value can be (128, 128, 128); for the reflectance attribute, the preset attribute value can be 0; after completing the decoding process of the current node, the current node can be placed in the preset decoding order The current node can be placed at position 1 in the initial reference set according to the parity characteristics of the index number. If the initial reference set is a non-empty set, then at least one prediction node can be obtained based on the initial reference set, and then the attribute prediction value corresponding to the current node is determined based on the at least one prediction node.

In a specific embodiment, when the index number of the current node is not equal to 0, determining the attribute prediction value corresponding to the current node based on at least one prediction node may include:

Obtain the respective attribute reconstruction value of at least one prediction node;

If at least one prediction node includes only one prediction node, the attribute reconstruction value of the prediction node is directly determined as the attribute prediction value corresponding to the current node;

If at least one prediction node includes at least two prediction nodes, a weighted average calculation is performed on the respective attribute reconstruction values of the at least two prediction nodes to obtain the attribute prediction value corresponding to the current node.

It should be noted that for the weighted average calculation, in one possible implementation, if the weight values are all set to 1, then the weighted average calculation is performed on the respective attribute reconstruction values of at least two prediction nodes, that is, the weighted average calculation is performed on at least two prediction nodes. The reconstructed attribute values of each of the two prediction nodes are averaged. In another possible implementation, if among the at least two prediction nodes, it is assumed that the weight value of the first type node is 1, the weight value of the second type node is 1/2, and the weight value of the third type node is 1/3, then a weighted average calculation can be performed on the respective attribute reconstruction values of the at least two prediction nodes based on these weight values.

In a specific embodiment, when the index number of the current node is not equal to 0, determining at least one prediction node from the initial reference set may include:

If the index number of the current node is equal to 1, then determine one reference node included in the initial reference set as at least one prediction node;

If the index number of the current node is equal to 2, determine the two reference nodes included in the initial reference set as at least one prediction node;

If the index number of the current node is greater than or equal to 3, obtain a preset number of reference nodes with a relatively small distance value from the current node from the initial reference set, and determine the preset number of reference nodes as at least one prediction node .

It should be noted that the preset number can be set to k; wherein k can be a fixed value (for example, 3) or a range (for example, 3 to 16), which is not specifically limited in the embodiment of the present application.

It should also be noted that in the embodiment of the present application, for the situation where the index number of the current node is greater than or equal to 3, in a specific implementation manner, it can be divided into two situations:

If the index number of the current node is greater than or equal to 3 and less than or equal to the preset constant value, the first m reference nodes of the current node in the preset decoding order are obtained from the initial reference set, and the m reference nodes are determined to be at least one prediction node;

If the index number of the current node is greater than the preset constant value, k reference nodes with relatively small distance values from the current node are obtained from the initial reference set, and the k reference nodes are determined as at least one prediction node.

Here, m is an integer greater than zero. Normally, the value of m is equal to 3, but there is no specific limit.

In a specific implementation, assuming i represents the index number of the current node, then for the prediction node, if i=0, then there is no prediction node; if i=1, the initial reference set includes the 0th node. , the 0th node can be directly determined as the prediction node; if i=2, the initial reference set includes the 0th node and the 1st node, and the 0th node and the 1st node can be directly determined as the prediction node; if i>= 3 and i<=128, then obtain the first 3 reference nodes of the current node in the preset decoding order from the initial reference set, and determine these 3 reference nodes as prediction nodes; if i>128, obtain the first 3 reference nodes of the current node in the preset decoding order from the initial reference set Obtain k reference nodes with relatively small distance values from the current node, and determine the k reference nodes as prediction nodes. In another specific implementation, the case of i<3 is the same as the aforementioned implementation; if i>=3, k reference nodes with relatively small distance values from the current node are obtained from the initial reference set. , determine k reference nodes as prediction nodes.

Further, in some embodiments, when the index number of the current node is greater than a preset constant value, the preset number of reference nodes with a relatively small distance value from the current node is obtained from the initial reference set. , which can include:

From the initial reference set, use the global search method to obtain a preset number of reference nodes with a relatively small distance value from the current node; or,

From the initial reference set, use the spatial relationship search method to obtain a preset number of reference nodes with a relatively small distance value from the current node; or,

From the initial reference set, the spatial relationship depth-first search method is used to obtain a preset number of reference nodes with a relatively small distance value from the current node.

That is to say, in this embodiment of the present application, the preset number of reference nodes can be determined by searching in the initial reference set using a global search method, or searching in the initial reference set using a spatial relationship search method, or by searching in the initial reference set. The spatial relationship depth-first search method can be used to search in the initial reference set, and other search methods can even be used to search in the initial reference set, etc., which are not specifically limited here.

In a possible implementation, using a global search method to obtain a preset number of reference nodes with a relatively small distance value from the current node may include:

Calculate the distance value between each reference node in the initial reference set and the current node, and select a preset number of distance values with relatively small distance values from the obtained N distance values;

Determine a preset number of reference nodes based on a preset number of distance values.

It should be noted that in the embodiment of the present application, the distance value between each reference node in the initial reference set and the current node can be calculated using the Manhattan distance calculation method, the Euclidean distance calculation method, etc., which will not be specified in the embodiment of the present application. limited.

It should also be noted that the preset quantity is represented by k. In this way, since the initial reference set includes N reference nodes, N distance values can be calculated; k distance values with the smallest distance values are selected from these N distance values, and then the reference node determined based on these k distance values is The k reference nodes closest to the current node are used as k prediction nodes.

In another possible implementation, using a spatial relationship search method to obtain a preset number of reference nodes with relatively small distance values from the current node may include:

Based on the spatial relationship between nodes, search for reference nodes that meet the preset conditions from the initial reference set, and obtain M reference nodes;

Calculate the distance value between each of the M reference nodes and the current node, select K distance values with relatively small distance values from the obtained M distance values, and determine K references based on the K distance values node;

If K is equal to the preset number, then the K reference nodes are used as the preset number of reference nodes.

In the embodiment of this application, the reference nodes that meet the preset conditions include at least: child nodes in the upper block of the current node, child nodes in the neighbor block coplanar with the upper block of the current node, and upper blocks of the current node. Child nodes within neighbor blocks that are collinear and child nodes within neighbor blocks that have a common point with the block above the current node.

It should also be noted that in this embodiment of the present application, the upper-layer block of the current node includes at least one of the following: the parent block of the current node and the grandfather block of the current node.

It should also be noted that in the embodiment of the present application, the distance value between each of the M reference nodes and the current node can be calculated using the Manhattan distance calculation method, the Euclidean distance calculation method, etc., in the embodiment of the present application No specific limitation is made. In addition, M is an integer greater than or equal to 0, and K is an integer greater than or equal to 0 and less than or equal to M.

In this way, based on the spatial relationship between nodes, the parent block of the current node (or, the grandfather block of the current node, etc.) itself and the parent block of the current node (or, the grandfather block of the current node, etc.) can be searched from the initial reference set. etc.) sub-nodes in the neighbor blocks that are coplanar, collinear, and co-point, get M reference nodes; then determine the k reference nodes closest to the current node from these M reference nodes as k prediction nodes .

Furthermore, if the point cloud to be processed is a sparse point cloud and k prediction nodes cannot be determined from these M reference nodes, then it is necessary to enter the global search mode to continue searching for reference nodes in order to complete the k prediction nodes. Therefore, in some embodiments, the method may further include:

If K is less than the preset number, the global search method is used to calculate the distance value between the reference node in the initial reference set and the current node, and the node with a relatively small distance value is determined based on the comparison result between the distance value and the K distance values. A preset number of distance values, and a preset number of reference nodes are determined based on the preset number of distance values.

It should be noted that after using the spatial relationship search method to determine M reference nodes, if only K reference nodes with relatively small distance values can be selected from the M reference nodes, and K is less than the second number, k is not satisfied. prediction nodes, then you need to enter the global search mode, calculate the distance value between the reference node in the initial reference set and the current node, and determine the relative distance value based on the comparison result between the calculated distance value and K distance values. A small preset number of reference nodes can be used to complete k prediction nodes.

In yet another possible implementation, using a spatial relationship depth-first search method to obtain a preset number of reference nodes with a relatively small distance value from the current node may include:

Based on the spatial relationship between nodes, search the child nodes in the upper block of the current node from the initial reference set to obtain K1 reference nodes;

Calculate the distance value between each of the K1 reference nodes and the current node, select K2 distance values with relatively small distance values from the obtained K1 distance values, and determine K2 references based on the K2 distance values node;

If K2 is equal to the preset number, then K2 reference nodes are used as the preset number of reference nodes;

If K2 is less than the preset number, continue to search for child nodes in the neighbor block that are coplanar with the upper block of the current node from the initial reference set, and obtain K3 reference nodes;

Calculate the distance value between each of the K3 reference nodes and the current node, and determine K4 distance values with relatively small distance values based on the comparison results of the K3 distance values and K2 distance values. According to K4 The distance values determine K4 reference nodes;

If K4 is equal to the preset number, then K4 reference nodes are used as the preset number of reference nodes;

If K4 is less than the preset number, continue to search from the initial reference set for child nodes in the neighbor block that are collinear with the upper block of the current node, and obtain K5 reference nodes;

Calculate the distance value between each of the K5 reference nodes and the current node, and determine K6 distance values with relatively small distance values based on the comparison results of the K5 distance values and K4 distance values. According to K6 The distance values determine K6 reference nodes;

If K6 is equal to the preset number, then K6 reference nodes are used as the preset number of reference nodes;

If K6 is less than the preset number, continue to search from the initial reference set for child nodes in the neighbor block that have the same point as the upper block of the current node, and obtain K7 reference nodes;

Calculate the distance value between each of the K7 reference nodes and the current node, and determine K8 distance values with relatively small distance values based on the comparison results of the K7 distance values and K6 distance values. According to K8 The distance values determine K8 reference nodes;

If K8 is equal to the preset number, then K8 reference nodes will be used as the preset number of reference nodes;

If K8 is less than the preset number, the global search method is used to calculate the distance value between the reference node in the initial reference set and the current node, and the node with a relatively small distance value is determined based on the comparison result between the distance value and the K8 distance values. A preset number of distance values, and a preset number of reference nodes are determined based on the preset number of distance values.

It should be noted that in this embodiment of the present application, the upper-level block of the current node includes at least one of the following: the parent block of the current node and the grandfather block of the current node.

It should also be noted that in the embodiment of the present application, the distance value between each of the M reference nodes and the current node can be calculated using the Manhattan distance calculation method, the Euclidean distance calculation method, etc., in the embodiment of the present application No specific limitation is made.

It should also be noted that in the embodiment of the present application, the child nodes in the neighbor blocks that are coplanar with the upper block of the current node are searched from the initial reference set. If there are multiple coplanar adjacent blocks, then these many Coplanar neighbor blocks can be searched at once or sequentially. For example, when searching sequentially, you can first search in the first coplanar neighbor block. If k reference nodes are completed in the search, then the search will no longer be performed; if k reference nodes are not completed, then the search will be performed in the first coplanar neighbor block. Search within the second coplanar neighbor block. If the search completes k reference nodes, then the search will no longer be performed; otherwise, the search will continue within the third coplanar neighbor block, and so on. In the same way, the same can be done for searching from the initial reference set for child nodes in the neighbor block that are collinear with the upper block of the current node, and from the initial reference set for searching for child nodes in the neighbor block that are in common with the upper block of the current node. Operation; no restrictions are made here.

In this way, in the spatial relationship depth-first search method, based on the spatial relationship between nodes, the first step can be to search for the children in the parent block of the current node (or the grandfather block of the current node, etc.) from the initial reference set. node, if k predicted nodes are not satisfied, then the second step can be to search the child nodes in the coplanar neighbor block of the parent block of the current node (or, the grandfather block of the current node, etc.) from the initial reference set, if it is still not satisfied k predicted nodes, then the third step can be to search the child nodes in the collinear neighbor block of the current node's parent block (or, the current node's grandparent block, etc.) from the initial reference set. If k predicted nodes are still not satisfied, Then the fourth step can be to search from the initial reference set for the child nodes in the neighbor blocks that are common to the parent block of the current node (or the grandfather block of the current node, etc.). If the sum of the previous four steps does not satisfy k predicted nodes, Then the fifth step is to enter the global search mode and calculate the distance value between the reference node in the initial reference set and the current node in order to complete the k prediction nodes.

It can be understood that in the embodiment of the present application, whether it is a spatial relationship search method or a spatial relationship depth-first search method, the search process based on spatial relationships is described as follows:

(a) First, based on the position of the current node in the parent block (or grandfather block, etc.), determine the neighbor blocks that are coplanar, collinear, and common with its parent block (or grandfather block, etc.). As shown in Figures 8A to 8H, there are eight modes for the orientation of the current node, including: the mode in which the current node is in the upper right side of the back as shown in Figure 8A, the mode in which the current node is in the lower right side of the back as shown in Figure 8B, The current node shown in Figure 8C is in the upper left mode of the back side, the current node shown in Figure 8D is in the lower left mode of the back side, the current node shown in Figure 8E is in the upper right mode of the front side, the current node shown in Figure 8F is in A mode in which the front side is lower right, a mode in which the current node shown in FIG. 8G is in a front upper left position, a mode in which the current node shown in FIG. 8H is in a front lower left mode, etc. For these eight modes, Figures 9A to 9H respectively show the corresponding coplanar neighbor blocks, collinear neighbor blocks, and co-point neighbor blocks in each mode. Among them, in Figures 9A to 9H, the parent block (or grandparent block, etc.) of the current node is represented by a bold box and filled with white, the coplanar neighbor blocks are filled with grid lines, and the collinear neighbor blocks are filled with diagonal lines. Point neighbor blocks are filled with points.

For example, taking Hilbert code (or Morton code, etc.) as an example, through the geometric coordinates of the current node's parent block (or grandparent block, etc.), plus a certain offset, it can be calculated The geometric coordinates of neighbor blocks can be used to calculate the corresponding Hilbert code. The offsets corresponding to the eight modes are:

hilbertShift[8][7][3]={

{{0,-1,0},{-1,0,0},{0,0,-1},{-1,-1,0},{-1,0,-1},{0 ,-1,-1},{-1,-1,-1}},

{{0,-1,0},{-1,0,0},{0,0,1},{-1,-1,0},{-1,0,1},{0,- 1,1},{-1,-1,1}},

{{0,1,0},{-1,0,0},{0,0,-1},{-1,1,0},{-1,0,-1},{0,1 ,-1},{-1,1,-1}},

{{0,1,0},{-1,0,0},{0,0,1},{-1,1,0},{-1,0,1},{0,1,1 },{-1,1,1}},

{{0,-1,0},{1,0,0},{0,0,-1},{1,-1,0},{1,0,-1},{0,-1 ,-1},{1,-1,-1}},

{{0,-1,0},{1,0,0},{0,0,1},{1,-1,0},{1,0,1},{0,-1,1 },{1,-1,1}},

{{0,1,0},{1,0,0},{0,0,-1},{-1,1,0},{1,0,-1},{0,1,- 1},{1,1,-1}},

{{0,1,0},{1,0,0},{0,0,1},{1,1,0},{1,0,1},{0,1,1},{ 1,1,1}}

}

(b) By comparing the Hilbert code of the reference node in the initial reference set with the Hilbert code of the neighbor block, it can be determined whether the reference node satisfies the conditions of coplanar, collinear, and common points.

It can also be understood that in this embodiment of the present application, the target position corresponding to the current node in the initial reference set needs to be determined based on the parity characteristics of the index sequence number, so that after the decoding process of the current node is completed, the current node can be used Replaces the reference node at the target location.

In some embodiments, determining the target position corresponding to the current node in the initial reference set based on the parity characteristics of the index sequence number may include: determining from the initial reference set that is opposite to the parity characteristics of the index sequence number and is placed earliest in the initial reference set. The target reference node in the set determines the position corresponding to the target reference node as the target position.

It should be noted that, taking the preset constant value of 128 as an example, if the index number i of the current node is an even number, then the value of the target position can be equal to the remainder of i and 128 plus 1; if the index number i of the current node is is an odd number, then the value of the target position can be equal to the remainder of i and 128 minus 1. For example, if the index number of the current node is 128, then the target position is 1; if the index number of the current node is 129, then the target position is 0; if the index number of the current node is 130, then the target position is 3; if The index number of the current node is 131, then the target position is 2; and so on.

In some embodiments, determining the target position corresponding to the current node in the initial reference set based on the parity characteristics of the index sequence number may include: in the initial reference set, determining a set of candidate references that are placed earliest according to the preset step size. Node; determine the target reference node that is opposite to the parity characteristics of the index sequence number from a group of candidate reference nodes, and determine the position corresponding to the target reference node as the target position.

It should be noted that in the embodiment of the present application, the preset step size is the step size used for determining the parity characteristics. The value of the preset step size can be changed. For example, the preset step size can be set to 2, 4, 8, etc., and there is no specific limit here.

For example, when the preset step size is equal to 4, take the circular cache as an example:

If the current node is the 128th node (that is, the index number is 128), then it is placed at position 3 in the initial reference set;

If the current node is the 129th node (that is, the index number is 129), then it is placed at position 2 in the initial reference set;

If the current node is the 130th node (that is, the index number is 130), then it is placed at position 1 in the initial reference set;

If the current node is the 131st node (that is, the index number is 131), then it is placed at position 0 in the initial reference set;

If the current node is the 132nd node (that is, the index number is 132), then it is placed at position 7 in the initial reference set;

If the current node is the 133rd node (that is, the index number is 133), then it is placed at position 6 in the initial reference set;

If the current node is the 134th node (that is, the index number is 134), then it is placed at position 5 in the initial reference set;

If the current node is the 135th node (that is, the index number is 135), then it is placed at position 4 in the initial reference set;

And so on until the last node. Among them, the same can be said for first-in, first-out.

It should also be noted that in the embodiment of the present application, the placement method within a preset step size can also be changed. For example, when the preset step size is equal to 4, take the circular cache as an example:

If the current node is the 128th node (that is, the index number is 128), then it is placed at position 3 in the initial reference set;

If the current node is the 129th node (that is, the index number is 129), then it is placed at position 0 in the initial reference set;

If the current node is the 130th node (that is, the index number is 130), then it is placed at position 1 in the initial reference set;

If the current node is the 131st node (that is, the index number is 131), then it is placed at position 2 in the initial reference set;

If the current node is the 132nd node (that is, the index number is 132), then it is placed at position 7 in the initial reference set;

If the current node is the 133rd node (that is, the index number is 133), then it is placed at position 4 in the initial reference set;

If the current node is the 134th node (that is, the index number is 134), then it is placed at position 5 in the initial reference set;

If the current node is the 135th node (that is, the index number is 135), then it is placed at position 6 in the initial reference set;

And so on until the last node. Among them, the same can be said for first-in, first-out.

In some embodiments, the method may further include: when the index number is greater than or equal to a preset constant value, determining the tail position of the initial reference set as the corresponding target position of the current node in the initial reference set;

After decoding the current node according to the initial reference set, delete the reference node at the head position of the initial reference set and place the current node at the target position to obtain the target reference set.

It should be noted that, in the embodiment of the present application, the head position of the team represents the corresponding position in the initial reference set of the value obtained by using the index number of the current node and the preset constant value to perform a remainder operation; the tail position of the team represents the current node The position to be placed; therefore, after completing the decoding process of the current node, the point at the head position of the team in the initial reference set can be eliminated, and the current node can be added to the tail position of the team in the initial reference set; it can also be regarded as using the current node to replace the head position of the team The reference node at the location to get the target reference set.

In a specific embodiment, if k prediction nodes are searched based on spatial relationships, the current node is decoded, and then the point at the head of the initial reference set is eliminated, and the current node is added to the tail of the initial reference set. Position; only when entering the global search, the target position will be determined in the initial reference set based on the parity characteristics of the index sequence number, and then the current node will be used to replace the reference node at the target position to obtain the target reference set.

In some embodiments, the initial reference set may include a first initial reference set and a second initial reference set; the method may further include:

After decoding the current node according to the first initial reference set, a first target reference set is obtained; wherein the first target reference set is obtained by replacing the reference node at the target position in the first initial reference set based on the current node; and/ or

After decoding the current node according to the second initial reference set, a second target reference set is obtained; wherein the second target reference set is based on deleting the reference node at the target position in the second initial reference set and placing the current node in the queue. The tail position is obtained.

In a specific embodiment, the method may also include: if the current node uses the spatial relationship search method or the spatial relationship depth first search method, decoding the current node according to the second initial reference set; if the current node uses the global In search mode, the current node is decoded according to the first initial reference set.

It should be noted that the first target reference set is the first initial reference set of the next node of the current node in the preset decoding order, which can be regarded as the reference range 1; the second target reference set is the current node in the preset decoding order. The second initial reference set of the next node on can be regarded as reference range 2. That is to say, the embodiment of the present application can maintain two reference ranges, and the contents in reference range 1 and reference range 2 are consistent, but the order is inconsistent. Here, reference range 1 is based on the parity characteristics of the index sequence number to determine the target position and is maintained by replacing the reference node at the target position with the current node, while reference range 2 is based on deleting the point at the target position and placing the current node is maintained at the end of the queue; this ensures that the reference nodes in reference range 2 are arranged in Hilbert order, which can speed up searches based on spatial relationships; therefore, when determining prediction nodes based on spatial relationships, in reference range 2 Search in; when entering global search to determine the prediction node, search in reference range 1.

In addition, in some embodiments, after decoding the current node, the method may also include:

If the current node uses the spatial relationship search method or the spatial relationship depth-first search method, then determining the first target reference set and the second target reference set is based on deleting the reference node at the head of the team and placing the current node at the end of the team. way to maintain;

If the current node uses the global search method, it is determined that the first target reference set is maintained based on the current node replacing the reference node at the target position, and the second target reference set is based on deleting the reference node at the target position and placing the current node at The position at the end of the team is maintained.

It should be noted that the embodiments of this application can maintain two reference ranges. If k prediction nodes are found based on the spatial relationship, then the current node is decoded, and then the reference range 1 and reference range 2 are maintained by excluding the point at the head of the team and adding the current node to the tail of the team; when entering When it comes to global search, reference range 1 is determined by the parity characteristics of the index sequence number and maintained by replacing the reference node at the target position with the current node, while reference range 2 is maintained by eliminating points at the target position. The current node is added to the end of the queue to maintain it.

It should also be noted that in the embodiment of the present application, the head position of the team represents the corresponding position in the initial reference set of the value obtained by using the index number of the current node and the preset constant value to perform a remainder operation; the tail position of the team represents the current position in the initial reference set. The position where the node is to be placed; therefore, after completing the decoding process of the current node, the point at the head of the team can be eliminated and the current node added to the tail of the team; it can also be regarded as using the current node to replace the reference node at the head of the team.

This embodiment provides a decoding method, through which the reference range can be determined. Specifically, the reference range is constructed through the parity of the index number corresponding to the current node, and the prediction node is searched within this reference range for prediction. Intra-frame prediction of point cloud attributes can not only reduce encoding and decoding efficiency based on spatial relationships, but also improve intra-frame prediction accuracy through global search, achieving a good compromise between coding efficiency and performance, thereby improving the accuracy of point cloud attributes. Codec performance.

In another embodiment of the present application, see FIG. 10 , which shows a schematic flowchart of an encoding method provided by an embodiment of the present application. As shown in Figure 10, the method may include:

S1001: Determine the index sequence number and initial reference set corresponding to the current node.

It should be noted that the encoding method described in the embodiment of the present application specifically refers to a point cloud encoding method, and more specifically, an intra-frame prediction method of point cloud attributes, which is used to construct a reference range for determining prediction nodes. This method can be applied to point cloud encoders (also simply called "encoders").

It should also be noted that in this embodiment of the present application, the point cloud to be processed includes at least one node. Among them, for the node in the point cloud to be processed, when encoding the node, it can be used as the node to be encoded in the point cloud to be processed, and there are multiple encoded nodes around the node. Here, the current node is the node to be encoded that currently needs to be encoded among the at least one node.

Further, in the embodiment of this application, for each node in the point cloud to be processed, it corresponds to a geometric information and an attribute information; wherein, the geometric information represents the spatial relationship of the point, and the attribute information represents the attribute information of the point. . Here, the attribute information may be color components, reflectivity or other attributes, which are not specifically limited in the embodiments of this application.

It should also be noted that in this embodiment of the present application, the encoder can arrange the at least one node according to a preset encoding order to determine the index number corresponding to each node. In this way, according to the index number corresponding to each node, the encoder can process each node in the point cloud to be processed according to the preset encoding order.

In some embodiments, the preset encoding order may be one of the following: point cloud original order, Morton order, Hilbert order, etc., which is not specifically limited in the embodiments of this application.

It can be understood that the initial reference set represents the initial reference range for each node to search for prediction nodes, and the reference nodes within this range are all coded nodes before the current node. Specifically, assuming that the index number of the current node is i, then the nodes with index numbers 0 to i-1 are all coded nodes, and the initial reference set is determined based on these coded nodes.

In some embodiments, the initial reference set is composed of N coded reference nodes; the method may also include:

If the index number of the current node is greater than or equal to 0 and less than the preset constant value, then it is determined that the value of N is equal to the index number of the current node;

If the index number of the current node is greater than or equal to the preset constant value, it is determined that the value of N is equal to the preset constant value.

It should be noted that in this embodiment of the present application, the maximum value of the initial reference set for each node to search for prediction nodes is a fixed value, which can be represented by a preset constant value. In other words, the preset constant value represents the maximum number of reference nodes included in the initial reference set. For example, the preset constant value may be 128, but this is not specifically limited.

It should also be noted that, in the embodiment of the present application, N is an integer greater than or equal to 0 and less than or equal to a preset constant value. If N is equal to 0, then the initial reference set is an empty set; if N is not equal to 0, then the initial reference set is a non-empty set.

In a specific embodiment, assuming that the preset constant value is 128 and the initial reference set is composed of N coded reference nodes, then when the current node is the 0th to 127th node, that is, the index number i of the current node =0~127, at this time N=i; otherwise, N=128.

S1002: Based on the parity characteristics of the index sequence number, determine the target position corresponding to the current node in the initial reference set.

S1003: After encoding the current node according to the initial reference set, place the current node at the target position to obtain the target reference set.

It should be noted that, in this embodiment of the present application, the target reference set represents the initial reference set corresponding to the next node in the preset coding sequence of the current node.

It should also be noted that in some embodiments, after decoding the current node according to the initial reference set, placing the current node at the target location may include:

When the index number of the current node is greater than or equal to 0 and less than the preset constant value, directly place the current node at the target position in the initial reference set;

When the index number of the current node is greater than or equal to the preset constant value, the current node is used to replace the reference node at the target position.

Here, in this embodiment of the present application, the method may also include: when the index number of the current node is greater than or equal to 0 and less than a preset constant value, after encoding the current node according to the initial reference set, the current node The nodes are placed in the initial reference set according to the preset coding order to obtain the target reference set.

In some embodiments, encoding the current node according to the initial reference set may include:

Get the original value of the attribute corresponding to the current node;

According to the initial reference set, determine the attribute prediction value corresponding to the current node;

Determine the attribute residual value corresponding to the current node based on the original attribute value and the attribute predicted value;

Encode the attribute residual value and write the resulting encoded bits into the code stream.

In a specific embodiment, determining the attribute residual value corresponding to the current node based on the original attribute value and the predicted attribute value may include: performing a subtraction calculation on the original attribute value and the predicted attribute value to obtain the attribute residual value corresponding to the current node. Attribute residual value.

It should be noted that in this embodiment of the present application, the attribute residual value written into the code stream is the residual value after transformation and quantization. That is to say, the attribute residual value is encoded, including transforming and quantizing the attribute residual value, and then writing it into the code stream according to the encoding bits.

In some embodiments, determining the attribute prediction value corresponding to the current node based on the initial reference set may include: if the index number is equal to 0, determining the initial reference set to be an empty set, and directly determining the preset attribute value as the current node. The corresponding attribute prediction value; if the index number is not equal to 0, determine that the initial reference set is a non-empty set, determine at least one prediction node from the initial reference set, and determine the attribute prediction value corresponding to the current node based on at least one prediction node.

It should be noted that when the index number is equal to 0, it means that the initial reference set is an empty set. At this time, there is no prediction node, and the attribute prediction value corresponding to the current node can be directly set to the preset attribute value. For example, for the color attribute, the preset attribute value can be (128,128,128); for the reflectance attribute, the preset attribute value can be 0; after completing the encoding process of the current node, the current node can be placed in the initial position according to the preset encoding order. The head position of the queue is 0 in the reference set; or the current node can be placed at position 1 in the initial reference set according to the parity characteristics of the index sequence number.

It should also be noted that when the index number is not equal to 0, determining at least one prediction node from the initial reference set may include:

If the index number is equal to 1, then one reference node included in the initial reference set is determined as at least one prediction node;

If the index number is equal to 2, determine the two reference nodes included in the initial reference set as at least one prediction node;

If the index number of the current node is greater than or equal to 3, obtain a preset number of reference nodes with a relatively small distance value from the current node from the initial reference set, and determine the preset number of reference nodes as at least one prediction node .

It should be noted that the preset number can be set to k; wherein k can be a fixed value (for example, 3) or a range (for example, 3 to 16), which is not specifically limited in the embodiment of the present application.

It should also be noted that in the embodiment of the present application, for the situation where the index number of the current node is greater than or equal to 3, in a specific implementation manner, it can be divided into two situations:

If the index number is greater than or equal to 3 and less than or equal to the preset constant value, obtain the first m reference nodes of the current node in the preset coding order from the initial reference set, and determine the m reference nodes as at least one prediction node;

If the index number is greater than the preset constant value, k reference nodes with relatively small distance values from the current node are obtained from the initial reference set, and the k reference nodes are determined as at least one prediction node.

Here, m is an integer greater than zero. Normally, the value of m is equal to 3, but there is no specific limit.

In this embodiment of the present application, after at least one prediction node is determined, determining the attribute prediction value corresponding to the current node based on the at least one prediction node may include:

Obtain the respective attribute reconstruction value of at least one prediction node;

If at least one prediction node includes only one prediction node, the attribute reconstruction value of the prediction node is directly determined as the attribute prediction value corresponding to the current node;

If at least one prediction node includes at least two prediction nodes, a weighted average calculation is performed on the respective attribute reconstruction values of the at least two prediction nodes to obtain the attribute prediction value corresponding to the current node.

Here, for the weighted average calculation, in one possible implementation, if the weight values are both set to 1, then the weighted average calculation is performed on the respective attribute reconstruction values of at least two prediction nodes, that is, the weighted average calculation is performed on at least two prediction nodes. The reconstructed values of the respective attributes of the predicted nodes are averaged.

Further, in some embodiments, when the index number of the current node is greater than a preset constant value, the preset number of reference nodes with a relatively small distance value from the current node is obtained from the initial reference set. , which can include:

From the initial reference set, use the global search method to obtain a preset number of reference nodes with a relatively small distance value from the current node; or,

From the initial reference set, use the spatial relationship search method to obtain a preset number of reference nodes with a relatively small distance value from the current node; or,

From the initial reference set, the spatial relationship depth-first search method is used to obtain a preset number of reference nodes with a relatively small distance value from the current node.

In a possible implementation, using a global search method to obtain a preset number of reference nodes with a relatively small distance value from the current node may include:

Calculate the distance value between each reference node in the initial reference set and the current node, and select a preset number of distance values with relatively small distance values from the obtained N distance values;

Determine a preset number of reference nodes based on a preset number of distance values.

In a possible implementation, using a spatial relationship search method to obtain a preset number of reference nodes with a relatively small distance value from the current node may include:

Based on the spatial relationship between nodes, search for reference nodes that meet the preset conditions from the initial reference set, and obtain M reference nodes;

Calculate the distance value between each of the M reference nodes and the current node, select K distance values with relatively small distance values from the obtained M distance values, and determine K references based on the K distance values node;

If K is equal to the preset number, then the K reference nodes are used as the preset number of reference nodes.

In the embodiment of this application, the reference nodes that meet the preset conditions include at least: child nodes in the upper block of the current node, child nodes in the neighbor block coplanar with the upper block of the current node, and upper blocks of the current node. Child nodes within neighbor blocks that are collinear and child nodes within neighbor blocks that have a common point with the block above the current node.

In the embodiment of the present application, M is an integer greater than or equal to 0, and K is an integer greater than or equal to 0 and less than or equal to M.

In this way, based on the spatial relationship between nodes, the parent block of the current node (or, the grandfather block of the current node, etc.) itself and the parent block of the current node (or, the grandfather block of the current node, etc.) can be searched from the initial reference set. etc.) sub-nodes in the neighbor blocks that are coplanar, collinear, and co-point, get M reference nodes; then determine the k reference nodes closest to the current node from these M reference nodes as k prediction nodes .

Furthermore, if the point cloud to be processed is a sparse point cloud and k prediction nodes cannot be determined from these M reference nodes, then it is necessary to enter the global search mode to continue searching for reference nodes in order to complete the k prediction nodes. Therefore, in some embodiments, the method may further include:

If K is less than the preset number, the global search method is used to calculate the distance value between the reference node in the initial reference set and the current node, and the node with a relatively small distance value is determined based on the comparison result between the distance value and the K distance values. A preset number of distance values, and a preset number of reference nodes are determined based on the preset number of distance values.

It should be noted that after using the spatial relationship search method to determine M reference nodes, if only K reference nodes with relatively small distance values can be selected from the M reference nodes, and K is less than the second number, k is not satisfied. prediction nodes, then you need to enter the global search mode, calculate the distance value between the reference node in the initial reference set and the current node, and determine the relative distance value based on the comparison result between the calculated distance value and K distance values. A small preset number of reference nodes can be used to complete k prediction nodes.

In yet another possible implementation, using a spatial relationship depth-first search method to obtain a preset number of reference nodes with a relatively small distance value from the current node may include:

Based on the spatial relationship between nodes, search the child nodes in the upper block of the current node from the initial reference set to obtain K1 reference nodes;

Calculate the distance value between each of the K1 reference nodes and the current node, select K2 distance values with relatively small distance values from the obtained K1 distance values, and determine K2 references based on the K2 distance values node;

If K2 is equal to the preset number, then K2 reference nodes are used as the preset number of reference nodes;

If K2 is less than the preset number, continue to search for child nodes in the neighbor block that are coplanar with the upper block of the current node from the initial reference set, and obtain K3 reference nodes;

Calculate the distance value between each of the K3 reference nodes and the current node, and determine K4 distance values with relatively small distance values based on the comparison results of the K3 distance values and K2 distance values. According to K4 The distance values determine K4 reference nodes;

If K4 is equal to the preset number, then K4 reference nodes are used as the preset number of reference nodes;

If K4 is less than the preset number, continue to search from the initial reference set for child nodes in the neighbor block that are collinear with the upper block of the current node, and obtain K5 reference nodes;

Calculate the distance value between each of the K5 reference nodes and the current node, and determine K6 distance values with relatively small distance values based on the comparison results of the K5 distance values and K4 distance values. According to K6 The distance values determine K6 reference nodes;

If K6 is equal to the preset number, then K6 reference nodes are used as the preset number of reference nodes;

If K6 is less than the preset number, continue to search from the initial reference set for child nodes in the neighbor block that have the same point as the upper block of the current node, and obtain K7 reference nodes;

Calculate the distance value between each of the K7 reference nodes and the current node, and determine K8 distance values with relatively small distance values based on the comparison results of the K7 distance values and K6 distance values. According to K8 The distance values determine K8 reference nodes;

If K8 is equal to the preset number, then K8 reference nodes will be used as the preset number of reference nodes;

If K8 is less than the preset number, the global search method is used to calculate the distance value between the reference node in the initial reference set and the current node, and the node with a relatively small distance value is determined based on the comparison result between the distance value and the K8 distance values. A preset number of distance values, and a preset number of reference nodes are determined based on the preset number of distance values.

It should be noted that in this embodiment of the present application, the upper-level block of the current node includes at least one of the following: the parent block of the current node and the grandfather block of the current node.

It should also be noted that in the embodiment of the present application, the distance value between each of the M reference nodes and the current node can be calculated using the Manhattan distance calculation method, the Euclidean distance calculation method, etc., in the embodiment of the present application No specific limitation is made.

It should also be noted that in the embodiment of the present application, the child nodes in the neighbor blocks that are coplanar with the upper block of the current node are searched from the initial reference set. If there are multiple coplanar adjacent blocks, then these many Coplanar neighbor blocks can be searched at once or sequentially. For example, when searching sequentially, you can first search in the first coplanar neighbor block. If k reference nodes are completed in the search, then the search will no longer be performed; if k reference nodes are not completed, then the search will be performed in the first coplanar neighbor block. Search within the second coplanar neighbor block. If the search completes k reference nodes, then the search will no longer be performed; otherwise, the search will continue within the third coplanar neighbor block, and so on. In the same way, the same can be done for searching from the initial reference set for child nodes in the neighbor block that are collinear with the upper block of the current node, and from the initial reference set for searching for child nodes in the neighbor block that are in common with the upper block of the current node. Operation; no restrictions are made here.

In this way, in the spatial relationship depth-first search method, based on the spatial relationship between nodes, the first step can be to search for the children in the parent block of the current node (or the grandfather block of the current node, etc.) from the initial reference set. node, if k predicted nodes are not satisfied, then the second step can be to search the child nodes in the coplanar neighbor block of the parent block of the current node (or, the grandfather block of the current node, etc.) from the initial reference set, if it is still not satisfied k predicted nodes, then the third step can be to search the child nodes in the collinear neighbor block of the current node's parent block (or, the current node's grandparent block, etc.) from the initial reference set. If k predicted nodes are still not satisfied, Then the fourth step can be to search from the initial reference set for the child nodes in the neighbor blocks that are common to the parent block of the current node (or the grandfather block of the current node, etc.). If the sum of the previous four steps does not satisfy k predicted nodes, Then the fifth step is to enter the global search mode and calculate the distance value between the reference node in the initial reference set and the current node in order to complete the k prediction nodes.

It can also be understood that in this embodiment of the present application, it is necessary to determine the target position corresponding to the current node in the initial reference set according to the parity characteristics of the index sequence number, so that after the encoding process of the current node is completed, the current node can be used Replaces the reference node at the target location.

In some embodiments, determining the target position corresponding to the current node in the initial reference set based on the parity characteristics of the index sequence number may include: determining from the initial reference set that is opposite to the parity characteristics of the index sequence number and is placed earliest in the initial reference set. The target reference node in the set determines the position corresponding to the target reference node as the target position.

It should be noted that, taking the preset constant value of 128 as an example, if the index number i of the current node is an even number, then the value of the target position can be equal to the remainder of i and 128 plus 1; if the index number i of the current node is is an odd number, then the value of the target position can be equal to the remainder of i and 128 minus 1. For example, if the index number of the current node is 128, then the target position is 1; if the index number of the current node is 129, then the target position is 0; and so on.

In some embodiments, determining the target position corresponding to the current node in the initial reference set based on the parity characteristics of the index sequence number may include: in the initial reference set, determining a set of candidate references that are placed earliest according to the preset step size. Node; determine the target reference node that is opposite to the parity characteristics of the index sequence number from a group of candidate reference nodes, and determine the position corresponding to the target reference node as the target position.

It should be noted that in the embodiment of the present application, the preset step size is the step size used for determining the parity characteristics. The value of the preset step size can be changed. For example, the preset step size can be set to 2, 4, 8, etc., and there is no specific limit here. In addition, in the embodiment of the present application, the placement method within a preset step can also be changed. For example, when the preset step is equal to 4, if the index number of the current node is 128 , 129, 130, 131, then place it at positions 3, 2, 1, 0 in the initial reference set; or it can also be placed at positions 3, 0, 1, 2, etc. in the initial reference set, here There is no specific limit.

In some embodiments, the method may further include: when the index number is greater than or equal to a preset constant value, determining the tail position of the initial reference set as the corresponding target position of the current node in the initial reference set;

After encoding the current node according to the initial reference set, delete the reference node at the head position of the initial reference set and place the current node at the target position to obtain the target reference set.

In a specific embodiment, if k prediction nodes are searched based on spatial relationships, the current node is encoded, and then the point at the head of the initial reference set is eliminated, and the current node is added to the tail of the initial reference set. Position; only when entering the global search, the target position will be determined in the initial reference set based on the parity characteristics of the index sequence number, and then the current node will be used to replace the reference node at the target position to obtain the target reference set.

Here, the head position of the team represents the corresponding position in the initial reference set of the value obtained by using the remainder operation of the current node's index number and the preset constant value; the tail position of the team represents the position where the current node is to be placed; therefore, after completing the current After the decoding process of the node, the point at the head position of the team in the initial reference set can be eliminated, and the current node can be added to the tail position of the team in the initial reference set; it can also be regarded as using the current node to replace the reference node at the head position of the team to obtain the target Reference collection.

In some embodiments, the initial reference set includes a first initial reference set and a second initial reference set; the method may further include:

After encoding the current node according to the first initial reference set, a first target reference set is obtained; wherein the first target reference set is obtained by replacing the reference node at the target position in the first initial reference set based on the current node; and/ or

After decoding the current node according to the second initial reference set, a second target reference set is obtained; wherein the second target reference set is based on deleting the reference node at the target position in the second initial reference set and placing the current node in the queue. The tail position is obtained.

In a specific embodiment, the method may also include: if the current node uses the spatial relationship search method or the spatial relationship depth first search method, encoding the current node according to the second initial reference set; if the current node uses the global In search mode, the current node is encoded according to the first initial reference set.

It should be noted that the first target reference set is the first initial reference set of the next node of the current node in the preset coding order, which can be regarded as the reference range 1; the second target reference set is the current node in the preset coding order. The second initial reference set of the next node on can be regarded as reference range 2. That is to say, the embodiment of the present application can maintain two reference ranges, and the contents in reference range 1 and reference range 2 are consistent, but the order is inconsistent. Here, reference range 1 is based on the parity characteristics of the index sequence number to determine the target position and is maintained by replacing the reference node at the target position with the current node, while reference range 2 is based on deleting the point at the target position and placing the current node is maintained at the end of the queue; this ensures that the reference nodes in reference range 2 are arranged in Hilbert order, which can speed up searches based on spatial relationships; therefore, when determining prediction nodes based on spatial relationships, in reference range 2 Search in; when entering global search to determine the prediction node, search in reference range 1.

In addition, in some embodiments, after encoding the current node, the method may also include:

If the current node uses the spatial relationship search method or the spatial relationship depth-first search method, then determining the first target reference set and the second target reference set is based on deleting the reference node at the head of the team and placing the current node at the end of the team. way to maintain;

If the current node uses the global search method, it is determined that the first target reference set is maintained based on the current node replacing the reference node at the target position, and the second target reference set is based on deleting the reference node at the target position and placing the current node at The position at the end of the team is maintained.

It should be noted that the embodiments of this application can maintain two reference ranges. If k prediction nodes are found based on the spatial relationship, then the current node is encoded, and then the reference range 1 and reference range 2 are maintained by excluding the point at the head of the team and adding the current node to the tail of the team; when entering When it comes to global search, reference range 1 is determined by the parity characteristics of the index sequence number and maintained by replacing the reference node at the target position with the current node, while reference range 2 is maintained by eliminating points at the target position. The current node is added to the end of the queue to maintain it.

It should also be noted that in the embodiment of the present application, the head position of the team represents the corresponding position in the initial reference set of the value obtained by using the index number of the current node and the preset constant value to perform a remainder operation; the tail position of the team represents the current position in the initial reference set. The position where the node is to be placed; therefore, after completing the encoding process of the current node, the point at the head of the team can be eliminated and the current node can be added to the tail of the team; it can also be regarded as using the current node to replace the reference node at the head of the team.

This embodiment provides a coding method through which the reference range can be determined. Specifically, the reference range is constructed through the parity of the index number corresponding to the current node, and the prediction node is searched within this reference range for prediction. Intra-frame prediction of point cloud attributes can not only reduce encoding and decoding efficiency based on spatial relationships, but also improve intra-frame prediction accuracy through global search, achieving a good compromise between coding efficiency and performance, thereby improving the accuracy of point cloud attributes. Codec performance.

In yet another embodiment of the present application, see FIG. 11 , which shows a schematic flowchart of a reference range determination provided by the embodiment of the present application. As shown in Figure 11, the process may include:

S1101: Determine the index sequence number and initial reference set corresponding to the current node.

S1102: Determine at least one prediction node according to the initial reference set, and simultaneously determine the target position where the current node is placed in the initial reference set.

S1103: Predict the current node according to at least one prediction node, and after completing the encoding/decoding process of the current node, place the current node at the determined target position to obtain a target reference set.

It should be noted that in this embodiment of the present application, the initial reference set does not include the current node, the target reference set includes the current node, and the target reference set represents the next node corresponding to the current node in the preset encoding/decoding order. Initial reference set. That is to say, the initial reference set/target reference set here is used to characterize the reference range for determining the prediction node, and the reference range is continuously updated as the current node changes.

It should also be noted that the reference range determination process shown in Figure 11 can be applied to both the encoding end and the decoding end. The embodiment of this application processes each node in the point cloud according to a fixed encoding/decoding order (for example, the original order of the point cloud, Morton order, Hilbert order, etc.) at the encoding and decoding end. The specific implementation steps are as follows:

Step 1. Assume that the maximum reference range of each node to search for predicted nodes is a fixed value, such as 128. This reference range can be composed of N reference nodes that have been encoded/decoded before the current node. If the current node is the 0th ~127 nodes (that is, when its index number i=0~127), then N=i; otherwise, N=128;

Step 2. After determining the reference range, the current node needs to determine the predicted node within the reference range, and at the same time determine the target position where the current node is placed within the reference range;

Step 3: Predict the current node based on the attribute reconstruction value of the predicted node, complete encoding/decoding of the current node, and then place the encoded/decoded current node at the target position within the reference range determined in step 2.

For step 2, the embodiment of the present application may have multiple implementation modes. Three implementation modes are taken as examples for a detailed description below.

The first implementation mode: global search (ie global search method).

Assume that the current node is Pi and the encoded/decoded reference nodes are (P0, P1,...,Pi-1).

If i=0, then the reference range is empty, and the attribute prediction value of the current node can be directly set to a fixed value (for example, for the color attribute, it can be set to (128,128,128); for the reflectance attribute, it can be set to 0). Complete After encoding/decoding, add the current node to position 1 of the reference range;

If i=1, the reference range contains the 0th node P0, then directly determine P0 as the predicted node, and after completing encoding/decoding, add the current node to position 0 of the reference range;

If i=2, the reference range includes P0 and P1, directly determine P0 and P1 as prediction nodes, and after completing encoding/decoding, add the current node to position 3 of the reference range;

If i>=3, compare the index numbers from large to small (or small to large) in the reference range to determine the closest distance (Manhattan distance, Euclidean distance, etc.) to the current node among all nodes in the reference range. k nodes (k can be a fixed value of 3, or a range of 3 to 16), these k points are used as prediction nodes of the current node. After completing encoding/decoding, if the index number of the current node is less than 128, then according to Parity adds the current node to the reference range. If the index number of the current node is greater than or equal to 128, use the current node to replace the earliest node that enters the reference range with the opposite parity of the index number of the current node, that is, the current node is added to the reference range. operation.

The second implementation mode: search based on spatial relationship (ie, spatial relationship search method).

Assume that the current node is Pi and the encoded/decoded reference nodes are (P0, P1,...,Pi-1).

If i=0, then the reference range is empty, and the attribute prediction value of the current node can be directly set to a fixed value (for example, for the color attribute, it can be set to (128,128,128); for the reflectance attribute, it can be set to 0). Complete After encoding/decoding, add the current node to position 1 of the reference range;

If i=1, the reference range contains the 0th node P0, then directly determine P0 as the predicted node, and after completing encoding/decoding, add the current node to position 0 of the reference range;

If i=2, the reference range includes P0 and P1, directly determine P0 and P1 as prediction nodes, and after completing encoding/decoding, add the current node to position 3 of the reference range;

If i>=3, then based on the spatial relationship within the reference range, first search for the parent block of the current node (or the grandfather block of the current node, etc.), and the coplanar block with the parent block of the current node (or the grandfather block of the current node, etc.), For child nodes in collinear and common-point neighbor blocks, determine the k nodes closest to the current node (Manhattan distance, Euclidean distance, etc.) within these child nodes (k can be a fixed value of 3, or a range of 3 ~16), if k prediction nodes are found, after encoding/decoding is completed through these prediction nodes, the earliest node that enters the reference range with the opposite index number parity than the current node is replaced with the current node, that is, the current point is added to the reference Range operation; if not enough k prediction nodes are found, the global search method is entered to complete 3 to 16 prediction nodes. After encoding/decoding is completed through these prediction nodes, if the index number of the current node is less than 128, then Add the current node to the reference range based on parity. If the index number of the current node is greater than or equal to 128, use the current node to replace the earliest node that enters the reference range with the opposite index parity of the current node, that is, the current node is added to the reference range. operation.

The third implementation mode: depth-first search based on spatial relationship (ie, spatial relationship depth-first search method).

Assume that the current node is Pi and the encoded/decoded reference nodes are (P0, P1,...,Pi-1).

If i=0, then the reference range is empty, and the attribute prediction value of the current node can be directly set to a fixed value (for example, for the color attribute, it can be set to (128,128,128); for the reflectance attribute, it can be set to 0). Complete After encoding/decoding, add the current node to position 1 of the reference range;

If i=1, the reference range contains the 0th node P0, then directly determine P0 as the predicted node, and after completing encoding/decoding, add the current node to position 0 of the reference range;

If i=2, the reference range includes P0 and P1, directly determine P0 and P1 as prediction nodes, and after completing encoding/decoding, add the current node to position 3 of the reference range;

If i>=3, based on the spatial relationship within the reference range, first search for the child nodes in the parent block of the current node (or the grandfather block of the current node, etc.), and determine the distance (Manhattan distance, Euclidean distance, etc.) to the current node within these child nodes. distance, etc.) (k can be a fixed value of 3, or a range of 3 to 16). If k prediction nodes are found, after encoding/decoding is completed through these prediction nodes, if the index sequence number of the current node is less than 128, the current node is added to the reference range based on parity. If the index number of the current node is greater than or equal to 128, the earliest node that enters the reference range with the opposite parity of the index number of the current node is replaced with the current node, that is, the The operation of adding the current node to the reference range; if not enough k prediction nodes are found, then based on the spatial relationship in the reference range, search for neighbor blocks that are coplanar with the parent block of the current node (or the grandfather block of the current node, etc.) Child nodes, complete 3 to 16 prediction nodes. After encoding/decoding is completed through these prediction nodes, if the index number of the current node is less than 128, the current node will be added to the reference range based on parity. If the index number of the current node is greater than Or equal to 128, use the current node to replace the earliest node that enters the reference range with the opposite index number parity than the current node, that is, the operation of adding the current node to the reference range is completed; if k prediction nodes are still not found, then Within the reference range, based on the spatial relationship, find the child nodes in the neighbor block that are collinear with the current node's parent block (or the current node's grandparent block, etc.), complete 3 to 16 prediction nodes, and complete encoding/decoding through these prediction nodes , if the index number of the current node is less than 128, the current node is added to the reference range according to the parity. If the index number of the current node is greater than or equal to 128, the current node is used to replace the earliest entry into the reference range that is opposite to the parity of the index number of the current node. range of nodes, that is, the operation of adding the current node to the reference range is completed; if the first three steps combined do not find enough k prediction nodes, then the parent block (or current node) of the current node is searched based on the spatial relationship in the reference range. grandparent block, etc.), complete 3 to 16 prediction nodes. After encoding/decoding is completed through these prediction nodes, if the index number of the current node is less than 128, the current node will be changed according to parity. Add to the reference range, if the index number of the current node is greater than or equal to 128, replace the earliest node that enters the reference range with the opposite parity of the index number of the current node with the current node, that is, the operation of adding the current node to the reference range is completed; if the previous If the total of four steps does not find enough k prediction nodes, then enter the global search mode to complete 3 to 16 prediction nodes. After encoding/decoding is completed through these prediction nodes, if the index number of the current node is less than 128, according to Parity adds the current node to the reference range. If the index number of the current node is greater than or equal to 128, use the current node to replace the earliest node that enters the reference range with the opposite parity of the index number of the current node, that is, the current node is added to the reference range. operation.

It should be noted that in the second implementation manner and the third implementation manner, the specific search method based on spatial relationships is described as follows:

(a) First, based on the position of the current node in the parent block (or grandparent block, etc.), determine the neighbor blocks that are coplanar, collinear, and common with its parent block (or grandparent block, etc.), as shown in Figure 8A to Figure 8H It shows that there are eight modes in total for the orientation of the current node. Figures 9A to 9H show the corresponding coplanar, collinear, and copoint neighbor block distribution in each mode. Taking Hilbert code (or Morton code, etc.) as an example, the geometric coordinates of the neighbor block can be calculated by adding a certain offset to the geometric coordinates of the parent block (or grandparent block, etc.) of the current node. , the corresponding Hilbert code can be calculated through geometric coordinates. The offsets corresponding to the eight modes are detailed in the above content.

(b) By comparing the Hilbert code of the node within the reference range with the Hilbert code of the neighbor block, it can be determined whether the node satisfies the conditions of coplanar, collinear, and common points.

It should also be noted that at the encoding end, the current node is predicted based on at least one prediction node. After obtaining the attribute prediction value corresponding to the current node, the attribute residual can also be calculated based on the attribute prediction value and the original attribute value corresponding to the current node. value, and then the attribute residual value needs to be written into the code stream for transmission to the decoding end. Therefore, embodiments of the present application also provide a code stream, which is generated by bit encoding based on the information to be encoded; wherein the information to be encoded at least includes: the attribute residual value corresponding to the current node.

In this way, after the attribute residual value is written into the code stream and transmitted from the encoding end to the decoding end, the decoding end receives the code stream and parses the code stream, and can obtain the attribute residual value; then the decoding end uses the same process to predict the attribute prediction value, and After adding the attribute prediction value and the attribute residual value, the attribute reconstruction value corresponding to the current node can be obtained.

The specific implementation of the foregoing embodiments is explained in detail through the above embodiments. According to the technical solutions of the foregoing embodiments, it can be seen that this technical solution provides a method for determining the reference range. Based on the parity characteristics of the index sequence number, the construction includes the current Target reference set including nodes, using this target reference set to predict point cloud attributes can improve the prediction accuracy of point cloud attributes and improve the encoding and decoding performance of point cloud attributes.

In yet another embodiment of the present application, based on the same inventive concept of the previous embodiment, see FIG. 12 , which shows a schematic structural diagram of an encoder 120 provided by an embodiment of the present application. As shown in Figure 12, the encoder 120 may include: a first determining unit 1201 and an encoding unit 1202; wherein,

The first determination unit 1201 is configured to determine the index sequence number corresponding to the current node and the initial reference set; and based on the parity characteristics of the index sequence number, determine the target position corresponding to the current node in the initial reference set;

The encoding unit 1202 is configured to, after encoding the current node according to the initial reference set, place the current node at the target position to obtain the target reference set.

In some embodiments, the first determination unit 1201 is also configured to directly place the current node at the target position in the initial reference set when the index number is greater than or equal to 0 and less than the preset constant value; when the index number is greater than Or if it is equal to the preset constant value, the current node is used to replace the reference node at the target position.

In some embodiments, the preset constant value indicates that the initial reference set includes the maximum number of reference nodes, and the target reference set indicates the initial reference set corresponding to the next node in the preset coding sequence of the current node.

In some embodiments, the initial reference set is composed of N coded reference nodes; accordingly, the first determination unit 1201 is also configured to determine N if the index number is greater than or equal to 0 and less than a preset constant value. The value is equal to the index serial number; if the index serial number is greater than or equal to the preset constant value, it is determined that the value of N is equal to the preset constant value.

In some embodiments, referring to Figure 12, the encoder 120 may also include a first prediction unit 1203 configured to obtain the original attribute value corresponding to the current node; and determine the predicted attribute value corresponding to the current node according to the initial reference set;

The first determination unit 1201 is also configured to determine the attribute residual value corresponding to the current node based on the original attribute value and the attribute predicted value;

The encoding unit 1202 is also configured to encode the attribute residual value and write the resulting encoded bits into the code stream.

In some embodiments, the first determination unit 1201 is further configured to perform subtraction calculation on the original attribute value and the predicted attribute value to obtain the attribute residual value corresponding to the current node.

In some embodiments, the first prediction unit 1203 is also configured to determine that the initial reference set is an empty set if the index number is equal to 0, and directly determine the preset attribute value as the attribute prediction value corresponding to the current node; if the index number is not If equal to 0, it is determined that the initial reference set is a non-empty set, at least one prediction node is determined from the initial reference set, and the attribute prediction value corresponding to the current node is determined based on at least one prediction node.

In some embodiments, the first determining unit 1201 is further configured to determine a reference node included in the initial reference set as at least one prediction node if the index number is equal to 1; if the index number is equal to 2, then determine the initial reference node The two reference nodes included in are determined to be at least one prediction node; if the index number is greater than or equal to 3, a preset number of reference nodes with a relatively small distance value from the current node are obtained from the initial reference set, and the prediction nodes are A number of reference nodes are determined as at least one prediction node.

In some embodiments, referring to FIG. 12 , the encoder 120 may further include a first search unit 1204 configured to obtain a relatively small preset number of distance values from the current node using a global search method from the initial reference set. reference nodes; or, from the initial reference set, use the spatial relationship search method to obtain a preset number of reference nodes with a relatively small distance value from the current node; or, from the initial reference set, use the spatial relationship depth first The search method obtains a preset number of reference nodes that have a relatively small distance value from the current node.

In some embodiments, the first search unit 1204 is also configured to calculate the distance value between each reference node in the initial reference set and the current node, and select a predetermined distance value with a relatively small distance value from the obtained N distance values. Set a number of distance values; and determine a preset number of reference nodes based on the preset number of distance values.

In some embodiments, the first search unit 1204 is also configured to search for reference nodes that meet preset conditions from the initial reference set based on the spatial relationship between nodes, and obtain M reference nodes; and calculate M reference nodes. The distance value between each reference node in the node and the current node, select K distance values with relatively small distance values from the obtained M distance values, and determine K reference nodes based on the K distance values; and if K is equal to the preset number, then the K reference nodes will be used as the preset number of reference nodes; among them, the reference nodes that meet the preset conditions include at least: child nodes in the upper block of the current node, and those in the upper block of the current node. The child nodes in the neighbor block of the face, the child nodes in the neighbor block that are collinear with the upper block of the current node, and the child nodes in the neighbor block that are in common with the upper block of the current node.

In some embodiments, the first search unit 1204 is also configured to use a global search method to calculate the distance value between the reference node in the initial reference set and the current node if K is less than the preset number, and calculate the distance value based on the distance value. The comparison result with the K distance values determines a preset number of distance values with relatively small distance values, and determines a preset number of reference nodes based on the preset number of distance values.

In some embodiments, the first search unit 1204 is also configured to search the child nodes in the upper block of the current node from the initial reference set to obtain K1 reference nodes based on the spatial relationship between nodes. ; and calculate the distance value between each of the K1 reference nodes and the current node, select K2 distance values with relatively small distance values from the obtained K1 distance values, and according to the K2 distance values determine the K2 reference nodes; if the K2 is equal to the preset number, then the K2 reference nodes are used as the preset number of reference nodes; if the K2 is less than the preset number number, then continue to search from the initial reference set for child nodes in the neighbor blocks that are coplanar with the upper block of the current node, and obtain K3 reference nodes; and calculate the relationship between each reference node and the K3 reference nodes. The distance values between the current nodes, and K4 distance values with relatively small distance values are determined based on the comparison results of the obtained K3 distance values and the K2 distance values, and K4 is determined based on the K4 distance values reference nodes; if K4 is equal to the preset number, then use the K4 reference nodes as the preset number of reference nodes; if K4 is less than the preset number, continue from the initial Search the reference set for child nodes in neighbor blocks that are collinear with the upper block of the current node to obtain K5 reference nodes; and calculate the distance between each of the K5 reference nodes and the current node. value, and determine K6 distance values with relatively small distance values based on the comparison results of the obtained K5 distance values and the K4 distance values, and determine K6 reference nodes based on the K6 distance values; if the K6 is equal to the preset number, then the K6 reference nodes are used as the preset number of reference nodes; if the K6 is less than the preset number, continue to search for the current reference node from the initial reference set. Obtain K7 reference nodes from the child nodes in the neighbor blocks that share the same point with the node's upper block; and calculate the distance value between each of the K7 reference nodes and the current node, and calculate the distance value based on the obtained K7 The comparison result between the distance values and the K6 distance values determines K8 distance values with relatively small distance values, and determines K8 reference nodes based on the K8 distance values; if the K8 is equal to the preset number, then Use the K8 reference nodes as the preset number of reference nodes; if the K8 is less than the preset number, use a global search method to calculate the distance between the reference nodes in the initial reference set and the current node. value, and determine a preset number of distance values with relatively small distance values based on the comparison result between the distance value and the K8 distance values, and determine the preset number of reference nodes based on the preset number of distance values. .

In some embodiments, the upper-level block of the current node includes at least one of the following: the parent block of the current node, or the grandfather block of the current node.

In some embodiments, the first determination unit 1201 is further configured to determine from the initial reference set the target reference node that is opposite to the parity characteristics of the index sequence number and is placed earliest in the initial reference set, and determines the position corresponding to the target reference node as target location.

In some embodiments, the first determination unit 1201 is further configured to determine a set of candidate reference nodes placed earliest according to a preset step size in the initial reference set; and determine the parity with the index sequence number from a set of candidate reference nodes. For target reference nodes with opposite characteristics, the position corresponding to the target reference node is determined as the target position.

In some embodiments, the first determination unit 1201 is also configured to determine the tail position of the initial reference set as the corresponding target position of the current node in the initial reference set when the index number is greater than or equal to the preset constant value. ;

The encoding unit 1202 is also configured to, after encoding the current node according to the initial reference set, delete the reference node at the head position in the initial reference set, and place the current node at the target position to obtain the target reference set.

In some embodiments, the initial reference set includes a first initial reference set and a second initial reference set; accordingly, the encoding unit 1202 is further configured to obtain the first target after encoding the current node according to the first initial reference set. Reference set; wherein, the first target reference set is obtained by replacing the reference node at the target position in the first initial reference set based on the current node; and/or, after encoding the current node according to the second initial reference set, the third target reference set is obtained. Two target reference sets; wherein, the second target reference set is obtained based on deleting the reference node at the target position in the second initial reference set and placing the current node at the end of the queue.

In some embodiments, the encoding unit 1202 is also configured to encode the current node according to the second initial reference set if the current node uses the spatial relationship search method or the spatial relationship depth first search method; if the current node uses the global search method , then the current node is encoded according to the first initial reference set.

In some embodiments, the first determining unit 1201 is also configured to, after encoding the current node according to the first initial reference set and/or the second initial reference set, if the current node uses the spatial relationship search method or spatial relationship depth If the priority search mode is used, the first target reference set and the second target reference set are determined to be maintained based on deleting the reference node at the head position of the team and placing the current node at the tail position of the team; if the current node uses the global search mode, then Determining the first target reference set is maintained based on the current node replacing the reference node at the target position, and the second target reference set is maintained based on deleting the reference node at the target position and placing the current node at the end of the queue.

It can be understood that in this embodiment, the "unit" may be part of a circuit, part of a processor, part of a program or software, etc., and of course may also be a module, or may be non-modular. Moreover, each component in this embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or software function modules.

If the integrated unit is implemented in the form of a software function module and is not sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this embodiment is essentially either The part that contributes to the existing technology or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions to make a computer device (can It is a personal computer, server, or network device, etc.) or processor that executes all or part of the steps of the method described in this embodiment. The aforementioned storage media include: U disk, mobile hard disk, Read Only Memory (ROM), Random Access Memory (RAM), magnetic disk or optical disk and other media that can store program code.

Therefore, embodiments of the present application provide a computer-readable storage medium for use in the encoder 120. The computer-readable storage medium stores a computer program. When the computer program is executed by the first processor, any of the foregoing embodiments can be implemented. method described in one item.

Based on the above composition of the encoder 120 and the computer-readable storage medium, see FIG. 13 , which shows a schematic diagram of the specific hardware structure of the encoder 120 provided by the embodiment of the present application. As shown in FIG. 13 , the encoder 120 may include: a first communication interface 1301 , a first memory 1302 and a first processor 1303 ; the various components are coupled together through a first bus system 1304 . It can be understood that the first bus system 1304 is used to implement connection communication between these components. In addition to the data bus, the first bus system 1304 also includes a power bus, a control bus and a status signal bus. However, for the sake of clear explanation, various buses are labeled as the first bus system 1304 in FIG. 13 . in,

The first communication interface 1301 is used for receiving and sending signals during the process of sending and receiving information with other external network elements;

The first memory 1302 is used to store a computer program capable of running on the first processor 1303;

The first processor 1303 is configured to execute: when running the computer program:

Determine the index number corresponding to the current node and the initial reference set;

Based on the parity characteristics of the index sequence number, determine the target position corresponding to the current node in the initial reference set;

After encoding the current node according to the initial reference set, the current node is placed at the target position to obtain the target reference set.

It can be understood that the first memory 1302 in the embodiment of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, non-volatile memory can be read-only memory (Read-Only Memory, ROM), programmable read-only memory (Programmable ROM, PROM), erasable programmable read-only memory (Erasable PROM, EPROM), electrically removable memory. Erase programmable read-only memory (Electrically EPROM, EEPROM) or flash memory. Volatile memory may be Random Access Memory (RAM), which is used as an external cache. By way of illustration, but not limitation, many forms of RAM are available, such as static random access memory (Static RAM, SRAM), dynamic random access memory (Dynamic RAM, DRAM), synchronous dynamic random access memory (Synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (Double Data Rate SDRAM, DDRSDRAM), enhanced synchronous dynamic random access memory (Enhanced SDRAM, ESDRAM), synchronous link dynamic random access memory (Synchlink DRAM, SLDRAM) and Direct Rambus RAM (DRRAM). The first memory 1302 of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

The first processor 1303 may be an integrated circuit chip with signal processing capabilities. During the implementation process, each step of the above method can be completed by instructions in the form of hardware integrated logic circuits or software in the first processor 1303 . The above-mentioned first processor 1303 can be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or an off-the-shelf programmable gate array (Field Programmable Gate Array, FPGA). or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. Each method, step and logical block diagram disclosed in the embodiment of this application can be implemented or executed. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present application can be directly implemented by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module can be located in random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers and other mature storage media in this field. The storage medium is located in the first memory 1302. The first processor 1303 reads the information in the first memory 1302 and completes the steps of the above method in combination with its hardware.

It will be understood that the embodiments described in this application can be implemented using hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more Application Specific Integrated Circuits (ASIC), Digital Signal Processing (DSP), Digital Signal Processing Device (DSP Device, DSPD), programmable Logic device (Programmable Logic Device, PLD), Field-Programmable Gate Array (FPGA), general-purpose processor, controller, microcontroller, microprocessor, and other devices used to perform the functions described in this application electronic unit or combination thereof. For software implementation, the technology described in this application can be implemented through modules (such as procedures, functions, etc.) that perform the functions described in this application. Software code may be stored in memory and executed by a processor. The memory can be implemented in the processor or external to the processor.

Optionally, as another embodiment, the first processor 1303 is further configured to perform the method described in any one of the preceding embodiments when running the computer program.

This embodiment provides an encoder in which a target reference set is constructed based on the parity and even characteristics of the index number, and then the target reference set is used to predict point cloud attributes, which can improve the prediction accuracy of point cloud attributes. And improve the encoding and decoding performance of point cloud attributes.

In yet another embodiment of the present application, based on the same inventive concept of the previous embodiment, see FIG. 14 , which shows a schematic structural diagram of a decoder 140 provided by an embodiment of the present application. As shown in Figure 14, the decoder 140 may include: a second determination unit 1401 and a decoding unit 1402; wherein,

The second determination unit 1401 is configured to determine the index sequence number corresponding to the current node and the initial reference set; and determine the target position corresponding to the current node in the initial reference set based on the parity characteristics of the index sequence number;

The decoding unit 1402 is configured to decode the current node according to the initial reference set, and then place the current node at the target position to obtain the target reference set.

In some embodiments, the second determination unit 1401 is also configured to directly place the current node at the target position in the initial reference set when the index number is greater than or equal to 0 and less than the preset constant value; when the index number is greater than Or equal to the preset constant value, the current node is used to replace the reference node at the target position.

In some embodiments, the preset constant value indicates that the initial reference set includes the maximum number of reference nodes, and the target reference set indicates the initial reference set corresponding to the next node in the preset decoding order of the current node.

In some embodiments, the initial reference set is composed of N decoded reference nodes; accordingly, the second determination unit 1401 is also configured to determine N if the index number is greater than or equal to 0 and less than a preset constant value. The value of is equal to the index serial number; if the index serial number is greater than or equal to the preset constant value, it is determined that the value of N is equal to the preset constant value.

In some embodiments, referring to Figure 14, the decoder 140 may also include a second prediction unit 1403 configured to determine the attribute prediction value corresponding to the current node according to the initial reference set;

The decoding unit 1402 is also configured to parse the code stream and determine the attribute residual value corresponding to the current node;

The second determination unit 1401 is also configured to determine the attribute reconstruction value corresponding to the current node based on the attribute residual value and the attribute prediction value.

In some embodiments, the second determination unit 1401 is further configured to perform an addition calculation on the attribute residual value and the attribute prediction value to obtain the attribute reconstruction value corresponding to the current node.

In some embodiments, the second prediction unit 1403 is also configured to determine that the initial reference set is an empty set if the index number is equal to 0, and directly determine the preset attribute value as the attribute prediction value corresponding to the current node; if the index number is not If equal to 0, it is determined that the initial reference set is a non-empty set, at least one prediction node is determined from the initial reference set, and the attribute prediction value corresponding to the current node is determined based on at least one prediction node.

In some embodiments, the second determination unit 1401 is further configured to determine a reference node included in the initial reference set as at least one prediction node if the index number is equal to 1; if the index number is equal to 2, then determine the initial reference node The two reference nodes included in are determined to be at least one prediction node; if the index number is greater than or equal to 3, a preset number of reference nodes with a relatively small distance value from the current node are obtained from the initial reference set, and the prediction nodes are A number of reference nodes are determined as at least one prediction node.

In some embodiments, referring to FIG. 14 , the decoder 140 may further include a second search unit 1404 configured to obtain a relatively small preset number of distance values from the current node using a global search method from the initial reference set. reference nodes; or, from the initial reference set, use the spatial relationship search method to obtain a preset number of reference nodes with a relatively small distance value from the current node; or, from the initial reference set, use the spatial relationship depth first The search method obtains a preset number of reference nodes that have a relatively small distance value from the current node.

In some embodiments, the second search unit 1404 is also configured to calculate the distance value between each reference node in the initial reference set and the current node, and select a predetermined distance value with a relatively small distance value from the obtained N distance values. Set a number of distance values; and determine a preset number of reference nodes based on the preset number of distance values.

In some embodiments, the second search unit 1404 is also configured to search for reference nodes that meet preset conditions from the initial reference set based on the spatial relationship between nodes, and obtain M reference nodes; and calculate M reference nodes. The distance value between each reference node in the node and the current node, select K distance values with relatively small distance values from the obtained M distance values, and determine K reference nodes based on the K distance values; and if K is equal to the preset number, then the K reference nodes will be used as the preset number of reference nodes; among them, the reference nodes that meet the preset conditions include at least: child nodes in the upper block of the current node, and those in the upper block of the current node. The child nodes in the neighbor block of the face, the child nodes in the neighbor block that are collinear with the upper block of the current node, and the child nodes in the neighbor block that are in common with the upper block of the current node.

In some embodiments, the second search unit 1404 is also configured to use a global search method to calculate the distance value between the reference node in the initial reference set and the current node if K is less than the preset number, and calculate the distance value based on the distance value. The comparison result with the K distance values determines a preset number of distance values with relatively small distance values, and determines a preset number of reference nodes based on the preset number of distance values.

In some embodiments, the second search unit 1404 is also configured to search the child nodes in the upper block of the current node from the initial reference set to obtain K1 reference nodes based on the spatial relationship between nodes. ; and calculate the distance value between each of the K1 reference nodes and the current node, select K2 distance values with relatively small distance values from the obtained K1 distance values, and according to the K2 distance values determine the K2 reference nodes; if the K2 is equal to the preset number, then the K2 reference nodes are used as the preset number of reference nodes; if the K2 is less than the preset number number, then continue to search from the initial reference set for child nodes in the neighbor blocks that are coplanar with the upper block of the current node, and obtain K3 reference nodes; and calculate the relationship between each reference node and the K3 reference nodes. The distance values between the current nodes, and K4 distance values with relatively small distance values are determined based on the comparison results of the obtained K3 distance values and the K2 distance values, and K4 is determined based on the K4 distance values reference nodes; if K4 is equal to the preset number, then use the K4 reference nodes as the preset number of reference nodes; if K4 is less than the preset number, continue from the initial Search the reference set for child nodes in neighbor blocks that are collinear with the upper block of the current node to obtain K5 reference nodes; and calculate the distance between each of the K5 reference nodes and the current node. value, and determine K6 distance values with relatively small distance values based on the comparison results of the obtained K5 distance values and the K4 distance values, and determine K6 reference nodes based on the K6 distance values; if the K6 is equal to the preset number, then the K6 reference nodes are used as the preset number of reference nodes; if the K6 is less than the preset number, continue to search for the current reference node from the initial reference set. Obtain K7 reference nodes from the child nodes in the neighbor blocks that share the same point with the node's upper block; and calculate the distance value between each of the K7 reference nodes and the current node, and calculate the distance value based on the obtained K7 The comparison result between the distance values and the K6 distance values determines K8 distance values with relatively small distance values, and determines K8 reference nodes based on the K8 distance values; if the K8 is equal to the preset number, then Use the K8 reference nodes as the preset number of reference nodes; if the K8 is less than the preset number, use a global search method to calculate the distance between the reference nodes in the initial reference set and the current node. value, and determine a preset number of distance values with relatively small distance values based on the comparison result between the distance value and the K8 distance values, and determine the preset number of reference nodes based on the preset number of distance values. .

In some embodiments, the upper-level block of the current node includes at least one of the following: the parent block of the current node, or the grandfather block of the current node.

In some embodiments, the second determination unit 1401 is further configured to determine from the initial reference set the target reference node that is opposite to the parity characteristics of the index sequence number and is placed earliest in the initial reference set, and determines the position corresponding to the target reference node as target location.

In some embodiments, the second determination unit 1401 is further configured to determine a set of earliest placed candidate reference nodes in the initial reference set according to a preset step size; and determine the parity with the index sequence number from a set of candidate reference nodes. For target reference nodes with opposite characteristics, the position corresponding to the target reference node is determined as the target position.

In some embodiments, the second determination unit 1401 is also configured to determine the tail position of the initial reference set as the corresponding target position of the current node in the initial reference set when the index number is greater than or equal to the preset constant value. ;

The decoding unit 1402 is also configured to, after decoding the current node according to the initial reference set, delete the reference node at the head position in the initial reference set, and place the current node at the target position to obtain the target reference set.

In some embodiments, the initial reference set includes a first initial reference set and a second initial reference set; accordingly, the decoding unit 1402 is further configured to obtain the first target after decoding the current node according to the first initial reference set. Reference set; wherein, the first target reference set is obtained by replacing the reference node at the target position in the first initial reference set based on the current node; and/or, after decoding the current node according to the second initial reference set, the third target reference set is obtained. Two target reference sets; wherein, the second target reference set is obtained based on deleting the reference node at the target position in the second initial reference set and placing the current node at the end of the queue.

In some embodiments, the decoding unit 1402 is also configured to decode the current node according to the second initial reference set if the current node uses the spatial relationship search method or the spatial relationship depth first search method; if the current node uses the global search method , then the current node is decoded according to the first initial reference set.

In some embodiments, the second determination unit 1401 is also configured to, after decoding the current node according to the first initial reference set and/or the second initial reference set, if the current node uses the spatial relationship search method or spatial relationship depth If the priority search mode is used, the first target reference set and the second target reference set are determined to be maintained based on deleting the reference node at the head position of the team and placing the current node at the tail position of the team; if the current node uses the global search mode, then Determining the first target reference set is maintained based on the current node replacing the reference node at the target position, and the second target reference set is maintained based on deleting the reference node at the target position and placing the current node at the end of the queue.

It can be understood that in this embodiment, the "unit" may be part of a circuit, part of a processor, part of a program or software, etc., and of course may also be a module, or may be non-modular. Moreover, each component in this embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or software function modules.

If the integrated unit is implemented in the form of a software function module and is not sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, this embodiment provides a computer-readable storage medium for use in the decoder 140. The computer-readable storage medium stores a computer program. When the computer program is executed by the second processor, the foregoing embodiments are implemented. any one of the methods.

Based on the above composition of the decoder 140 and the computer-readable storage medium, see FIG. 15 , which shows a schematic diagram of the specific hardware structure of the decoder 140 provided by the embodiment of the present application. As shown in Figure 15, the decoder 140 may include: a second communication interface 1501, a second memory 1502, and a second processor 1503; the various components are coupled together through a second bus system 1504. It can be understood that the second bus system 1504 is used to implement connection communication between these components. In addition to the data bus, the second bus system 1504 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity of explanation, various buses are labeled as second bus system 1504 in FIG. 15 . in,

The second communication interface 1501 is used for receiving and sending signals during the process of sending and receiving information with other external network elements;

The second memory 1502 is used to store a computer program capable of running on the second processor 1503;

The second processor 1503 is used to execute: when running the computer program:

Determine the index number corresponding to the current node and the initial reference set;

Based on the parity characteristics of the index sequence number, determine the target position corresponding to the current node in the initial reference set;

After decoding the current node according to the initial reference set, the current node is placed at the target position to obtain the target reference set.

Optionally, as another embodiment, the second processor 1503 is also configured to perform the method described in any one of the preceding embodiments when running the computer program.

It can be understood that the hardware functions of the second memory 1502 and the first memory 1302 are similar, and the hardware functions of the second processor 1503 and the first processor 1303 are similar; details will not be described here.

This embodiment provides a decoder. In the decoder, a target reference set is constructed based on the parity characteristics of the index sequence number, and then the target reference set is used to predict point cloud attributes, which can improve the prediction accuracy of point cloud attributes. And improve the encoding and decoding performance of point cloud attributes.

It should be noted that in this application, the terms "comprising", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device that includes a series of elements not only includes those elements , but also includes other elements not expressly listed or inherent in such process, method, article or apparatus. Without further limitation, an element defined by the statement "comprises a..." does not exclude the presence of additional identical elements in a process, method, article or apparatus that includes that element.

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

The methods disclosed in several method embodiments provided in this application can be combined arbitrarily to obtain new method embodiments without conflict.

The features disclosed in several product embodiments provided in this application can be combined arbitrarily without conflict to obtain new product embodiments.

The features disclosed in several method or device embodiments provided in this application can be combined arbitrarily without conflict to obtain new method embodiments or device embodiments.

The above are only specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application. should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Industrial applicability

In the embodiment of this application, at the encoding end or decoding end, the index sequence number corresponding to the current node and the initial reference set are determined; based on the parity characteristics of the index sequence number, the target position corresponding to the current node in the initial reference set is determined; according to the initial reference set pair After the current node is encoded/decoded, the current node is placed at the target position to obtain the target reference set. In this way, a target reference set including the current node is constructed based on the parity characteristics of the index sequence number, and the target reference set is used to predict point cloud attributes, which can improve the prediction accuracy of point cloud attributes and improve the encoding and decoding performance of point cloud attributes. .

Claims (46)

1. A decoding method, applied to a decoder, the method includes:

   Determine the index number corresponding to the current node and the initial reference set;

   Based on the parity characteristics of the index sequence number, determine the target position corresponding to the current node in the initial reference set;

   After decoding the current node according to the initial reference set, the current node is placed at the target position to obtain a target reference set.
2. The method according to claim 1, wherein, after decoding the current node according to the initial reference set, placing the current node at the target location includes:

   If the index number is greater than or equal to 0 and less than a preset constant value, directly place the current node at the target position in the initial reference set;

   When the index number is greater than or equal to a preset constant value, the reference node at the target position is replaced with the current node.
3. The method according to claim 2, wherein the preset constant value represents that the initial reference set includes a maximum number of reference nodes, and the target reference set represents the next node in the preset decoding order. The initial reference set corresponding to a node.
4. The method according to claim 2, wherein the initial reference set is composed of N decoded reference nodes; the method further includes:

   If the index number is greater than or equal to 0 and less than the preset constant value, then it is determined that the value of N is equal to the index number;

   If the index number is greater than or equal to the preset constant value, then it is determined that the value of N is equal to the preset constant value.
5. The method according to claim 4, wherein said decoding the current node according to the initial reference set includes:

   Parse the code stream and determine the attribute residual value corresponding to the current node;

   According to the initial reference set, determine the attribute prediction value corresponding to the current node;

   According to the attribute residual value and the attribute prediction value, the attribute reconstruction value corresponding to the current node is determined.
6. The method according to claim 5, wherein determining the attribute reconstruction value corresponding to the current node according to the attribute residual value and the attribute prediction value includes:

   The attribute residual value and the attribute prediction value are added together to obtain the attribute reconstruction value corresponding to the current node.
7. The method according to claim 5, wherein determining the attribute prediction value corresponding to the current node according to the initial reference set includes:

   If the index number is equal to 0, it is determined that the initial reference set is an empty set, and the preset attribute value is directly determined as the attribute prediction value corresponding to the current node;

   If the index number is not equal to 0, determine that the initial reference set is a non-empty set, determine at least one prediction node from the initial reference set, and determine the attribute prediction corresponding to the current node based on the at least one prediction node. value.
8. The method according to claim 7, wherein when the index sequence number is not equal to 0, determining at least one prediction node from the initial reference set includes:

   If the index number is equal to 1, determine one reference node included in the initial reference set as the at least one prediction node;

   If the index number is equal to 2, determine the two reference nodes included in the initial reference set as the at least one prediction node;

   If the index number is greater than or equal to 3, obtain a preset number of reference nodes with a relatively small distance value from the current node from the initial reference set, and determine the preset number of reference nodes. is the at least one prediction node.
9. The method according to claim 8, wherein said obtaining a preset number of reference nodes with a relatively small distance value from the current node from the initial reference set includes:

   From the initial reference set, use a global search method to obtain a preset number of reference nodes with a relatively small distance value from the current node; or,

   From the initial reference set, use a spatial relationship search method to obtain a preset number of reference nodes with a relatively small distance value from the current node; or,

   From the initial reference set, a preset number of reference nodes with a relatively small distance value from the current node is obtained using a spatial relationship depth-first search method.
10. The method according to claim 9, wherein said using a global search method to obtain a preset number of reference nodes with a relatively small distance value from the current node includes:

    Calculate the distance value between each reference node in the initial reference set and the current node, and select a preset number of distance values with relatively small distance values from the obtained N distance values;

    The preset number of reference nodes are determined according to the preset number of distance values.
11. The method according to claim 9, wherein the using a spatial relationship search method to obtain a preset number of reference nodes with a relatively small distance value from the current node includes:

    Based on the spatial relationship between nodes, search for reference nodes that meet preset conditions from the initial reference set to obtain M reference nodes;

    Calculate the distance value between each of the M reference nodes and the current node, select K distance values with relatively small distance values from the obtained M distance values, and use the K The distance value determines K reference nodes;

    If the K is equal to the preset number, then use the K reference nodes as the preset number of reference nodes;

    Wherein, the reference node that meets the preset conditions at least includes: child nodes in the upper block of the current node, child nodes in the neighbor block coplanar with the upper block of the current node, and child nodes in the upper block of the current node. The child nodes within the neighbor blocks that are collinear with the upper layer block and the child nodes within the neighbor blocks that are co-pointed with the upper layer block of the current node.
12. The method of claim 11, wherein the method further includes:

    If the K is less than the preset number, the global search method is used to calculate the distance value between the reference node in the initial reference set and the current node, and the distance value is compared with the K distance values. As a result, a preset number of distance values with relatively small distance values are determined, and the preset number of reference nodes are determined according to the preset number of distance values.
13. The method according to claim 9, wherein the using a spatial relationship depth-first search method to obtain a preset number of reference nodes with a relatively small distance value from the current node includes:

    Based on the spatial relationship between nodes, search the child nodes in the upper block of the current node from the initial reference set to obtain K1 reference nodes;

    Calculate the distance value between each of the K1 reference nodes and the current node, select K2 distance values with relatively small distance values from the obtained K1 distance values, and use the K2 The distance value determines the K2 reference nodes;

    If the K2 is equal to the preset number, then the K2 reference nodes are used as the preset number of reference nodes;

    If K2 is less than the preset number, continue to search from the initial reference set for child nodes in neighbor blocks that are coplanar with the upper block of the current node, and obtain K3 reference nodes;

    Calculate the distance value between each of the K3 reference nodes and the current node, and determine K4 with a relatively small distance value based on the comparison result of the K3 distance values and the K2 distance values. distance values, and K4 reference nodes are determined based on the K4 distance values;

    If the K4 is equal to the preset number, then the K4 reference nodes are used as the preset number of reference nodes;

    If K4 is less than the preset number, continue to search from the initial reference set for child nodes in neighbor blocks that are collinear with the upper block of the current node, and obtain K5 reference nodes;

    Calculate the distance value between each of the K5 reference nodes and the current node, and determine K6 with a relatively small distance value based on the comparison result of the K5 distance values and the K4 distance values. distance values, and K6 reference nodes are determined based on the K6 distance values;

    If the K6 is equal to the preset number, then the K6 reference nodes are used as the preset number of reference nodes;

    If the K6 is less than the preset number, then continue to search from the initial reference set for child nodes in the neighbor blocks that have the same point as the upper block of the current node, and obtain K7 reference nodes;

    Calculate the distance value between each of the K7 reference nodes and the current node, and determine K8 with a relatively small distance value based on the comparison result of the K7 distance values and the K6 distance values. distance values, and K8 reference nodes are determined based on the K8 distance values;

    If the K8 is equal to the preset number, then the K8 reference nodes are used as the preset number of reference nodes;

    If the K8 is less than the preset number, the global search method is used to calculate the distance value between the reference node in the initial reference set and the current node, and the distance value is compared with the K8 distance values. As a result, a preset number of distance values with relatively small distance values are determined, and the preset number of reference nodes are determined according to the preset number of distance values.
14. The method according to any one of claims 11 to 13, wherein the upper-layer block of the current node includes at least one of the following: a parent block of the current node and a grandfather block of the current node.
15. The method according to claim 1, wherein determining the target position corresponding to the current node in the initial reference set based on the parity characteristics of the index sequence number includes:

    The target reference node that is opposite to the parity characteristics of the index number and is placed earliest in the initial reference set is determined from the initial reference set, and the position corresponding to the target reference node is determined as the target position.
16. The method according to claim 1, wherein determining the target position corresponding to the current node in the initial reference set based on the parity characteristics of the index sequence number includes:

    In the initial reference set, determine a set of earliest placed candidate reference nodes according to a preset step size;

    A target reference node with an opposite parity characteristic of the index sequence number is determined from the group of candidate reference nodes, and a position corresponding to the target reference node is determined as the target position.
17. The method of claim 1, further comprising:

    When the index number is greater than or equal to a preset constant value, determine the tail position of the initial reference set as the target position corresponding to the current node in the initial reference set;

    After the current node is decoded according to the initial reference set, the reference node at the head position in the initial reference set is deleted, and the current node is placed at the target position to obtain the target reference set.
18. The method of claim 1, wherein the initial reference set includes a first initial reference set and a second initial reference set; the method further includes:

    After decoding the current node according to the first initial reference set, a first target reference set is obtained; wherein the first target reference set is based on the current node replacing all the nodes in the first initial reference set. obtained from the reference node at the target position; and/or

    After decoding the current node according to the second initial reference set, a second target reference set is obtained; wherein the second target reference set is based on deleting the target location in the second initial reference set. The reference node is obtained by placing the current node at the end of the queue.
19. The method of claim 18, wherein the method further includes:

    If the current node uses the spatial relationship search method or the spatial relationship depth-first search method, then decode the current node according to the second initial reference set;

    If the current node uses the global search method, the current node is decoded according to the first initial reference set.
20. The method of claim 18, wherein the method further includes:

    If the current node uses the spatial relationship search method or the spatial relationship depth-first search method, determining the first target reference set and the second target reference set is based on deleting the reference node at the head position of the team and adding the The way the current node is placed at the end of the queue is maintained;

    If the current node uses the global search method, it is determined that the first target reference set is maintained based on the current node replacing the reference node at the target position, and the second target reference set is determined based on deleting the The reference node at the target position is maintained by placing the current node at the end of the queue.
21. An encoding method, applied to an encoder, the method includes:

    Determine the index number corresponding to the current node and the initial reference set;

    Based on the parity characteristics of the index sequence number, determine the target position corresponding to the current node in the initial reference set;

    After encoding the current node according to the initial reference set, the current node is placed at the target position to obtain a target reference set.
22. The method of claim 21, wherein, after encoding the current node according to the initial reference set, placing the current node at the target location includes:

    If the index number is greater than or equal to 0 and less than a preset constant value, directly place the current node at the target position in the initial reference set;

    When the index number is greater than or equal to a preset constant value, the reference node at the target position is replaced with the current node.
23. The method according to claim 22, wherein the preset constant value represents that the initial reference set includes a maximum number of reference nodes, and the target reference set represents the next node in the preset coding order. The initial reference set corresponding to a node.
24. The method of claim 22, wherein the initial reference set is composed of N coded reference nodes; the method further includes:

    If the index number is greater than or equal to 0 and less than the preset constant value, then it is determined that the value of N is equal to the index number;

    If the index number is greater than or equal to the preset constant value, then it is determined that the value of N is equal to the preset constant value.
25. The method of claim 24, wherein encoding the current node according to the initial reference set includes:

    Obtain the original value of the attribute corresponding to the current node;

    According to the initial reference set, determine the attribute prediction value corresponding to the current node;

    Determine the attribute residual value corresponding to the current node according to the attribute original value and the attribute predicted value;

    The attribute residual value is encoded, and the obtained encoded bits are written into the code stream.
26. The method according to claim 25, wherein determining the attribute residual value corresponding to the current node based on the original attribute value and the attribute predicted value includes:

    Subtraction calculation is performed on the original attribute value and the predicted attribute value to obtain the attribute residual value corresponding to the current node.
27. The method according to claim 25, wherein determining the attribute prediction value corresponding to the current node according to the initial reference set includes:

    If the index number is equal to 0, it is determined that the initial reference set is an empty set, and the preset attribute value is directly determined as the attribute prediction value corresponding to the current node;

    If the index number is not equal to 0, determine that the initial reference set is a non-empty set, determine at least one prediction node from the initial reference set, and determine the attribute prediction corresponding to the current node based on the at least one prediction node. value.
28. The method according to claim 27, wherein when the index sequence number is not equal to 0, determining at least one prediction node from the initial reference set includes:

    If the index number is equal to 1, determine one reference node included in the initial reference set as the at least one prediction node;

    If the index number is equal to 2, determine the two reference nodes included in the initial reference set as the at least one prediction node;

    If the index number is greater than or equal to 3, obtain a preset number of reference nodes with a relatively small distance value from the current node from the initial reference set, and determine the preset number of reference nodes. is the at least one prediction node.
29. The method according to claim 28, wherein said obtaining a preset number of reference nodes with a relatively small distance value from the current node from the initial reference set includes:

    From the initial reference set, use a global search method to obtain a preset number of reference nodes with a relatively small distance value from the current node; or,

    From the initial reference set, use a spatial relationship search method to obtain a preset number of reference nodes with a relatively small distance value from the current node; or,

    From the initial reference set, a preset number of reference nodes with a relatively small distance value from the current node is obtained using a spatial relationship depth-first search method.
30. The method according to claim 29, wherein said using a global search method to obtain a preset number of reference nodes with a relatively small distance value from the current node includes:

    Calculate the distance value between each reference node in the initial reference set and the current node, and select a preset number of distance values with relatively small distance values from the obtained N distance values;

    The preset number of reference nodes are determined according to the preset number of distance values.
31. The method according to claim 29, wherein the using a spatial relationship search method to obtain a preset number of reference nodes with a relatively small distance value from the current node includes:

    Based on the spatial relationship between nodes, search for reference nodes that meet preset conditions from the initial reference set to obtain M reference nodes;

    Calculate the distance value between each of the M reference nodes and the current node, select K distance values with relatively small distance values from the obtained M distance values, and use the K The distance value determines K reference nodes;

    If the K is equal to the preset number, then use the K reference nodes as the preset number of reference nodes;

    Wherein, the reference node that meets the preset conditions at least includes: child nodes in the upper block of the current node, child nodes in the neighbor block coplanar with the upper block of the current node, and child nodes in the upper block of the current node. The child nodes within the neighbor blocks that are collinear with the upper layer block and the child nodes within the neighbor blocks that are co-pointed with the upper layer block of the current node.
32. The method of claim 31, wherein the method further includes:

    If the K is less than the preset number, the global search method is used to calculate the distance value between the reference node in the initial reference set and the current node, and the distance value is compared with the K distance values. As a result, a preset number of distance values with relatively small distance values are determined, and the preset number of reference nodes are determined according to the preset number of distance values.
33. The method according to claim 29, wherein the using a spatial relationship depth-first search method to obtain a preset number of reference nodes with a relatively small distance value from the current node includes:

    Based on the spatial relationship between nodes, search the child nodes in the upper block of the current node from the initial reference set to obtain K1 reference nodes;

    Calculate the distance value between each of the K1 reference nodes and the current node, select K2 distance values with relatively small distance values from the obtained K1 distance values, and use the K2 The distance value determines the K2 reference nodes;

    If the K2 is equal to the preset number, then the K2 reference nodes are used as the preset number of reference nodes;

    If K2 is less than the preset number, continue to search from the initial reference set for child nodes in neighbor blocks that are coplanar with the upper block of the current node, and obtain K3 reference nodes;

    Calculate the distance value between each of the K3 reference nodes and the current node, and determine K4 with a relatively small distance value based on the comparison result of the K3 distance values and the K2 distance values. distance values, and K4 reference nodes are determined based on the K4 distance values;

    If the K4 is equal to the preset number, then the K4 reference nodes are used as the preset number of reference nodes;

    If K4 is less than the preset number, continue to search from the initial reference set for child nodes in neighbor blocks that are collinear with the upper block of the current node, and obtain K5 reference nodes;

    Calculate the distance value between each of the K5 reference nodes and the current node, and determine K6 with a relatively small distance value based on the comparison result of the K5 distance values and the K4 distance values. distance values, and K6 reference nodes are determined based on the K6 distance values;

    If the K6 is equal to the preset number, then the K6 reference nodes are used as the preset number of reference nodes;

    If the K6 is less than the preset number, then continue to search from the initial reference set for child nodes in the neighbor blocks that have the same point as the upper block of the current node, and obtain K7 reference nodes;

    Calculate the distance value between each of the K7 reference nodes and the current node, and determine K8 with a relatively small distance value based on the comparison result of the K7 distance values and the K6 distance values. distance values, and K8 reference nodes are determined based on the K8 distance values;

    If the K8 is equal to the preset number, then the K8 reference nodes are used as the preset number of reference nodes;

    If the K8 is less than the preset number, the global search method is used to calculate the distance value between the reference node in the initial reference set and the current node, and the distance value is compared with the K8 distance values. As a result, a preset number of distance values with relatively small distance values are determined, and the preset number of reference nodes are determined according to the preset number of distance values.
34. The method according to any one of claims 31 to 33, wherein the upper-layer block of the current node includes at least one of the following: a parent block of the current node and a grandparent block of the current node.
35. The method according to claim 21, wherein determining the target position corresponding to the current node in the initial reference set based on the parity characteristics of the index sequence number includes:

    The target reference node that is opposite to the parity characteristics of the index number and is placed earliest in the initial reference set is determined from the initial reference set, and the position corresponding to the target reference node is determined as the target position.
36. The method according to claim 21, wherein determining the target position corresponding to the current node in the initial reference set based on the parity characteristics of the index sequence number includes:

    In the initial reference set, determine a set of earliest placed candidate reference nodes according to a preset step size;

    A target reference node with an opposite parity characteristic of the index sequence number is determined from the group of candidate reference nodes, and a position corresponding to the target reference node is determined as the target position.
37. The method of claim 21, wherein the method further includes:

    When the index number is greater than or equal to a preset constant value, determine the tail position of the initial reference set as the target position corresponding to the current node in the initial reference set;

    After encoding the current node according to the initial reference set, delete the reference node at the head position in the initial reference set, and place the current node at the target position to obtain the target reference set.
38. The method of claim 21, wherein the initial reference set includes a first initial reference set and a second initial reference set; the method further includes:

    After encoding the current node according to the first initial reference set, a first target reference set is obtained; wherein the first target reference set is based on the current node replacing all the nodes in the first initial reference set. obtained from the reference node at the target position; and/or

    After encoding the current node according to the second initial reference set, a second target reference set is obtained; wherein the second target reference set is based on deleting the target location in the second initial reference set. The reference node is obtained by placing the current node at the end of the queue.
39. The method of claim 38, wherein the method further includes:

    If the current node uses the spatial relationship search method or the spatial relationship depth-first search method, the current node is encoded according to the second initial reference set;

    If the current node uses the global search method, the current node is encoded according to the first initial reference set.
40. The method according to claim 38, wherein, after encoding the current node according to the first initial reference set and/or the second initial reference set, the method further includes:

    If the current node uses the spatial relationship search method or the spatial relationship depth-first search method, determining the first target reference set and the second target reference set is based on deleting the reference node at the head position of the team and adding the The way the current node is placed at the end of the queue is maintained;

    If the current node uses the global search method, it is determined that the first target reference set is maintained based on the current node replacing the reference node at the target position, and the second target reference set is determined based on deleting the The reference node at the target position is maintained by placing the current node at the end of the queue.
41. A code stream is generated by bit encoding based on information to be encoded; wherein the information to be encoded at least includes: an attribute residual value corresponding to the current node.
42. An encoder, the encoder includes a first determination unit and a coding unit; wherein,

    The first determination unit is configured to determine the index sequence number corresponding to the current node and the initial reference set; and based on the parity characteristics of the index sequence number, determine the target position corresponding to the current node in the initial reference set;

    The encoding unit is configured to, after encoding the current node according to the initial reference set, place the current node at the target position to obtain a target reference set.
43. An encoder, the encoder includes a first memory and a first processor; wherein,

    The first memory is used to store a computer program capable of running on the first processor;

    The first processor is configured to execute the method according to any one of claims 21 to 40 when running the computer program.
44. A decoder, the decoder includes a second determination unit and a decoding unit; wherein,

    The second determination unit is configured to determine the index sequence number corresponding to the current node and the initial reference set; and based on the parity characteristics of the index sequence number, determine the target position corresponding to the current node in the initial reference set;

    The decoding unit is configured to, after decoding the current node according to the initial reference set, place the current node at the target position to obtain a target reference set.
45. A decoder, the decoder includes a second memory and a second processor; wherein,

    The second memory is used to store a computer program capable of running on the second processor;

    The second processor is configured to perform the method according to any one of claims 1 to 20 when running the computer program.
46. A computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program is executed, the method according to any one of claims 1 to 20 is implemented, or the method according to claim 21 is implemented. The method described in any one of to 40.

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