WO2023123284A1

WO2023123284A1 - Decoding method, encoding method, decoder, encoder, and storage medium

Info

Publication number: WO2023123284A1
Application number: PCT/CN2021/143372
Authority: WO
Inventors: 魏红莲
Original assignee: Oppo广东移动通信有限公司
Priority date: 2021-12-30
Filing date: 2021-12-30
Publication date: 2023-07-06

Abstract

An embodiment of the application provides a decoding method, an encoding method, a decoder, an encoder, and a storage medium. By means of parsing a stream of data, determine an attribute residual error value of a color component corresponding to a current point; acquire an attribute prediction value of a color component corresponding to a current point; determine a prediction model of a color component of a current point; wherein, the prediction model is determined on the basis of a degree of difference between color components; decoding and reconstructing the color component of the current point on the basis of the prediction model, the attribute residual error value, the attribute prediction value and the initial cross-component attribute residual error prediction value, obtaining an attribute reconstruction value of the color component.

Description

Decoding method, encoding method, decoder, encoder and storage medium

technical field

The embodiment of the present application relates to a video encoding technology, and relates to but not limited to a decoding method, an encoding method, a decoder, an encoder, and a storage medium.

Background technique

In the Audio Video Standard-Point Cloud Compression (AVSAVS-PCC) encoding and decoding framework provided by the audio and video encoding standard, the geometric information of the point cloud and the attribute information corresponding to each point cloud are encoded separately. After the geometric encoding is completed, the geometric information is reconstructed, and the encoding of the attribute information will depend on the reconstructed geometric information. Among them, attribute information coding is mainly aimed at the coding of color information (that is, color components), so as to transform color information from the spatial domain to the frequency domain, and convert it into Luminance-Chrominance (YUV) that is more in line with the visual characteristics of the human eye. color space, and then perform attribute encoding on the preprocessed attribute information to obtain a quantized residual value, and input the quantized residual value into the attribute entropy encoder to form a binary attribute code stream.

At present, during the attribute encoding process, the point cloud compression reference platform (Point Cloud Reference Model, PCRM) conducts secondary prediction of attribute residual values based on cross-component attribute residuals, and further eliminates the correlation between the three color components. redundancy. Among them, the secondary prediction algorithm of the residual value of the attribute uses the R component to predict the G component, and uses the sum of the R component and the G component to predict the B component. However, due to the different wavelengths among the three color components, this prediction method is not accurate.

Contents of the invention

Embodiments of the present application provide a decoding method, an encoding method, a decoder, an encoder, and a storage medium, which can improve the accuracy of encoding and decoding during attribute encoding.

In the first aspect, the embodiment of the present application provides a decoding method, which is applied to a decoder, and the method includes:

Analyze the code stream to determine the attribute residual value of the color component corresponding to the current point;

Acquiring the attribute prediction value of the color component corresponding to the current point;

Determine the prediction mode of the color component of the current point; wherein, the prediction mode is determined based on the degree of difference between the color components;

Based on the prediction mode, the attribute residual value, the attribute prediction value and the initial cross-component attribute residual prediction value, decode and reconstruct the color component of the current point to obtain the attribute reconstruction value of the color component.

In the second aspect, the embodiment of the present application also provides an encoding method, which is applied to an encoder, and the method includes:

Get the attribute prediction value of the color component corresponding to the current point in the point cloud;

Based on the attribute prediction value, determine a standard value of the color component corresponding to the current point;

determining at least two degrees of difference between at least two color components corresponding to the current point and the standard value;

determining a prediction mode for the color component based on the at least two degrees of difference;

Based on the prediction mode, the attribute prediction value and the initial cross-component attribute residual prediction value, the color component of the current point is predicted twice to obtain the attribute residual value of the color component.

In a third aspect, the embodiment of the present application provides a decoder, including:

The parsing part is configured to parse the code stream and determine the attribute residual value of the color component corresponding to the current point;

The first acquisition part is configured to acquire the attribute prediction value of the color component corresponding to the current point;

The first determining part is configured to determine a prediction mode of the color component of the current point; wherein the prediction mode is determined based on the degree of difference between the color components;

The decoding part is configured to decode and reconstruct the color component of the current point based on the prediction mode, the attribute residual value, the attribute prediction value and the initial cross-component attribute residual prediction value, to obtain the color component Property reconstruction value.

In a fourth aspect, the embodiment of the present application provides an encoder, including:

The second acquisition part is configured to acquire the attribute prediction value of the color component corresponding to the current point in the point cloud;

The second determination part is configured to determine a standard value of the color component corresponding to the current point based on the attribute prediction value; determine at least two color components corresponding to the current point, and at least the standard value two degrees of difference; based on the at least two degrees of difference, determining a prediction mode of the color component;

The prediction part is configured to perform secondary prediction on the color component of the current point based on the prediction mode, the attribute prediction value and the initial cross-component attribute residual prediction value, to obtain the attribute residual value of the color component.

In the fifth aspect, the embodiment of the present application also provides a decoder, including:

a first memory and a first processor;

The first memory stores a computer program that can run on the first processor, and the first processor implements the decoding method of the decoder when executing the program.

In a sixth aspect, the embodiment of the present application also provides an encoder, including:

a second memory and a second processor;

The second memory stores a computer program that can run on the second processor, and the second processor executes the program and the encoding method of the encoder.

The embodiment of the present application provides a storage medium on which a computer program is stored, and when the computer program is executed by the first processor, the decoding method of the claim decoder is realized; or, the computer program is executed by the second processor When executed, the encoding method of the claim encoder is realized.

The embodiment of the present application provides a decoding method, an encoding method, a decoder, an encoder, and a storage medium. By analyzing the code stream, determine the attribute residual value of the color component corresponding to the current point; obtain the attribute of the color component corresponding to the current point Prediction value; determine the prediction mode of the color component of the current point; where the prediction mode is determined based on the degree of difference between the color components; based on the prediction mode, attribute residual value, attribute prediction value and initial cross-component attribute residual prediction Value, decode and reconstruct the color component of the current point to obtain the attribute reconstruction value of the color component. Since the adaptive selection of the prediction mode can be performed based on the degree of difference between the color components, when the decoding and reconstruction of the color component of the current point is performed according to the prediction mode, the accuracy of the attribute reconstruction value of the obtained color component higher.

Description of drawings

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

FIG. 1B is a partially enlarged view of an exemplary three-dimensional point cloud image provided by an embodiment of the present application;

Figure 2A-Figure 2F is an exemplary point cloud image at different angles provided by the embodiment of the present application;

Fig. 2G is an exemplary illustration of the data storage format corresponding to Fig. 2A-Fig. 2F provided by the embodiment of the present application;

FIG. 3 is a schematic diagram of the composition and structure of an exemplary video codec network architecture provided by an embodiment of the present application;

FIG. 4 is a structural diagram of an exemplary video coding system provided by an embodiment of the present application;

FIG. 5 is a structural diagram of an exemplary video decoding system provided by an embodiment of the present application;

Fig. 6A is an exemplary bounding box illustration provided by the embodiment of the present application;

6B-6G are exemplary schematic diagrams of iterative octree division of bounding boxes provided by the embodiment of the present application;

FIG. 7A is a schematic diagram 1 of an exemplary encoding sequence of Morton codes in two-dimensional space provided by the embodiment of the present application;

FIG. 7B is a second schematic diagram of the coding sequence of an exemplary Morton code in a two-dimensional space provided by the embodiment of the present application;

FIG. 7C is a schematic diagram 3 of an exemplary Morton code encoding sequence in two-dimensional space provided by the embodiment of the present application;

FIG. 8 is a schematic diagram of an exemplary Morton code encoding sequence in three-dimensional space provided by an embodiment of the present application;

FIG. 9 is a schematic diagram of wavelengths of exemplary different color components provided by the embodiment of the present application;

FIG. 10 is a flow chart of a decoding method further provided in the embodiment of the present application;

FIG. 11 is a flow chart of an encoding method further provided in the embodiment of the present application;

FIG. 12 is a first schematic structural diagram of a decoder provided by an embodiment of the present application;

FIG. 13 is a second schematic structural diagram of a decoder provided in an embodiment of the present application;

FIG. 14 is a first schematic structural diagram of an encoder provided by an embodiment of the present application;

FIG. 15 is a second structural schematic diagram of an encoder provided by an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the specific embodiments described here are only used to explain the related application, not to limit the application. It should also be noted that, for the convenience of description, only the parts related to the relevant application are shown in the drawings.

Before the embodiment of the present application is described in further detail, the terms and terms involved in the embodiments of the present application are described, and the terms and terms involved in the embodiments of the present application are applicable to the following explanations: point cloud compression (Point Cloud Compression, PCC), Geometry-based Point Cloud Compression (G-PCC), video-based point cloud compression (Video Point Cloud Compression, V-PCC), level of detail (Level of Detail, LOD), area adaptive analysis Region Adaptive Hierarchal Transform (RAHT), slice, bounding box, octree, triangle soup, trisoup, block, vertex , Root Node (RootNode), Moving Picture Experts Group (MPEG), International Standardization Organization (International Standardization Organization, ISO), International Electrotechnical Commission (International Electrotechnical Commission, IEC), audio and video coding standard (AVS).

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

A point cloud is a set of discrete point sets randomly distributed in space that express the spatial structure and surface properties of a 3D object or scene. Figure 1A shows a 3D point cloud image and Figure 1B shows a partial enlarged view of a 3D point cloud image. It can be seen that the point cloud surface is composed of densely distributed points.

The two-dimensional image has information expression at each pixel, and the distribution is regular, so there is no need to additionally record its position information; however, the distribution of points in the point cloud in three-dimensional space is random and irregular, so it is necessary to record each The position of the point in space can completely express a point cloud. Similar to two-dimensional images, each position in the acquisition process has corresponding attribute information, usually RGB color value, and the color value reflects the color of the object; for point cloud, 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, the points in the point cloud can include point location information and point attribute information. For example, the position information of the point may be three-dimensional coordinate information (x, y, z) of the point. The location information of a point may also be referred to as geometric information of a point. For example, the point attribute information may include color information (three-dimensional color information) and/or reflectance (one-dimensional reflectance information r) and the like. For example, color information may be information on any color space. For example, color information may be RGB information. Wherein, R represents red (Red, R), G represents green (Green, G), and B represents blue (Blue, B). For another example, the color information may be luminance 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 by the principle of laser measurement, the points in the point cloud can include the three-dimensional coordinate information of the point and the reflectance value of the point. For another example, according to the 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, the point cloud is obtained by combining the principles of laser measurement and photogrammetry. The points in the point cloud can include the three-dimensional coordinate information of the point, the reflectance value of the point and the three-dimensional color information of the point.

Figure 2A-Figure 2G shows a point cloud image and its corresponding data storage format, wherein Figure 2A-Figure 2F provides six viewing angles of the point cloud image; Figure 2G consists of the file header information part and data The header information includes the data format, data representation type, total point cloud points, and the content represented by the point cloud. For example, the point cloud is in ".ply" format, represented by ASCII code, the total number of points is 207242, and each point has three-dimensional coordinate information (x, y, z) and three-dimensional color information RGB (Red, Green, Blue).

Point clouds can be divided into the following ways:

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

Dynamic point cloud: the object is moving, but the device for obtaining the point cloud is still;

Dynamically obtain point cloud: The device for obtaining point cloud is in motion.

For example, according to the purpose of point cloud, it is divided into two categories:

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 emergency rescue robots;

Category 2: Human eyes perceive point clouds, which can be used in point cloud application scenarios such as digital cultural heritage, free viewpoint broadcasting, 3D immersive communication, and 3D immersive interaction.

Point cloud can flexibly and conveniently express the spatial structure and surface properties of three-dimensional objects or scenes, and because point cloud is obtained by directly sampling real objects, it can provide a strong sense of reality under the premise of ensuring accuracy, so it is widely used. Including virtual reality games, computer-aided design, geographic information systems, automatic navigation systems, digital cultural heritage, free viewpoint broadcasting, 3D immersive telepresence, 3D reconstruction of biological tissues and organs, etc.

The collection of point clouds 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 The point cloud of tens of millions of points can be obtained per second. These technologies reduce the cost and time period of point cloud data acquisition, and improve the accuracy of the data. The transformation of point cloud data acquisition methods has made it possible to acquire a large amount of point cloud data. With the growth of application requirements, the processing of massive 3D point cloud data encounters the bottleneck of storage space and transmission bandwidth limitations.

Exemplarily, taking a point cloud video with a frame rate of 30 frames per second (fps) as an example, the number of points in each frame of 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 about 0.7million×(4Byte×3+1Byte×3)×30fps×10s=3.15GB, in which, 1Byte is 8bit, and the YUV sampling format is 4:2:0, and the frame rate is For 1280×720 2D video at 24fps, the data volume of 10s is about 1280×720×12bit×24fps×10s≈0.33GB, and the data volume of 10s two-view 3D video 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 duration. Therefore, in order to better realize data management, save server storage space, and reduce the 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.

That is to say, because point cloud is a collection of massive points, storing point cloud will not only consume a lot of memory, but also is not conducive to transmission, and there is not such a large bandwidth to support the direct transmission of point cloud at the network layer without compression, so , need to compress the point cloud.

Currently, the point cloud coding framework that can compress the point cloud can be the G-PCC codec framework or the V-PCC codec framework provided by MPEG, or the AVS-PCC codec framework provided by AVS. The G-PCC codec framework can be used to compress the first type of static point cloud and the third type of dynamically acquired point cloud, and the V-PCC codec framework can be used to compress the second type of dynamic point cloud. The G-PCC codec framework is also called point cloud codec TMC13, and the V-PCC codec framework is also called point cloud codec TMC2.

The embodiment of the present application provides a network architecture of a video encoding and decoding system including a decoding method and an encoding method. FIG. It includes one or more electronic devices 13 to 1N and a communication network 01 , where the electronic devices 13 to 1N can perform video interaction through the communication network 01 . The electronic device may be various types of devices with video codec functions during implementation, for example, the electronic device may include a mobile phone, a tablet computer, a personal computer, a personal digital assistant, a navigator, a digital phone, a video phone, TV sets, sensing devices, servers, etc., are not limited in this embodiment of the application. Wherein, the decoder or encoder in the embodiment of the present application may be the above-mentioned electronic device.

Wherein, the electronic device in the embodiment of the present application has a video encoding and decoding function, and generally includes a video encoder (ie, an encoder) and a video decoder (ie, a decoder).

In the embodiment of the present application, the codec framework is described in the AVS-PCC codec framework.

Point cloud compression generally uses point cloud geometric information and attribute information to compress separately. Compression of cloud attributes; at the decoding end, the geometric information of the point cloud is first decoded in the geometric decoder, and then the decoded geometric information is input into the attribute decoder as additional information to assist in the compression of the point cloud attributes. The entire codec consists of preprocessing/postprocessing, geometric encoding/decoding, and attribute encoding/decoding.

The present application provides a video encoding system, as shown in FIG. 4 , the framework of the point cloud compression reference platform PCRM of AVS point cloud. The video encoding system 11 includes a geometric encoder: a coordinate translation unit 111, a coordinate quantization unit 112, and an octave Tree construction unit 113 , geometric entropy encoder 114 , geometric reconstruction unit 115 . Attribute encoder: attribute recoloring unit 116 , color space transformation unit 117 , first attribute prediction unit 118 , quantization unit 119 and attribute entropy encoder 1110 .

For PCRM, in the geometric coding part of the encoding end, the original geometric information is firstly preprocessed, the geometric origin is normalized to the minimum value position in the point cloud space by the coordinate translation unit 111, and the geometric information is converted from the floating point by the coordinate quantization unit 112 Points are converted into plastics, which is convenient for subsequent regularization processing; then the regularized geometric information is geometrically coded, and the point cloud space is recursively divided by the octree structure through the octree construction unit 113, and each time the current node is divided into Eight sub-blocks of the same size, and judge the occupancy code word of each sub-block. When the sub-block does not contain a point, it is recorded as empty, otherwise it is recorded as non-empty, and the occupancy code of all blocks is recorded in the last layer of recursive division. word information, and carry out geometric encoding; the geometric information expressed by the octree structure is input into the geometric entropy encoder 114 on the one hand to form a geometric code stream; on the other hand, the geometric reconstruction unit 115 in the encoder performs geometric reconstruction processing. The geometric information of is fed into the attribute encoder as additional information.

In the attribute encoding part, the original attribute information is firstly preprocessed. Since the geometric information has changed after the geometric encoding, the attribute recoloring unit 116 is used to reassign the attribute value for each point after the geometric encoding to realize the attribute Recolor. In addition, if the attribute information to be processed is color information, the original color information needs to be transformed into a YUV color space that is more in line with the visual characteristics of the human eye through the color space transformation unit 117; Unit 118 performs attribute encoding or prediction on the preprocessed attribute information. The attribute prediction first needs to reorder the point cloud, and the reordering method is Morton code. Therefore, the traversal order of attribute encoding or attribute prediction is Morton order. The attribute prediction method in PCRM is a single-point prediction based on Morton order, that is, according to the Morton order, one point is traced forward from the current point to be encoded (current point), and the neighbor point found is the prediction reference point of the current point to be encoded. Then the attribute reconstruction value of the predicted reference point is used as the attribute prediction value, and the attribute residual value is the difference between the attribute value of the current point to be encoded and the attribute prediction value; finally, the residual is quantized by the quantization unit 119, and the quantized residual The difference is input to the attribute entropy encoder 1110 to form an attribute code stream.

The present application provides a video decoding system, as shown in Figure 5, the framework of the point cloud compression reference platform PCRM of AVS point cloud, the video decoding system 12 includes a geometric decoder: a geometric entropy decoder 121, an octree reconstruction unit 122 . The coordinate inverse quantization unit 123 , and the 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 .

At the decoding end, the geometry and attributes are also decoded separately. In the geometric decoding part, first, the geometric code stream is entropy decoded by the geometric entropy decoder 121 to obtain the geometric information of each node, and then the octree structure is constructed by the octree reconstruction unit 122 in the same manner as the geometric encoding, Combining the decoded geometry to reconstruct the geometric information expressed through the octree structure after the coordinate transformation, on the one hand, the information is subjected to coordinate inverse quantization by the coordinate inverse quantization unit 123 and detranslated by the coordinate inverse translation unit 124 to obtain the decoded geometric information. On the other hand, it is input into the attribute decoder as additional information. In the attribute decoding part, the Morton sequence is constructed in the same way as the encoding end, and the attribute code stream is first entropy decoded by the attribute entropy decoder 125 to obtain the quantized residual information; then the inverse quantization is performed by the inverse quantization unit 126, Obtain the point cloud residual value; similarly, in the same manner as the attribute encoding, obtain the attribute prediction value of the point to be decoded by the second attribute prediction unit 127, and then add the attribute prediction value and the attribute residual value to restore The YUV attribute value of the current point to be decoded is obtained; finally, the decoded attribute information is obtained through the color space inverse transformation of the color space inverse transformation unit 128.

The regularization processing of the octree of the point cloud is introduced below.

Due to the irregular distribution of the point cloud in space, it brings challenges to the encoding process. Therefore, the recursive octree structure is used to express the point in the point cloud as the center of the cube in a regular way, as shown in Figure 6A. First, the The entire point cloud is placed in a cube bounding box, and the coordinates of the points in the point cloud are expressed as (x ^k , y ^k , z ^k ), k=0,...,K-1, where K is the total number of points in the point cloud, The boundary values of the point cloud in the x, y, and z directions are formula (1) - formula (6):

x ^min ＝min(x ⁰ ,x ¹ ,…,x ^K-1 ) (1)

y ^min ＝min(y ⁰ ,y ¹ ,…,y ^K-1 ) (2)

z ^min ＝min(z ⁰ ,z ¹ ,…,z ^K-1 ) (3)

x ^man ＝max(x ⁰ ,x ¹ ,…,x ^K-1 ) (4)

y ^max ＝max(y ⁰ ,y ¹ ,...,y ^K-1 ) (5)

z ^max ＝max(z ⁰ ,z ¹ ,…,z ^K-1 ) (6)

Among them, the origin (x ^origin , y ^origin , z ^origin ) of the bounding box can be calculated as formula (7) - formula (9):

x ^origin = int(floor(x ^min )) (7)

y ^origin = int(floor(y ^min )) (8)

z ^origin = int(floor(z ^min )) (9)

Among them, the dimensions Bouding BoxSize _x , Bouding BoxSize _y and Bouding BoxSize _z of the bounding box in the x, y, and z directions can be calculated as formula (10) - formula (12):

Bouding BoxSize _x = int(x ^max -z ^xrigin +1 (10)

Bouding BoxSize _y = int(y ^max -y ^origin +1 (11)

Bouding BoxSize _z = int(z ^max -z ^origin +1 (12)

In the embodiment of the present application, as shown in Figures 6B-6G, the bounding box is first divided into octrees, and each time eight sub-blocks are obtained, and then the non-empty blocks (blocks containing points) in the sub-blocks are divided again The octree division of , so recursively divided until a certain depth, the non-empty sub-block of the final size is called voxel, each voxel contains one or more points, and the geometric positions of these points are normalized to the center point of the voxel , the attribute value of the center point is the average value of the attribute values of all points in the voxel, and finally the image shown in Figure 6G is obtained.

It should be noted that regularizing the point cloud into blocks in space is beneficial to the description of the relationship between points in the point cloud, and then can express a specific encoding sequence, and encode each voxel in a certain order, that is, the encoded voxel represents The points (or "nodes") of , a commonly used coding order is the cross-separated Morton order. Exemplarily, the encoding sequence of the Morton code in the two-dimensional space in Fig. 7A-Fig. 7C is used, taking a block of size 8*8 as an example, where the order of the arrows represents the encoding order of the points under the Morton order. As shown in FIG. 7A, the "z"-shaped Morton coding order of 2*2 pixels in the block is shown. Figure 7B shows the "z"-shaped Morton coding sequence between four 2*2 blocks, and Figure 7C shows the "z"-shaped Morton coding sequence between four 4*4 blocks, which form the entire 8*8 block Morton coding sequence. The Morton coding sequence extended to the three-dimensional space is shown in Figure 8, which shows 16 nodes, and the Morton coding sequence between each "z" and "z" inside each "z" is First encode along the x-axis, then along the y-axis, and finally along the z-axis.

In the embodiment of this application, the attribute residual quadratic prediction algorithm currently used by PCRM uses the R component to predict the G component, and uses the sum of the R component and the G component to predict the B component, which can effectively eliminate the correlation between the three components. Thereby improving the coding efficiency. However, in nature, the wavelength distribution range of red light is 620-750nm, the wavelength distribution range of green light is 495-570nm, and the wavelength distribution range of blue light is 450-475nm, as shown in Figure 9, according to the From the point of view of the coincidence degree, it is obvious that it is not very reasonable to use the R component to predict the other two components, and the prediction is not accurate and fixed.

Based on this, when performing the encoding method, perform secondary prediction on the attribute residual for the current point, which mainly acts on the quantization unit 119 and the attribute entropy encoder 1110 of the video encoding system 11; The residual performs secondary prediction, which is mainly used between the second attribute prediction unit 127 and the color space inverse transformation unit 128 of the video decoding system 12 .

An embodiment of the present application provides a decoding method, which is applied to a video decoding device, that is, a decoder. The function realized by this method can be realized by calling the program code by the first processor in the video decoding device. Of course, the program code can be stored in the computer storage medium. It can be seen that the video decoding device includes at least the first processor and the first memory medium. Wherein, the current decoding point and the current encoding point are both represented by the current point below.

FIG. 10 is a schematic diagram of an implementation flow of a decoding method according to an embodiment of the present application. The method includes:

S101. Analyze the code stream, and determine the attribute residual value of the color component corresponding to the current point.

S102. Obtain an attribute prediction value of the color component corresponding to the current point.

In the embodiment of the present application, after obtaining the code stream, the decoder can analyze the attribute residual value of the color component corresponding to the current point from the code stream. Wherein, the attribute residual value analyzed in the code stream is a quantized residual value.

It should be noted that, in a decoding method provided by an embodiment of the present application, in the process of performing attribute decoding on color components, the color component at the current point may include: a first color component, a second color component, and a third color component. The first color component, the second color component and the third color component may be three RGB components respectively.

In the embodiment of the present application, the points in the point cloud all have attribute information of RGB three components. The decoder can parse out the attribute residual values corresponding to each color component of the current point.

In the embodiment of the present application, the decoder needs to perform decoding processing on each color component of the current point.

In the embodiment of this application, since the encoding can be based on the single-point prediction of the Morton order, that is, one point is traced forward from the current point according to the Morton order, the found point is the prediction reference point of the current point, and then the prediction reference point The attribute reconstruction value of is used as the attribute prediction value. When decoding the current point, after the decoder predicts the attribute of the current point, it can obtain the attribute reconstruction value of the prediction reference point of the current point, that is, obtain the attribute prediction value of the color component corresponding to the current point.

S103. Determine a prediction mode of the color component of the current point, wherein the prediction mode is determined based on the degree of difference between the color components.

S104. Based on the prediction mode, the attribute residual value, the attribute prediction value and the initial cross-component attribute residual prediction value, decode and reconstruct the color component of the current point to obtain the attribute reconstruction value of the color component.

During the decoding process, the decoder can perform secondary attribute prediction to eliminate redundancy after decoding the attribute residual value. Therefore, in the process of secondary attribute prediction, the decoder can determine the prediction mode of the color component of the current point during the secondary attribute prediction, and then perform secondary attribute prediction according to the prediction mode, and combine the attribute residual value and attribute prediction value and the initial cross-component attribute residual prediction value, decode and reconstruct the color component of the current point, and obtain the attribute reconstruction value of the color component.

In some embodiments of the present application, the prediction mode represents the encoding and decoding sequence of the color components or represents the prediction form of the color components (for example, which color component is encoded and decoded first). Wherein, the prediction mode is determined based on the degree of difference between the color components.

In some embodiments of the present application, the prediction mode includes: the first color component to be predicted; the first color component to be predicted is the first coded color among the first color component, the second color component and the third color component portion.

It is understandable that the decoder can adaptively decide how to decode and reconstruct the color component by first encoding the first color component to be predicted. Considering the adaptive prediction form of the color component, the secondary attribute prediction can be improved. the accuracy.

In some embodiments of the present application, S1031 and S1032 may be used to determine the prediction mode, and S1033-1035 may also be used to implement, which is not limited in this embodiment of the present application.

S1031. When parsing the code stream, parse out the prediction mode flag bit.

S1032. Determine the prediction mode of the color component of the current point according to the prediction mode flag bit.

When decoding the code stream, since the prediction mode has been confirmed during encoding, the prediction mode flag is transmitted in the code stream, so that when decoding the current point, the decoder can simultaneously parse out the current point from the code stream The prediction mode flag of the color component when performing secondary attribute prediction, wherein the prediction mode flag indicates which color component is coded first. Therefore, the decoder can determine the prediction mode of the color component at the current point according to the prediction mode flag bit.

It should be noted that the prediction mode flag can indicate which color component is coded first. Exemplarily, the prediction mode flag can be represented in digital form. For example, 0 can be used to represent the first color component, 1 can be used to represent the second color component, and 2 can be used to represent the third color component. This embodiment of the present application does not limit it. The prediction mode flag is determined based on the degree of difference between color components during encoding.

It can be understood that the decoder can determine the prediction mode through the indication of the prediction mode flag, without performing calculation of the prediction mode, which can save decoding time and improve decoding efficiency.

S1033. Based on the attribute prediction value, determine a standard value of the color component corresponding to the current point.

S1034. Determine at least two degrees of difference between at least two color components corresponding to the current point and a standard value.

S1035. Based on at least two difference degrees, determine a prediction mode of the color component of the current point.

The decoder can also determine the prediction mode in a way that does not require the prediction mode flag bit. The decoder can determine a standard value for the color component according to the attribute prediction value corresponding to the current point, and then compare the attribute prediction value of each color component of the current point with the standard value to determine at least two color components. degree of difference, and then determine the prediction mode based on at least two degrees of difference.

In the embodiment of the present application, the property prediction value includes: a first property prediction value of the first color component, a second property prediction value of the second color component, and a third property prediction value of the third color component.

Then, the decoder determines the standard value of the color component corresponding to the current point based on the attribute prediction value, including at least one of the following:

averaging the first attribute predicted value, the second attribute predicted value and the third attribute predicted value to determine a standard value;

Determining the maximum value among the first attribute predicted value, the second attribute predicted value and the third attribute predicted value as the standard value;

Determining that the minimum value among the first attribute predicted value, the second attribute predicted value and the third attribute predicted value is a standard value;

The median value of the first attribute predicted value, the second attribute predicted value and the third attribute predicted value is determined as a standard value.

It should be noted that the standard value can also be obtained according to other mathematical processing means of the predicted value of the first attribute, the predicted value of the second attribute and the predicted value of the third attribute, which is not limited in this embodiment of the present application.

In the embodiment of this application, after the decoder determines the standard value, it can compare the attribute prediction value of each color component of the current point with the standard value to obtain three color difference degrees, or it can compare the attribute prediction value of each color component in the current point The attribute prediction values of any two color components are compared with the standard values respectively, and two difference degrees corresponding to any two color components are obtained.

In some embodiments of the present application, the decoder may determine the minimum degree of difference among at least two degrees of difference; and determine the color component corresponding to the minimum degree of difference as the prediction mode. Alternatively, the decoder determines a sorting result of at least two different degrees based on the at least two different degrees; and determines a prediction mode according to the sorting result.

It should be noted that the prediction mode indicates that the first predicted color component to be predicted is firstly decoded in the second attribute prediction of the current point, and then the second attribute prediction is performed on other color components.

It should be noted that, based on the at least two difference degrees, the decoder determines the sorting results of the at least two difference degrees; according to the sorting results, the prediction mode corresponding to the color component with the smallest difference can be determined. Moreover, when the secondary attribute prediction of the color components of the current point is performed, the decoding order of the color components can be determined from the order of the difference degrees from small to large according to the sorting results.

Exemplarily, the decoder calculates the difference between the R component and the G component and the standard value (that is, the difference diff _R and diff _G ), and compares the two differences, and if diff _R <diff _G , then determine that the R component is the prediction mode for secondary prediction of attribute residuals, otherwise use the G component as the prediction mode for secondary prediction of attribute residuals.

Exemplarily, the decoder calculates the differences (diff _R , diff G, and diff _B ) between the R component, the _G component, and the B component and the standard value, and compares them. If diff _R in diff _R , diff _G , and diff _B If it is the smallest, determine the R component as the prediction mode for secondary prediction of the attribute residual; if the diff _G is the smallest, use the G component as the prediction mode for the secondary prediction of the attribute residual; if the diff _B is the smallest, use the B component as the prediction mode Quadratic prediction of attribute residuals.

It should be noted that after the decoder determines the prediction mode of the current point, it first decodes the first color component to be predicted, and then decodes the other color components (the second color component to be predicted) based on the first color component to be predicted. component and the third color component to be predicted) for decoding and reconstruction (that is, secondary attribute prediction), or based on the first color component to be predicted, the second color component to be predicted is decoded and reconstructed, and the second color component to be predicted is used The component decodes and reconstructs the third color component to be predicted. Wherein, the second to-be-predicted color component and the third to-be-predicted color component are color components other than the first to-be-predicted color component among the first, second, and third color components.

In some embodiments of the present application, the implementation of S104 may include:

S1041. According to the prediction mode, based on the attribute residual value of the first color component to be predicted, determine the reconstruction value of the first attribute residual of the first color component to be predicted; wherein, the first color component to be predicted is the prediction mode The color component of the representation.

S1042. Based on the attribute prediction value, the first attribute residual reconstruction value and the initial cross-component attribute residual prediction value, decode and reconstruct the color component of the current point to obtain the attribute reconstruction value of the color component.

In this embodiment of the present application, the decoder may dequantize the attribute residual value of the first to-be-predicted color component according to the prediction mode, and determine the first reconstructed attribute value of the first to-be-predicted color component. Since each point can have three color components, when performing secondary attribute prediction on the current point, each color component needs to be processed to complete the decoding and reconstruction of the current point.

In some embodiments of the present application, the attribute reconstruction value includes: the first attribute reconstruction value corresponding to the first to-be-predicted color component, the second attribute reconstruction value corresponding to the second to-be-predicted color component, and the third to-be-predicted color component The third attribute reconstruction value corresponding to the predicted color component.

In some embodiments of the present application, since the first color component to be predicted is the color component corresponding to the prediction mode, the decoder first decodes and reconstructs the first color component to be predicted, and then based on the first color component to be predicted component continues to decode other color components. Here, the decoder can add the initial cross-component attribute residual prediction value, the attribute prediction value corresponding to the first to-be-predicted color component, and the first attribute residual reconstruction value to obtain the first to-be-predicted color component A property reconstruction value.

Determine the second cross-component attribute residual prediction value based on the first attribute residual reconstruction value; based on the second cross-component attribute residual prediction value, the second to-be-predicted color component and the third to-be-predicted color component Perform decoding and reconstruction to obtain the second attribute reconstruction value and the third attribute reconstruction value. Or, based on the reconstruction value of the first attribute residual, the second cross-component attribute residual prediction value and the third cross-component attribute residual prediction value are determined; based on the second cross-component attribute residual prediction value, the second Decode and reconstruct the color components to be predicted to obtain the second attribute reconstruction value; based on the third cross-component attribute residual prediction value, decode and reconstruct the third color component to be predicted to obtain the third attribute reconstruction value.

In some embodiments of the present application, the second cross-component attribute residual prediction value is the sum of the first attribute residual reconstruction value and the initial cross-component attribute residual prediction value, or is the first attribute residual Multiplier or divisor of the difference reconstruction value.

In some embodiments of the present application, the third cross-component attribute residual prediction value is the sum of the first attribute residual reconstruction value and the initial cross-component attribute residual prediction value, or is the first attribute residual Multiplier or divisor of the difference reconstruction value.

It should be noted that, for each point in the point cloud, the initial cross-component attribute residual prediction value may be 0, which is not limited in this embodiment of the present application. In the embodiment of this application, the decoder uses the cross-component attribute residual prediction value to perform secondary attribute prediction, but the cross-component attribute residual prediction values corresponding to different color components of a point are related, but may not be the same .

In this embodiment of the application, the first color component to be predicted uses the initial cross-component attribute residual prediction value to perform secondary attribute prediction, and the second color component to be predicted uses the second cross-component attribute residual prediction value to perform For secondary attribute prediction, the third color component to be predicted uses the third cross-component attribute residual prediction value for secondary attribute prediction.

In some embodiments of the present application, the decoder decodes and reconstructs other color components based on the second cross-component attribute residual prediction value, and the realization of obtaining the second attribute reconstruction value and the third attribute reconstruction value may include:

Based on the second cross-component attribute residual prediction value, decode and reconstruct the second color component to be predicted to obtain the second attribute reconstruction value; based on the second attribute residual reconstruction value, determine the third cross-component attribute residual difference prediction value; based on the third cross-component attribute residual prediction value, decode and reconstruct the third to-be-predicted color component to obtain the third attribute reconstruction value.

In some embodiments of the present application, the third cross-component attribute residual prediction value is the sum of the second attribute residual reconstruction value and the second cross-component attribute residual prediction value, or is the second attribute The multiplier or divisor of the residual reconstruction value.

Exemplarily, it is assumed that the first color component to be predicted is the G component, the second color component to be predicted is the R component, and the third color component to be predicted is the B component. Then, when the decoder performs secondary attribute prediction on the G component, it uses the initial cross-component attribute residual prediction value to obtain the first attribute reconstruction value of the G component. At this time, when the decoder performs secondary attribute prediction of other components, the first attribute residual reconstruction value of the G component can be used to update the initial cross-component attribute residual prediction value to obtain the second cross-component attribute residual value difference prediction value, and the first attribute residual reconstruction value of the G component can be used to update the initial cross-component attribute residual prediction value to obtain the third cross-component attribute residual prediction value, and the first attribute residual prediction value of the R component can also be used The reconstruction value of the residual of the two attributes is updated, and the predicted value of the second cross-component attribute residual is updated to obtain the third predicted value of the cross-component attribute residual.

Exemplarily, the first attribute residual reconstruction value of the G component can be used to update the initial cross-component attribute residual prediction value, and the second cross-component attribute residual prediction value can be the first attribute residual reconstruction value + Obtain the second cross-component attribute residual prediction value for the initial cross-component attribute residual prediction value; or, use twice the first attribute residual reconstruction value as the second cross-component attribute residual prediction value.

The first attribute residual reconstruction value of the G component can be used to update the initial cross-component attribute residual prediction value, and the third cross-component attribute residual prediction value can be obtained, which can be the first attribute residual reconstruction value + the initial The cross-component attribute residual predictors yield the third cross-component attribute residual predictors; alternatively, half the reconstructed values of the first attribute residuals are used as the third cross-component attribute residual predictors.

Use the second attribute residual reconstruction value of the R component + the second cross-component attribute residual prediction value to obtain the third cross-component attribute residual prediction value; or, the second attribute residual reconstruction value of the R component 3 times as the third cross-component attribute residual predictor.

Two examples are used below to illustrate the decoding method of the decoder.

Exemplarily, a specific implementation on the decoder side that needs to encode the secondary prediction mode flag is as follows:

a) Set the initial cross-component attribute residual prediction value residualPrevComponent to an initial value of 0, and then decode from the code stream to obtain the prediction mode flag bit of the attribute residual secondary attribute prediction, if the prediction mode flag bit indicates the use of the G component To carry out the second prediction of the attribute residual by reconstructing the value of the attribute residual, first continue to perform the following operations on the G component;

b) Decoding and obtaining the quantized attribute residual value of the G component from the code stream, performing inverse quantization on it to obtain the reconstructed value recResidual[i] (i=R or G or B) of the attribute residual of the G component;

c) Calculate the attribute reconstruction value reconValue by adding the attribute prediction value predictor[i] of the G component obtained through the nearest neighbor search, and the attribute residual reconstruction value recResidual[i] of the G component, and the initial cross-component attribute residual prediction value [i]:

reconValue[i]=recResidual[i]+predictor[i]+residualPrevComponent

d), set the second cross-component attribute residual prediction value as the attribute residual reconstruction value of the G component + 0;

Use the reconstructed residual value of the G component to update the cross-component attribute residual prediction value, which is used for the secondary attribute prediction of the next component.

residualPrevComponent + = recResidual[i];

e) Perform operations b), c) and d) on the next color component (the second color component to be predicted), until the processing of all three components of R, G and B is completed.

It can be understood that since the adaptive selection of the prediction mode can be determined based on the prediction mode flag bit of the color component, when the decoding and reconstruction of the color component at the current point is performed according to the prediction mode, the properties of the obtained color component The accuracy of the reconstructed values is high.

A specific implementation on the decoder side that does not need to encode the secondary prediction mode flag is as follows:

a), first calculate the mean mean of the color three components of the attribute prediction value of the current point, that is, the standard value (also can be the median, maximum value, minimum value, etc.);

b), respectively calculate the difference between the R component and G component and the average value, and compare the two differences (you can also calculate the difference between the R component, G component, B component and the average value, and compare), if diff _R <diff _G , then use the attribute residual reconstruction value of the R component for attribute residual secondary attribute prediction, otherwise use the attribute residual reconstruction value of the G component for attribute residual secondary attribute prediction. If the attribute residual reconstruction value of the G component is used to predict the secondary attribute of the attribute residual, the following operations are first performed on the G component;

c) Decoding and obtaining the quantized attribute residual value of the G component from the code stream, and dequantizing it to obtain the attribute residual reconstruction value recResidual[i] (i=R or G or B) of the G component;

d) Calculate the attribute reconstruction value by adding the attribute prediction value predictor[i] of the G component obtained through the nearest neighbor search, and the attribute residual reconstruction value recResidual[i] of the G component, and the initial cross-component attribute residual prediction value reconValue[i]:

reconValue[i]=recResidual[i]+predictor[i]+residualPrevComponent

e), setting the second cross-component attribute residual prediction value as the attribute residual reconstruction value of the G component + 0;

Use the reconstructed residual value of the G component to update the cross-component attribute residual prediction value, which is used for the secondary attribute prediction of the next color component.

residualPrevComponent + = recResidual[i];

f) Perform operations c), d) and e) on the next color component (the second color component to be predicted) until the processing of the three components of R, G and B is completed.

In some embodiments of the present application, the second cross-component attribute residual prediction value or the third cross-component attribute residual prediction value is set as a multiple or divisor of the attribute residual reconstruction value of the secondary prediction component. For example, when performing secondary prediction of attribute residuals on the R component, set the cross-component attribute residual prediction value to the attribute residual reconstruction value of the G component divided by 2; The predicted value of the component attribute residual is set as the reconstructed value of the attribute residual of the G component divided by 4.

It can be understood that since the adaptive selection of the prediction mode can be performed based on the degree of difference between the color components, when the decoding and reconstruction of the color component of the current point is performed according to the prediction mode, the properties of the obtained color components The accuracy of the reconstructed values is high.

An embodiment of the present application provides an encoding method, which is applied to a video encoding device, that is, an encoder. The function realized by this method can be realized by calling the program code by the second processor in the video encoding device, and of course the program code can be stored in the computer storage medium. It can be seen that the video encoding device includes at least the second processor and the second storage medium.

Fig. 11 is a schematic diagram of an implementation process of encoding according to an embodiment of the present application. The method includes:

S201. Obtain an attribute prediction value of a color component corresponding to a current point in a point cloud.

S202. Based on the attribute prediction value, determine a standard value of the color component corresponding to the current point.

S203. Determine at least two degrees of difference between at least two color components corresponding to the current point and a standard value.

S204. Determine a prediction mode of the color component based on at least two difference degrees.

In the embodiment of this application, an encoding method is proposed. In the process of attribute encoding, the encoder can obtain the attribute of the color component corresponding to the current point in the point cloud after the attribute prediction is performed by the first attribute unit. Predicted value, in order to eliminate redundancy at this time, you can continue to perform secondary attribute prediction on the color component of the current point.

In the embodiment of the present application, the encoder can first determine a standard value for the color component according to the attribute prediction value of each color component, and then determine the difference between at least two color components of the current point and the standard value, that is, at least Two degrees of difference, and then determine the prediction mode based on at least two degrees of difference.

It should be noted that the standard value can be directly obtained from the attribute prediction value of the color component, or it can be determined based on the attribute prediction value of at least two color components combined with the attribute information of the color component to obtain the initial attribute residual reconstruction value. This application implements Examples are not limited.

In some embodiments of the present application, at least two degrees of difference can be obtained by directly comparing attribute prediction values of at least two color components.

Wherein, the property prediction value includes: a first property prediction value of the first color component, a second property prediction value of the second color component, and a third property prediction value of the third color component.

Then, the encoder determines the standard value of the color component corresponding to the current point based on the attribute prediction value, including at least one of the following:

In the embodiment of this application, after the encoder determines the standard value, it can compare the attribute prediction value of each color component of the current point with the standard value to obtain three color difference degrees, or it can use the The attribute prediction values of any two color components are compared with the standard values respectively to obtain two degrees of difference corresponding to any two color components, which is not limited in this embodiment of the present application.

In some embodiments of the present application, the encoder determines the initial attribute residual reconstruction value obtained according to attribute prediction values of at least two color components combined with attribute information of the color components.

In some embodiments of the present application, the encoder determines the standard value of the color component corresponding to the current point based on the attribute prediction value as follows:

Based on the attribute prediction value and the attribute information of the current point, determine the initial attribute residual reconstruction value corresponding to the current point; based on the initial attribute residual reconstruction value, determine the standard value of the color component corresponding to the current point.

In the embodiment of the present application, the encoder determines the initial residual value corresponding to the current point based on the predicted attribute value and the attribute information of the current point; quantizes and dequantizes the initial residual value to obtain the reconstruction value of the initial attribute residual.

It should be noted that, according to the attribute prediction value of each color component and the attribute information of the color component of the current point, the encoder determines the initial attribute residual reconstruction value of each color component corresponding to the current point, and based on the initial attribute residual of each color component Reconstruct the value to determine the standard value of the color component corresponding to the current point.

In some embodiments of the present application, the initial attribute residual reconstruction value includes: the first initial attribute residual reconstruction value of the first color component, the second initial attribute residual reconstruction value of the second color component, and the third color component The residual reconstruction value of the third genus initial attribute;

The encoder determines the standard value of the color component corresponding to the current point based on the initial attribute residual reconstruction value, including at least one of the following:

averaging the first initial attribute residual reconstruction value, the second initial attribute residual reconstruction value and the third initial attribute residual reconstruction value to determine a standard value;

Determine the maximum value among the first initial attribute residual reconstruction value, the second initial attribute residual reconstruction value and the third initial attribute residual reconstruction value as the standard value;

Determine the minimum value among the first initial attribute residual reconstruction value, the second initial attribute residual reconstruction value and the third initial attribute residual reconstruction value as a standard value;

Determine the standard value as the median of the first initial attribute residual reconstruction value, the second initial attribute residual reconstruction value and the third initial attribute residual reconstruction value.

In the embodiment of this application, after determining the standard value, the encoder can compare the initial attribute residual reconstruction value of each color component of the current point with the standard value to obtain three color difference degrees, or the current The initial attribute residual reconstruction values of any two color components in the point are compared with the standard values to obtain two degrees of difference corresponding to any two color components, which is not limited in this embodiment of the present application.

It should be noted that the standard value can also be obtained according to other mathematical processing methods of the first initial attribute residual reconstruction value, the second initial attribute residual reconstruction value, and the third initial attribute residual reconstruction value, which is not limited in this embodiment of the present application.

In some embodiments of the present application, the encoder may determine the minimum degree of difference among at least two degrees of difference; and determine the color component corresponding to the minimum degree of difference as the prediction mode. Alternatively, the encoder determines a sorting result of the at least two difference degrees based on the at least two difference degrees; and determines a prediction mode according to the sorting result.

In some embodiments of the present application, the prediction mode represents the encoding and decoding sequence of the color components or represents the prediction form of the color components (for example, which color component is encoded and decoded first).

It should be noted that, based on the at least two difference degrees, the encoder determines the sorting results of the at least two difference degrees; according to the sorting results, the prediction mode corresponding to the color component with the smallest difference can be determined. Moreover, when the secondary attribute prediction of the color component of the current point is performed, the coding sequence of the color components can be determined from the order of the degree of difference from small to large according to the sorting result.

Exemplarily, the encoder calculates the difference between the R component and the G component and the standard value (ie, the difference diff _R and diff _G ), and compares the two differences, and if diff _R <diff _G , then determine that the R component is the prediction mode for secondary prediction of attribute residuals, otherwise use the G component as the prediction mode for secondary prediction of attribute residuals.

Exemplarily, the encoder calculates the differences (diff _R , diff G and diff _B ) between the R component, the _G component, and the B component and the standard value, and compares them. If diff _R among diff _R , diff _G and diff _B If it is the smallest, determine the R component as the prediction mode for secondary prediction of the attribute residual; if the diff _G is the smallest, use the G component as the prediction mode for the secondary prediction of the attribute residual; if the diff _B is the smallest, use the B component as the prediction mode Quadratic prediction of attribute residuals.

In some embodiments of the present application, when the encoder determines the prediction mode of the color component based on at least two differences, it can generate a prediction mode flag and write it into the code stream; the prediction mode flag represents the prediction mode.

It should be noted that, in the process of determining the prediction mode directly through the standard value determined by the attribute prediction value, the encoder does not need to generate the prediction mode flag, and directly performs the same determination process of the prediction mode on the decoder side. .

S205. Based on the prediction mode, the attribute prediction value and the initial cross-component attribute residual prediction value, perform secondary prediction on the color component of the current point to obtain the attribute residual value of the color component.

In the embodiment of this application, in the process of secondary attribute prediction, the encoder determines the prediction mode of the color component of the current point during the secondary attribute prediction, and then performs secondary attribute prediction according to the prediction mode, and combines the predicted value of the attribute and the initial cross-component attribute residual prediction value, perform secondary prediction on the color component of the current point, and obtain the attribute residual value of the color component.

In some embodiments of the present application, the encoder can perform secondary attribute prediction according to the prediction mode, and combine the attribute information of each color component, the attribute prediction value and the initial cross-component attribute residual prediction value to carry out the color component of the current point Quadratic prediction to obtain the attribute residual value of the color component.

It should be noted that after the encoder determines the prediction mode of the current point, it first performs second prediction on the first color component to be predicted, and then performs second prediction on the other color components (the second color component to be predicted) based on the first color component to be predicted. predicted color component and the third color component to be predicted) for secondary prediction, or secondly predict the second color component to be predicted based on the first color component to be predicted, and use the second color component to be predicted to predict the second color component Three to-be-predicted color components perform secondary prediction. Wherein, the second to-be-predicted color component and the third to-be-predicted color component are color components other than the first to-be-predicted color component among the first, second, and third color components.

In some embodiments of the present application, according to the prediction mode, the encoder combines the first attribute information of the first color component to be predicted with the attribute prediction value of the first color component to be predicted and the initial cross-component attribute residual prediction value Quantize after subtraction in turn to achieve secondary prediction, and obtain the attribute residual value of the first color component to be predicted; after inverse quantization of the attribute residual value of the first color component to be predicted, the first color to be predicted is obtained The first attribute residual reconstruction value of the component; based on the first attribute residual reconstruction value, the second cross-component attribute residual prediction value is determined; based on the second cross-component attribute residual prediction value, the other color components are The second prediction is to obtain the attribute residual value of the second to-be-predicted color component and the attribute residual value of the third to-be-predicted color component; wherein, the second to-be-predicted color component and the third to-be-predicted color component are the Other color components except the first to-be-predicted color component among the first color component, the second color component and the third color component.

In the embodiment of the present application, the encoder can use the first attribute information of the first color component to be predicted according to the prediction mode, subtract the attribute prediction value of the first color component to be predicted, and then subtract the initial cross-component attribute The residual prediction value is quantized to obtain the attribute residual value of the first color component to be predicted. Since each point can have three color components, when performing secondary attribute prediction on the current point, each color component needs to be processed to complete the coding part of the current point's secondary attribute prediction.

In some embodiments of the present application, the encoder performs secondary prediction on other color components based on the second cross-component attribute residual prediction value to obtain the attribute residual value of the second to-be-predicted color component and the third to-be-predicted color component. The implementation of predicting the attribute residual value of the color component is:

The encoder performs secondary prediction on the second color component to be predicted based on the second cross-component attribute residual prediction value to obtain the attribute residual value of the second color component to be predicted; for the second color component to be predicted After the attribute residual value is dequantized, the second attribute residual reconstruction value of the second color component to be predicted is obtained; based on the second attribute residual reconstruction value, the third cross-component attribute residual prediction value is determined; based on The third cross-component attribute residual prediction value performs secondary prediction on the third to-be-predicted color component to obtain the attribute residual value of the third to-be-predicted color component.

It should be noted that, for each point in the point cloud, the initial cross-component attribute residual prediction value may be 0, which is not limited in this embodiment of the present application. In the embodiment of this application, the encoder uses the cross-component attribute residual prediction value to perform secondary attribute prediction, but the cross-component attribute residual prediction values corresponding to different color components of a point are related, but may not be the same .

In some embodiments of the present application, after the encoder dequantizes the attribute residual value of the first color component to be predicted, and obtains the first attribute residual reconstruction value of the first color component to be predicted, the encoder Based on the first attribute residual reconstruction value, determine the second cross-component attribute residual prediction value and the third cross-component attribute residual prediction value; based on the second cross-component attribute residual prediction value, determine the second cross-component attribute residual prediction value The predicted color component is predicted twice to obtain the attribute residual value of the second color component to be predicted; based on the third cross-component attribute residual prediction value, the third color component to be predicted is predicted twice to obtain the third The attribute residual value of a color component to be predicted.

In the embodiment of the present application, when the encoder obtains the attribute residual value of each color component, it writes the attribute residual value of the color component into the code stream.

In some embodiments of the present application, the attribute residual value of the color component includes: the attribute residual value of the first color component to be predicted, the attribute residual value of the second color component to be predicted, and the third color component to be predicted Attribute residual value for the component.

Wherein, the attribute residual value of the first color component to be predicted, the attribute residual value of the second color component to be predicted, and the attribute residual value of the third color component to be predicted are quantized attribute residual values.

It should be noted that the description of the encoder is consistent with the principle of the decoder, and the implementation is corresponding, which will not be repeated here.

Two examples are used below to illustrate the decoding method of the decoder.

Exemplarily, a specific implementation on the encoder side that needs to encode the secondary prediction mode flag is as follows:

a), first under the premise of not using residual secondary attribute prediction, calculate the initial attribute residual reconstruction value recResidual[i] (i=R or G or B) of the color three-component of the current point;

b), calculate the mean value mean of the initial attribute residual reconstruction value of the three color components, that is, the standard value (also can be the median value, maximum value, minimum value, etc.), which is not limited by the embodiment of the present application;

c), respectively calculate the difference between the R component and the G component and the average value, that is, the degree of difference, and compare the two differences (you can also calculate the difference between the R component, the G component, the B component and the average value, and compare them ), if diff _R <diff _G , then use the attribute residual reconstruction value of the R component for the secondary attribute prediction of the attribute residual, otherwise use the attribute residual reconstruction value of the G component for the secondary prediction of the attribute residual;

d) Set the initial cross-component attribute residual prediction value residualPrevComponent to an initial value of 0, and according to the attribute residual secondary prediction mode determined in step c), if the attribute residual reconstruction value of the G component is used to perform attribute residual secondary Prediction, then first perform the following operations on the G component;

e), using the attribute information of the G component, obtaining the attribute prediction value of the G component and the initial cross-component attribute residual prediction value through the nearest neighbor search to calculate the residual value of the G component;

f), delta=currValue[i]-predictor[i]-residualPrevComponent(i=R or G or B);

g) Quantize the residual value to obtain the attribute residual value of the G component, then perform entropy encoding, write the code stream, and encode the flag bit of the prediction mode according to the G component;

h) Dequantize the attribute residual value of the quantized G component to obtain the reconstructed value recResidual[i] of the attribute residual of the G component;

i), setting the second cross-component attribute residual prediction value as the attribute residual reconstruction value of the G component + 0;

residualPrevComponent + = recResidual[i];

j), perform operations e), f), g), and h) on the next color component (the second color component to be predicted), until the processing of the three components of R, G, and B is completed.

It can be understood that since the adaptive selection of the prediction mode can be performed based on the degree of difference between the color components, when the second prediction of the color component of the current point is performed according to the prediction mode, the obtained color component The accuracy of attribute reconstruction values is high. In addition, the flag bit of the prediction mode can also be directly transmitted to the decoder, which improves the decoding efficiency of the decoder.

Exemplarily, a specific implementation on the encoder side that does not need to encode the secondary prediction mode flag is as follows:

a), calculate the average value mean of the attribute prediction value of the three color components, that is, the standard value (also can be the median, maximum value, minimum value, etc.), the embodiment of the present application is not limited;

b), respectively calculate the difference between the R component and the G component and the average value, that is, the degree of difference, and compare the two differences (you can also calculate the difference between the R component, the G component, the B component and the average value, and compare them ), if diff _R <diff _G , then use the attribute residual reconstruction value of the R component for the secondary attribute prediction of the attribute residual, otherwise use the attribute residual reconstruction value of the G component for the secondary prediction of the attribute residual;

c) Set the initial cross-component attribute residual prediction value residualPrevComponent to an initial value of 0, and according to the attribute residual secondary prediction mode determined in step c), if the attribute residual reconstruction value of the G component is used to perform attribute residual secondary Prediction, then first perform the following operations on the G component;

d), using the attribute information of the G component, obtaining the attribute prediction value of the G component and the initial cross-component attribute residual prediction value through the nearest neighbor search to calculate the residual value of the G component;

delta=currValue[i]-predictor[i]-residualPrevComponent(i=R or G or B);

e) Quantize the residual value to obtain the attribute residual value of the G component, then perform entropy encoding, and write it into the code stream;

f) Dequantize the attribute residual value of the quantized G component to obtain the attribute residual reconstruction value recResidual[i] of the G component;

g), setting the second cross-component attribute residual prediction value as the G component attribute residual reconstruction value+0;

residualPrevComponent + = recResidual[i];

h), perform operations e), f), g), and h) on the next color component (the second color component to be predicted), until the processing of the three components of R, G, and B is completed.

It can be understood that since the adaptive selection of the prediction mode can be performed based on the degree of difference between the color components, when the second prediction of the color component of the current point is performed according to the prediction mode, the obtained color component The accuracy of attribute reconstruction values is high.

Based on the implementation basis of the foregoing embodiments, as shown in FIG. 12 , the embodiment of the present application provides a decoder 1, including:

The parsing part 10 is configured to parse the code stream, and determine the attribute residual value of the color component corresponding to the current point;

The first acquiring part 11 is configured to acquire the attribute prediction value of the color component corresponding to the current point;

The first determining part 12 is configured to determine the prediction mode of the color component of the current point; wherein, the prediction mode is determined based on the degree of difference between the color components;

The decoding part 13 is configured to decode and reconstruct the color component of the current point based on the prediction mode, the attribute residual value, the attribute prediction value and the initial cross-component attribute residual prediction value, to obtain the color component The property reconstruction value for .

In some embodiments of the present application, the parsing part 10 is further configured to parse out the prediction mode flag when parsing the code stream;

The first determining part 12 is further configured to determine the prediction mode of the color component of the current point according to the prediction mode flag bit.

In some embodiments of the present application, the first determining part 12 is further configured to determine the standard value of the color component corresponding to the current point based on the attribute prediction value; determine at least two color components corresponding to the current point A component, at least two degrees of difference from the standard value; based on the at least two degrees of difference, determine the prediction mode of the color component of the current point.

In some embodiments of the present application, the first determination part 12 is further configured to determine the minimum difference degree among the at least two difference degrees; determine the color component corresponding to the minimum difference degree as the predicted model.

In some embodiments of the present application, the first determining part 12 is further configured to determine a ranking result of the at least two degrees of difference; and determine the prediction mode according to the ranking result.

In some embodiments of the present application, the property prediction value includes: a first property prediction value of the first color component, a second property prediction value of the second color component, and a third property prediction value of the third color component;

The first determining part 12 is further configured as at least one of the following:

averaging the first attribute predicted value, the second attribute predicted value and the third attribute predicted value to determine the standard value;

determining the maximum value of the first attribute predicted value, the second attribute predicted value, and the third attribute predicted value as the standard value;

determining that the minimum of the first attribute predicted value, the second attribute predicted value, and the third attribute predicted value is the standard value;

Determining a median value of the first attribute prediction value, the second attribute prediction value, and the third attribute prediction value as the standard value.

In some embodiments of the present application, the prediction mode includes: a first color component to be predicted; the first color component to be predicted is the first color component among the first color component, the second color component and the third color component The color components of the codec.

In some embodiments of the present application, the decoding part 13 is further configured to determine the first color component of the first color component to be predicted based on the attribute residual value of the first color component to be predicted according to the prediction mode. attribute residual reconstruction value; wherein, the first color component to be predicted is the color component characterized by the prediction mode; based on the attribute prediction value, the first attribute residual reconstruction value and the initial span The component attribute residual prediction value decodes and reconstructs the color component of the current point to obtain the attribute reconstruction value of the color component.

In some embodiments of the present application, the decoding part 13 is further configured to dequantize the attribute residual value of the first color component to be predicted according to the prediction mode, and determine the first The first attribute residual reconstruction value of the color component to be predicted.

In some embodiments of the present application, the attribute reconstruction value includes: a first attribute reconstruction value, a second attribute reconstruction value and a third attribute reconstruction value;

The decoding part 13 is further configured to add the initial cross-component attribute residual prediction value to the attribute prediction value corresponding to the first color component to be predicted and the first attribute residual reconstruction value to obtain the said first attribute reconstruction value of the first color component to be predicted;

determining a second cross-component attribute residual prediction value based on the first attribute residual reconstruction value;

Based on the second cross-component attribute residual prediction value, decode and reconstruct the second to-be-predicted color component and the third to-be-predicted color component to obtain the second attribute reconstruction value and the third attribute Reconstruction value; the second color component to be predicted and the third color component to be predicted are the first color component, the second color component and the third color component except the first color component to be predicted other color components.

In some embodiments of the present application, the decoding part 13 is further configured to decode and reconstruct the second color component to be predicted based on the second cross-component attribute residual prediction value to obtain the second attribute reconstruction value;

determining a third cross-component attribute residual prediction value based on the second attribute residual reconstruction value;

Based on the third cross-component attribute residual prediction value, decode and reconstruct a third to-be-predicted color component to obtain the third attribute reconstruction value.

In some embodiments of the present application, the decoding part 13 is further configured to use the initial cross-component attribute residual prediction value, the attribute prediction value corresponding to the first color component to be predicted, and the first After adding the attribute residual reconstruction values to obtain the first attribute reconstruction value of the first to-be-predicted color component, determine the second cross-component attribute residual based on the first attribute residual reconstruction value The predicted value and the third cross-component attribute residual prediction value; based on the second cross-component attribute residual prediction value, the second color component to be predicted is decoded and reconstructed to obtain the second attribute reconstruction value; based on the The third cross-component attribute residual prediction value is described, and the third color component to be predicted is decoded and reconstructed to obtain the third attribute reconstruction value.

In some embodiments of the present application, the second cross-component attribute residual prediction value is the sum of the first cross-component attribute residual reconstruction value and the initial cross-component attribute residual prediction value, or, The multiple or divisor of the reconstruction value for the first attribute residual.

In some embodiments of the present application, the third cross-component attribute residual prediction value is the sum of the second attribute residual reconstruction value and the second cross-component attribute residual prediction value, or , the multiple or divisor of the reconstruction value for the second attribute residual.

In some embodiments of the present application, the third cross-component attribute residual prediction value is the sum of the first cross-component attribute residual reconstruction value and the initial cross-component attribute residual prediction value, or, The multiple or divisor of the reconstruction value for the first attribute residual.

In the actual application of this application, as shown in Figure 13, the embodiment of this application also provides a decoder, including:

a first memory 14 and a first processor 15;

The first memory 14 stores a computer program that can run on the first processor 15, and the first processor 15 implements a decoding method corresponding to the decoder when executing the program.

Wherein, the first processor 15 can be implemented by software, hardware, firmware or a combination thereof, and can use circuits, single or multiple application specific integrated circuits (ASIC), single or multiple general integrated circuits, single or multiple a microprocessor, a single or multiple programmable logic devices, or a combination of the aforementioned circuits or devices, or other suitable circuits or devices, so that the first processor 15 can perform the decoding on the decoder side in the aforementioned embodiments corresponding steps of the method.

The embodiment of the present application provides an encoder 2, as shown in Figure 14, including:

The second acquiring part 20 is configured to acquire the attribute prediction value of the color component corresponding to the current point in the point cloud;

The second determining part 21 is configured to determine the standard value of the color component corresponding to the current point based on the attribute prediction value; determine the difference between the at least two color components corresponding to the current point and the standard value at least two degrees of difference; based on the at least two degrees of difference, determining a prediction mode of the color component;

The prediction part 22 is configured to perform secondary prediction on the color component of the current point based on the prediction mode, the attribute prediction value and the initial cross-component attribute residual prediction value to obtain the attribute residual value of the color component.

The second determining part 21 is further configured as at least one of the following:

In some embodiments of the present application, the prediction part 22 is further configured to determine the initial attribute residual reconstruction value corresponding to the current point based on the attribute prediction value and the attribute information of the current point; based on the initial attribute residual The difference reconstruction value determines the standard value of the color component corresponding to the current point.

In some embodiments of the present application, the prediction part 22 is further configured to determine an initial residual value corresponding to the current point based on the predicted attribute value and the attribute information of the current point; Quantization and inverse quantization to obtain the residual reconstruction value of the initial attribute.

In some embodiments of the present application, the initial attribute residual reconstruction value includes: the first initial attribute residual reconstruction value of the first color component, the second initial attribute residual reconstruction value of the second color component, and the third color The residual reconstruction value of the third attribute of the component's initial attribute;

averaging the first initial attribute residual reconstruction value, the second initial attribute residual reconstruction value and the third initial attribute residual reconstruction value to determine the standard value;

determining the maximum value of the first initial attribute residual reconstruction value, the second initial attribute residual reconstruction value, and the third initial attribute residual reconstruction value as the standard value;

determining that the minimum of the first initial attribute residual reconstruction value, the second initial attribute residual reconstruction value, and the third initial attribute residual reconstruction value is the standard value;

Determine the standard value as the median of the first initial attribute residual reconstruction value, the second initial attribute residual reconstruction value, and the third initial attribute residual reconstruction value.

In some embodiments of the present application, the encoder 2 further includes: a writing part 23;

The prediction part 22 is further configured to generate a prediction mode flag; the prediction mode flag represents the prediction mode;

The writing part 23 is further configured to write the prediction mode flag bit into the code stream.

In some embodiments of the present application, the second determining part 21 is further configured to determine the minimum difference degree among the at least two difference degrees; determine the color component corresponding to the minimum difference degree as the predicted model.

In some embodiments of the present application, the second determining part 21 is further configured to determine a ranking result of the at least two degrees of difference; and determine the prediction mode according to the ranking result.

In some embodiments of the present application, the prediction part 22 is further configured to predict the first property information of the first color component to be predicted and the property prediction of the first color component to be predicted according to the prediction mode Value and the initial cross-component attribute residual prediction value are sequentially subtracted and then quantized to realize secondary prediction, and obtain the attribute residual value of the first color component to be predicted; the prediction mode includes: the first color component to be predicted ; The first color component to be predicted is the first coded color component among the first color component, the second color component and the third color component;

After dequantizing the attribute residual value of the first color component to be predicted, the first attribute residual reconstruction value of the first color component to be predicted is obtained; based on the first attribute residual reconstruction value, determine the second cross-component attribute residual prediction value; based on the second cross-component attribute residual prediction value, perform secondary prediction on other color components, and obtain the second attribute residual value of the color component to be predicted and the attribute residual value of the third color component to be predicted; the second color component to be predicted and the third color component to be predicted are the first color component, the second color component and the third color component Other color components in excluding the first color component to be predicted.

In some embodiments of the present application, the prediction part 22 is further configured to perform secondary prediction on the second color component to be predicted based on the second cross-component attribute residual prediction value to obtain the second The attribute residual value of the color component to be predicted;

After dequantizing the attribute residual value of the second color component to be predicted, the second attribute residual reconstruction value of the second color component to be predicted is obtained;

Based on the third cross-component attribute residual prediction value, a second prediction is performed on the third to-be-predicted color component to obtain an attribute residual value of the third to-be-predicted color component.

In some embodiments of the present application, the prediction part 22 is further configured to obtain the first color to be predicted after dequantizing the attribute residual value of the first color component to be predicted. After the first attribute residual reconstruction value of the component, based on the first attribute residual reconstruction value, the second cross-component attribute residual prediction value and the third cross-component attribute residual prediction value are determined; based on the The second cross-component attribute residual prediction value performs secondary prediction on the second to-be-predicted color component to obtain the attribute residual value of the second to-be-predicted color component; based on the third cross-component attribute residual prediction value, perform secondary prediction on the third color component to be predicted, and obtain the attribute residual value of the third color component to be predicted.

The writing part 23 is further configured to write the property residual value of the color component into the code stream.

In some embodiments of the present application, the attribute residual value of the color component includes: the attribute residual value of the first color component to be predicted, the attribute residual value of the second color component to be predicted, and the Describe the attribute residual value of the third color component to be predicted.

In practical applications, as shown in Figure 15, the embodiment of the present application also provides an encoder, including:

a second memory 25 and a second processor 24;

The second memory 25 stores a computer program that can run on the second processor 24, and the second processor 24 executes the encoding method corresponding to the encoder when executing the program.

The embodiment of the present application provides a storage medium on which a computer program is stored. When the computer program is executed by the first processor, the decoding method corresponding to the claim decoder is realized; or, the computer program is processed by the second processor. When the encoder is executed, the encoding method corresponding to the encoder of the claim is realized.

Each component in the embodiment of the present application may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of 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 or It is said that the part that contributes to the prior art or the whole 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 several instructions to make a computer device (which can It is a personal computer, a server, or a network device, etc.) or a processor (processor) that executes all or part of the steps of the method described in this embodiment. The aforementioned storage medium includes: magnetic random access memory (FRAM, ferromagnetic random access memory), read-only memory (ROM, Read Only Memory), programmable read-only memory (PROM, Programmable Read-Only Memory), erasable Programmable Read-Only Memory (EPROM, Erasable Programmable Read-Only Memory), Electrically Erasable Programmable Read-Only Memory (EEPROM, Electrically Erasable Programmable Read-Only Memory), Flash Memory (Flash Memory), Magnetic Surface Memory, Optical Disk , or compact disc read-only memory (CD-ROM, Compact Disc Read-Only Memory) and other media that can store program codes, the embodiments of the present disclosure are not limited.

The above is only the embodiment of the present application, but the scope of protection of the present application is not limited thereto. Anyone familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, and should covered within the scope of protection of this application. Therefore, the protection scope of the present application should be determined by the protection scope of the claims.

Industrial Applicability

Claims

A decoding method, applied to a decoder, comprising:

Analyze the code stream to determine the attribute residual value of the color component corresponding to the current point;

Acquiring the attribute prediction value of the color component corresponding to the current point;

Determine the prediction mode of the color component of the current point; wherein, the prediction mode is determined based on the degree of difference between the color components;

Based on the prediction mode, the attribute residual value, the attribute prediction value and the initial cross-component attribute residual prediction value, decode and reconstruct the color component of the current point to obtain the attribute reconstruction value of the color component.
The method according to claim 1, wherein said determining the prediction mode of the color component of the current point comprises:

When parsing the code stream, parse out the prediction mode flag;

Determine the prediction mode of the color component of the current point according to the prediction mode flag bit.
The method according to claim 1, wherein said determining the prediction mode of the color component of the current point comprises:

Determine a standard value of the color component corresponding to the current point based on the attribute prediction value;

determining at least two degrees of difference between at least two color components corresponding to the current point and the standard value;

Based on the at least two degrees of difference, the prediction mode of the color component of the current point is determined.
The method according to claim 3, wherein the determining the prediction mode of the color component based on the at least two degrees of difference comprises:

determining a minimum degree of difference of the at least two degrees of difference;

The color component corresponding to the minimum degree of difference is determined as the prediction mode.
The method according to claim 3, wherein the determining the prediction mode of the color component based on the at least two degrees of difference comprises:

determining a ranking result of the at least two degrees of difference;

According to the ranking result, the prediction mode is determined.
The method according to any one of claims 3 to 5, wherein the property prediction value comprises: a first property prediction value of the first color component, a second property prediction value of the second color component and a third color component The predicted value of the third attribute;

The determining the standard value of the color component corresponding to the current point based on the attribute prediction value includes at least one of the following:

averaging the first attribute predicted value, the second attribute predicted value and the third attribute predicted value to determine the standard value;

determining the maximum value of the first attribute predicted value, the second attribute predicted value, and the third attribute predicted value as the standard value;

determining that the minimum of the first attribute predicted value, the second attribute predicted value, and the third attribute predicted value is the standard value;

Determining a median value of the first attribute prediction value, the second attribute prediction value, and the third attribute prediction value as the standard value.
The method according to any one of claims 1-5, wherein,

The prediction mode includes: a first color component to be predicted; the first color component to be predicted is the first coded color component among the first color component, the second color component and the third color component.
The method according to any one of claims 1-7, wherein the current The color component of the point is decoded and reconstructed to obtain the attribute reconstruction value of the color component, including:

According to the prediction mode, based on the attribute residual value of the first color component to be predicted, the first attribute residual reconstruction value of the first color component to be predicted is determined; wherein, the first color component to be predicted is a color component characterized by the prediction mode;

Decoding and reconstructing the color component of the current point based on the attribute prediction value, the first attribute residual reconstruction value and the initial cross-component attribute residual prediction value, to obtain the attribute reconstruction value of the color component.
The method according to claim 8, wherein, according to the prediction mode, based on the attribute residual value of the first color component to be predicted, the first reconstructed value of the attribute residual of the first color component to be predicted is determined ,include:

According to the prediction mode, inverse quantization is performed on the attribute residual value of the first to-be-predicted color component, and the first reconstructed attribute value of the first to-be-predicted color component is determined.
The method according to claim 8 or 9, wherein the attribute reconstruction value comprises: a first attribute reconstruction value, a second attribute reconstruction value and a third attribute reconstruction value;

Decoding and reconstructing the color component of the current point based on the attribute prediction value, the first attribute residual reconstruction value and the initial cross-component attribute residual prediction value, to obtain the attribute reconstruction of the color component values, including:

Adding the initial cross-component attribute residual prediction value, the attribute prediction value corresponding to the first color component to be predicted, and the first attribute residual reconstruction value to obtain the first color component to be predicted The first attribute rebuilds the value;

determining a second cross-component attribute residual prediction value based on the first attribute residual reconstruction value;

Based on the second cross-component attribute residual prediction value, decode and reconstruct the second to-be-predicted color component and the third to-be-predicted color component to obtain the second attribute reconstruction value and the third attribute Reconstruction value; the second color component to be predicted and the third color component to be predicted are the first color component, the second color component and the third color component except the first color component to be predicted other color components.
The method according to claim 10, wherein, based on the second cross-component attribute residual prediction value, decode and reconstruct other color components to obtain the second attribute reconstruction value and the third Attribute reconstruction values, including:

Decoding and reconstructing a second to-be-predicted color component based on the second cross-component attribute residual prediction value to obtain the second attribute reconstruction value;

determining a third cross-component attribute residual prediction value based on the second attribute residual reconstruction value;

Based on the third cross-component attribute residual prediction value, decode and reconstruct a third to-be-predicted color component to obtain the third attribute reconstruction value.
The method according to claim 10, wherein said adding the initial cross-component attribute residual prediction value to the attribute prediction value corresponding to the first color component to be predicted and the first attribute residual reconstruction value, After obtaining the first attribute reconstruction value of the first color component to be predicted, the method further includes:

determining a second cross-component attribute residual prediction value and a third cross-component attribute residual prediction value based on the first attribute residual reconstruction value;

Based on the second cross-component attribute residual prediction value, decode and reconstruct the second color component to be predicted to obtain a second attribute reconstruction value;

Based on the third cross-component attribute residual prediction value, the third to-be-predicted color component is decoded and reconstructed to obtain a third attribute reconstruction value.
A method according to any one of claims 10 to 12, wherein,

The second cross-component attribute residual prediction value is the sum of the first attribute residual reconstruction value and the initial cross-component attribute residual prediction value, or is the first attribute residual The multiple or divisor of the reconstruction value.
The method of claim 11, wherein,

The third cross-component attribute residual prediction value is the sum of the second attribute residual reconstruction value and the second cross-component attribute residual prediction value, or is the second attribute residual Multiplier or divisor of the difference reconstruction value.
The method of claim 12, wherein,

The third cross-component attribute residual prediction value is the sum of the first attribute residual reconstruction value and the initial cross-component attribute residual prediction value, or is the first attribute residual The multiple or divisor of the reconstruction value.
An encoding method, applied to an encoder, comprising:

Get the attribute prediction value of the color component corresponding to the current point in the point cloud;

Based on the attribute prediction value, determine a standard value of the color component corresponding to the current point;

determining at least two degrees of difference between at least two color components corresponding to the current point and the standard value;

determining a prediction mode for the color component based on the at least two degrees of difference;

Based on the prediction mode, the attribute prediction value and the initial cross-component attribute residual prediction value, the color component of the current point is predicted twice to obtain the attribute residual value of the color component.
The method according to claim 16, wherein the property prediction value comprises: a first property prediction value of the first color component, a second property prediction value of the second color component, and a third property prediction value of the third color component ;

The determining the standard value of the color component corresponding to the current point based on the attribute prediction value includes at least one of the following:

averaging the first attribute predicted value, the second attribute predicted value and the third attribute predicted value to determine the standard value;

determining the maximum value of the first attribute predicted value, the second attribute predicted value, and the third attribute predicted value as the standard value;

determining that the minimum of the first attribute predicted value, the second attribute predicted value, and the third attribute predicted value is the standard value;

Determining a median value of the first attribute prediction value, the second attribute prediction value, and the third attribute prediction value as the standard value.
The method according to claim 16, wherein said determining the standard value of the color component corresponding to the current point based on the attribute prediction value comprises:

Based on the attribute prediction value and the attribute information of the current point, determine the initial attribute residual reconstruction value corresponding to the current point;

Based on the initial attribute residual reconstruction value, determine a standard value of the color component corresponding to the current point.
The method according to claim 18, wherein said determining the initial attribute residual reconstruction value corresponding to the current point based on the attribute prediction value and the attribute information of the current point comprises:

Determining an initial residual value corresponding to the current point based on the attribute prediction value and the attribute information of the current point;

Quantization and inverse quantization are performed on the initial residual value to obtain the residual reconstruction value of the initial attribute.
The method according to claim 17 or 18, wherein the initial attribute residual reconstruction value comprises: a first initial attribute residual reconstruction value of the first color component, a second initial attribute residual reconstruction value of the second color component and the third initial attribute residual reconstruction value of the third color component;

The determining the standard value of the color component corresponding to the current point based on the reconstruction value of the initial attribute residual includes at least one of the following:

averaging the first initial attribute residual reconstruction value, the second initial attribute residual reconstruction value and the third initial attribute residual reconstruction value to determine the standard value;

determining the maximum value of the first initial attribute residual reconstruction value, the second initial attribute residual reconstruction value, and the third initial attribute residual reconstruction value as the standard value;

determining that the minimum of the first initial attribute residual reconstruction value, the second initial attribute residual reconstruction value, and the third initial attribute residual reconstruction value is the standard value;

Determine the standard value as the median of the first initial attribute residual reconstruction value, the second initial attribute residual reconstruction value, and the third initial attribute residual reconstruction value.
The method according to any one of claims 18-20, wherein, when determining the prediction mode of the color component based on the at least two degrees of difference, the method further comprises:

Generate a prediction mode flag and write it into the code stream; the prediction mode flag represents the prediction mode.
The method according to claim 16, wherein said determining said prediction mode of a color component based on said at least two degrees of difference comprises:

determining a minimum degree of difference of the at least two degrees of difference;

The color component corresponding to the minimum degree of difference is determined as the prediction mode.
The method according to claim 16, wherein said determining said prediction mode of a color component based on said at least two degrees of difference comprises:

determining a ranking result of the at least two degrees of difference;

According to the ranking result, the prediction mode is determined.
The method according to any one of claims 16 to 23, wherein, based on the prediction mode, the attribute prediction value and the initial cross-component attribute residual prediction value, the color component of the current point is twice Prediction, get the attribute residual value of the color component, including:

According to the prediction mode, the first attribute information of the first color component to be predicted, the attribute prediction value of the first color component to be predicted and the initial cross-component attribute residual prediction value are sequentially subtracted and then quantized to realize The second prediction is to obtain the attribute residual value of the first color component to be predicted; the prediction mode includes: the first color component to be predicted; the first color component to be predicted is the first color component, the second color The first coded color component among the color component and the third color component;

After dequantizing the attribute residual value of the first color component to be predicted, the first attribute residual reconstruction value of the first color component to be predicted is obtained;

determining a second cross-component attribute residual prediction value based on the first attribute residual reconstruction value;

Based on the second cross-component attribute residual prediction value, perform secondary prediction on other color components to obtain the attribute residual value of the second to-be-predicted color component and the attribute residual value of the third to-be-predicted color component; The second color component to be predicted and the third color component to be predicted are the first color component, the second color component and the third color component except the first color component to be predicted Additional color components.
The method according to claim 24, wherein, based on the second cross-component attribute residual prediction value, the second prediction is performed on other color components to obtain the attribute residual value and the second color component to be predicted. The attribute residual value of the third color component to be predicted, including:

Based on the second cross-component attribute residual prediction value, performing secondary prediction on the second to-be-predicted color component to obtain the attribute residual value of the second to-be-predicted color component;

After dequantizing the attribute residual value of the second color component to be predicted, the second attribute residual reconstruction value of the second color component to be predicted is obtained;

determining a third cross-component attribute residual prediction value based on the second attribute residual reconstruction value;

Based on the third cross-component attribute residual prediction value, a second prediction is performed on the third to-be-predicted color component to obtain an attribute residual value of the third to-be-predicted color component.
The method according to claim 24, wherein after dequantizing the attribute residual value of the first color component to be predicted, the first attribute residual value of the first color component to be predicted is obtained After reconstructing the values, the method also includes:

determining a second cross-component attribute residual prediction value and a third cross-component attribute residual prediction value based on the first attribute residual reconstruction value;

Based on the second cross-component attribute residual prediction value, performing secondary prediction on the second to-be-predicted color component to obtain the attribute residual value of the second to-be-predicted color component;

Based on the third cross-component attribute residual prediction value, a second prediction is performed on the third to-be-predicted color component to obtain an attribute residual value of the third to-be-predicted color component.
A method according to any one of claims 24 to 26, wherein,

The second cross-component attribute residual prediction value is the sum of the first attribute residual reconstruction value and the initial cross-component attribute residual prediction value, or is the first attribute residual The multiple or divisor of the reconstruction value.
The method of claim 25, wherein,

The third cross-component attribute residual prediction value is the sum of the second attribute residual reconstruction value and the second cross-component attribute residual prediction value, or is the second attribute residual Multiplier or divisor of the difference reconstruction value.
The method of claim 26, wherein,

The third cross-component attribute residual prediction value is the sum of the first attribute residual reconstruction value and the initial cross-component attribute residual prediction value, or is the first attribute residual The multiple or divisor of the reconstruction value.
The method according to claim 20, wherein said method further comprises:

Write the attribute residual value of the color component into the code stream.
A method according to any one of claims 24 to 26, wherein,

The property residual value of the color component includes: the property residual value of the first color component to be predicted, the property residual value of the second color component to be predicted, and the property residual value of the third color component to be predicted Attribute residual value.
A decoder comprising:

The parsing part is configured to parse the code stream and determine the attribute residual value of the color component corresponding to the current point;

The first acquisition part is configured to acquire the attribute prediction value of the color component corresponding to the current point;

The first determining part is configured to determine a prediction mode of the color component of the current point; wherein the prediction mode is determined based on the degree of difference between the color components;

The decoding part is configured to decode and reconstruct the color component of the current point based on the prediction mode, the attribute residual value, the attribute prediction value and the initial cross-component attribute residual prediction value, to obtain the color component Property reconstruction value.
An encoder comprising:

The second acquisition part is configured to acquire the attribute prediction value of the color component corresponding to the current point in the point cloud;

The second determination part is configured to determine a standard value of the color component corresponding to the current point based on the attribute prediction value; determine at least two color components corresponding to the current point, and at least the standard value two degrees of difference; based on the at least two degrees of difference, determining a prediction mode of the color component;

The prediction part is configured to perform secondary prediction on the color component of the current point based on the prediction mode, the attribute prediction value and the initial cross-component attribute residual prediction value, to obtain the attribute residual value of the color component.
A decoder comprising:

a first memory and a first processor;

The first memory stores a computer program that can run on the first processor, and the first processor implements the method according to any one of claims 1 to 15 when executing the program.
An encoder comprising:

a second memory and a second processor;

The second memory stores a computer program executable on the second processor, and the second processor implements the method according to any one of claims 16 to 31 when executing the program.
A storage medium, on which a computer program is stored. When the computer program is executed by the first processor, the method according to any one of claims 1 to 15 is realized; or, when the computer program is executed by the second processor, Implementing the method of any one of claims 16 to 31.