A run-length encoding method for adaptive compression of point cloud color attributes

Abstract

This invention discloses a method for adaptively compressing run-length encoding of point cloud color attributes, comprising: converting point cloud attributes from RGB color space to YUV color space; performing Hilbert reordering on the point cloud data, performing differential prediction under the Hilbert order, and obtaining prediction residuals; quantizing the prediction residuals to obtain prediction quantization residuals; and entropy encoding the prediction quantization residuals using a color attribute adaptively compressing run-length encoding method to obtain an attribute code stream. This invention can further compress point cloud data attribute information and is widely applicable to the field of image processing technology.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to a point cloud color attribute adaptive compression run-length encoding method. Background Art

[0002] At present, under the framework of the AVS-PCC (Point Cloud Compression of Audio Video coding Standard) point cloud compression algorithm based on geometry in domestic audio and video coding, the geometric position of the point cloud is first processed in the encoder and decoder, and the attribute information is processed based on the decoded geometric position. The compression process of point cloud attribute information in the AVS-PCC framework is roughly as follows. Since the geometric position of the point cloud is reconstructed through coordinate translation, quantization and octree, it is necessary to perform attribute interpolation and recoloring operations on each point in the point cloud. In order to further compress the data, the differential prediction method is used to predict the attribute information of the current point through several previous points, thereby obtaining the attribute prediction residual. The prediction residual is then quantized and finally entropy coding is performed.

[0003] Run-length coding is a relatively simple encoding technique. Its main idea is to replace a continuous string of identical values ​​with a single representative value and the string length. For example, the string "aaabccddddd" can be represented as "3a1b2c5d" after run-length coding. For image coding, a run is defined as a sequence of adjacent pixels with the same grayscale value along a specific direction. The length of this run is called the run, or simply a run.

[0004] In the latest PCRM framework, run-length encoding is used for color attribute prediction residuals (0, 0, 0). Zero color attribute prediction residuals Res are run-length encoded. If the attribute prediction residual Res is non-zero, the run_length value is first encoded, then the non-zero attribute prediction residual is encoded, and finally the run_length value is set to 0 and counted again.

[0005] For each component Res of the non-zero attribute prediction residual Res i (i=0,1,2) are encoded in sequence, and the encoding method is:

[0006] When the attribute information to be encoded is color, the attribute residual component Res is firstly coded using the context. i Whether to perform arithmetic coding when it is 0. i When it is not 0, bypass coding is used for its symbol; the attribute residual component Res is coded using the context. i Whether the absolute value is equal to 1 is arithmetic coding; in the attribute residual component Resi When the absolute value is greater than 1, the attribute residual component Res is calculated using the context i Whether the absolute value is equal to 2 is arithmetic coding;

[0007] In the attribute residual component Res i When the absolute value is greater than 2, the context pair (Res i When the attribute information is reflectivity, 3rd-order EGG is used, and when the attribute information is color, 1st-order EGG is used.

[0008] The correlation between the residual coefficients of color attribute prediction is further compressed by using context coding for entropy coding. The specific method is as follows:

[0009] 1. Use fixed context to encode a flag bit to represent whether Y / R is equal to 0,

[0010] 2. If Y / R is equal to 0, continue to use the fixed context to encode a flag bit to indicate whether U / G is equal to 0;

[0011] 1) If U / G and Y / R are both equal to 0, use the fixed context to encode the absolute value of V / B minus 1 and encode its sign;

[0012] 2) If Y / R is equal to 0 but U / G is not equal to 0, use the fixed context to encode the absolute value of U / G minus 1 and its sign, and continue to use the fixed context to encode V / B and its sign;

[0013] 3. If Y / R is not equal to 0, use the fixed context to encode the absolute value of Y / R minus 1 and encode its sign, continue to use the fixed context to encode U / G and its sign; continue to use the fixed context to encode V / B and its sign.

[0014] There are currently four test conditions (C1-C4) used to verify the compression effectiveness of the algorithm. C1: Limited lossy geometry and lossy attributes; C2: Lossless geometry and lossy attributes; C3: Lossless geometry and limited lossy attributes; C4: Lossless geometry and lossless attributes.

[0015] With the exception of condition C4, test conditions C1-C3 all have different attribute quantization step sizes. Statistical analysis of the color attribute prediction residuals under different attribute quantization step sizes was performed. It was found that with larger quantization step sizes, the proportion of run-length encoding in the color attribute entropy coding was significantly greater than that of non-zero data. Summary of the Invention

[0016] In view of this, an embodiment of the present invention provides a point cloud color attribute adaptive compression run length encoding method to further compress point cloud data attribute information.

[0017] One aspect of the present invention provides a method for adaptively compressing run-length encoding of point cloud color attributes, comprising:

[0018] Convert point cloud attributes from RGB color space to YUV color space;

[0019] Perform Hilbert reordering on the point cloud data, perform differential prediction under the Hilbert order, and obtain the prediction residual;

[0020] quantizing the prediction residual to obtain a prediction quantized residual;

[0021] The predicted quantization residual is entropy-coded by using a color attribute adaptive compression run length coding method to obtain an attribute code stream.

[0022] Optionally, the method further includes:

[0023] According to the changes in geometric information, when the operation of removing duplicate points is performed in the geometric encoding, the attribute interpolation operation is performed.

[0024] Optionally, the entropy coding of the predicted quantization residual using a color attribute adaptive compression run length coding method to obtain an attribute code stream includes:

[0025] Configure the adaptive threshold according to the attribute quantization step parameter;

[0026] Traverse the attribute prediction quantization residual of each point and count the first point where the continuous attribute prediction quantization residual value is 0;

[0027] Directly encoding a run length encoding value or using compressed run length encoding according to the first point number;

[0028] When the attribute prediction quantization residual is non-zero, the value of the first point is encoded, the value of the first point is set to 0 and counting is restarted, and then the non-zero attribute prediction quantization residual is encoded.

[0029] Optionally, using compressed run length encoding according to the first point number comprises the following steps:

[0030] Divide the first point number by 2 and round it down to obtain a second point number, and finally encode the second point number;

[0031] A fixed context code is added. If the first point number is divided by 2 and the remainder is 1, the fixed context code is 1; if the first point number is divided by 2 and the remainder is 0, the fixed context code is 0.

[0032] Optionally, encoding the non-zero attribute prediction quantization residual comprises the following steps:

[0033] Use fixed context encoding to determine whether the first flag bit is equal to 0.

[0034] If the first flag bit represents equal to 0, continue to use the fixed context to encode whether the second flag bit represents equal to 0;

[0035] If the second flag bit representative and the first flag bit representative are both equal to 0, using the absolute value of the fixed context code minus 1, and encoding the fixed context code symbol;

[0036] If the first flag bit represents a value equal to 0 but the second flag bit represents a value not equal to 0, subtract 1 from the absolute value of the fixed context encoding;

[0037] If the first flag bit represents not equal to 0, use the fixed context to encode the absolute value of the first flag bit representative minus 1, and encode the symbol represented by the first flag bit, and continue to use the fixed context to encode the second flag bit representative and the symbol represented by the second flag bit.

[0038] Optionally, the method further includes:

[0039] The attribute stream is entropy decoded using the color attribute adaptive compression run decoding method to obtain the attribute prediction quantization residual;

[0040] Inverse quantize the attribute prediction quantization residual to obtain the attribute prediction residual;

[0041] The attribute prediction of the points in the reconstructed point cloud is performed by the residual prediction method, and finally the attribute prediction residual corresponding to the point is added to obtain the attribute of the point in the point cloud;

[0042] Convert point cloud attributes from YUV color space to RGB color space.

[0043] Optionally, the method further includes:

[0044] Configuring an adaptive threshold according to the attribute quantization step size, wherein the adaptive threshold is used to determine whether to use compressed run decoding;

[0045] Decode zero attribute prediction quantization residual and run length coding;

[0046] Decode the non-zero attribute prediction quantization residual Res to obtain the non-zero attribute prediction quantization residual of the current point.

[0047] Optionally, decoding the zero attribute prediction quantization residual and decoding the run length coding includes:

[0048] If compressed run-length encoding is not used, the run-length encoding value is decoded directly;

[0049] If compressed run-length code decoding is used, the run-length code half value is decoded first, and then the fixed context is decoded. The fixed context takes the value 0 or 1 to obtain the run-length code value.

[0050] The present invention also discloses a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform the above method.

[0051] The embodiments of the present invention convert point cloud attributes from RGB color space to YUV color space; perform Hilbert reordering on the point cloud data, perform differential prediction under the Hilbert order, and obtain prediction residuals; quantize the prediction residuals to obtain prediction quantization residuals; and entropy encode the prediction quantization residuals using a color attribute adaptive compression run-length coding method to obtain an attribute code stream. The present invention can further compress point cloud data attribute information. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0053] Figure 1 An overall block diagram of the PCRM encoder and decoder provided in an embodiment of the present invention;

[0054] Figure 2 A flow chart of color attribute adaptive compression run-length coding provided by an embodiment of the present invention;

[0055] Figure 3 This is a flowchart of color attribute adaptive compression run-length code decoding provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solutions and advantages of this application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0057] In view of the problems existing in the prior art, one aspect of the present invention provides a point cloud color attribute adaptive compression run-length encoding method, comprising:

[0058] Convert point cloud attributes from RGB color space to YUV color space;

[0059] Perform Hilbert reordering on the point cloud data, perform differential prediction under the Hilbert order, and obtain the prediction residual;

[0060] quantizing the prediction residual to obtain a prediction quantized residual;

[0061] The predicted quantization residual is entropy-coded by using a color attribute adaptive compression run length coding method to obtain an attribute code stream.

[0062] Optionally, the method further includes:

[0063] According to the changes in geometric information, when the operation of removing duplicate points is performed in the geometric encoding, the attribute interpolation operation is performed.

[0064] Optionally, the entropy coding of the predicted quantization residual using a color attribute adaptive compression run length coding method to obtain an attribute code stream includes:

[0065] Configure the adaptive threshold according to the attribute quantization step parameter;

[0066] Traverse the attribute prediction quantization residual of each point and count the first point where the continuous attribute prediction quantization residual value is 0;

[0067] Directly encoding a run length encoding value or using compressed run length encoding according to the first point number;

[0068] When the attribute prediction quantization residual is non-zero, the value of the first point is encoded, the value of the first point is set to 0 and counting is restarted, and then the non-zero attribute prediction quantization residual is encoded.

[0069] Optionally, using compressed run length encoding according to the first point number comprises the following steps:

[0070] Divide the first point number by 2 and round it down to obtain a second point number, and finally encode the second point number;

[0071] A fixed context code is added. If the first point number is divided by 2 and the remainder is 1, the fixed context code is 1; if the first point number is divided by 2 and the remainder is 0, the fixed context code is 0.

[0072] Optionally, encoding the non-zero attribute prediction quantization residual comprises the following steps:

[0073] Use fixed context encoding to determine whether the first flag bit is equal to 0.

[0074] If the first flag bit represents equal to 0, continue to use the fixed context to encode whether the second flag bit represents equal to 0;

[0075] If the second flag bit representative and the first flag bit representative are both equal to 0, using the absolute value of the fixed context code minus 1, and encoding the fixed context code symbol;

[0076] If the first flag bit represents a value equal to 0 but the second flag bit represents a value not equal to 0, subtract 1 from the absolute value of the fixed context encoding;

[0077] If the first flag bit represents not equal to 0, use the fixed context to encode the absolute value of the first flag bit representative minus 1, and encode the symbol represented by the first flag bit, and continue to use the fixed context to encode the second flag bit representative and the symbol represented by the second flag bit.

[0078] Optionally, the method further includes:

[0079] The attribute stream is entropy decoded using the color attribute adaptive compression run decoding method to obtain the attribute prediction quantization residual;

[0080] Inverse quantize the attribute prediction quantization residual to obtain the attribute prediction residual;

[0081] The attribute prediction of the points in the reconstructed point cloud is performed by the residual prediction method, and finally the attribute prediction residual corresponding to the point is added to obtain the attribute of the point in the point cloud;

[0082] Convert point cloud attributes from YUV color space to RGB color space.

[0083] Optionally, the method further includes:

[0084] Configuring an adaptive threshold according to the attribute quantization step size, wherein the adaptive threshold is used to determine whether to use compressed run decoding;

[0085] Decode zero attribute prediction quantization residual and run length coding;

[0086] Decode the non-zero attribute prediction quantization residual Res to obtain the non-zero attribute prediction quantization residual of the current point.

[0087] Optionally, decoding the zero attribute prediction quantization residual and decoding the run length coding includes:

[0088] If compressed run-length encoding is not used, the run-length encoding value is decoded directly;

[0089] If compressed run-length code decoding is used, the run-length code half value is decoded first, and then the fixed context is decoded. The fixed context takes the value 0 or 1 to obtain the run-length code value.

[0090] The present invention also discloses a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform the above method.

[0091] The specific implementation principle of the present invention is described in detail below with reference to the accompanying drawings:

[0092] The present invention Figure 1 The logical relationship between each module is presented. In the encoder and decoder, the point cloud geometric position is first processed, and the attribute information is processed based on the decoded geometric position.

[0093] Specifically, the attribute information encoding in the present invention includes the following five parts:

[0094] 1. Space transformation: convert the point cloud attributes from RGB color space to YUV color space.

[0095] 2. Attribute interpolation: Attribute interpolation, i.e. recoloring, is required only when the geometric information (number of points or relative positions of points) has changed, such as when duplicate points are removed in the geometric encoding.

[0096] 3. Attribute prediction: For attribute prediction, the point cloud is first Hilbert reordered. Differential prediction is performed under the Hilbert order to obtain the prediction residual.

[0097] 4. Residual quantization: quantize the prediction residual to obtain the prediction quantized residual.

[0098] 5. Entropy coding: Entropy coding is performed on the predicted quantized residual to obtain an attribute bit stream. The entropy coding method adopts the color attribute adaptive compression run length coding method.

[0099] In addition, the attribute information decoding of the present invention includes four parts:

[0100] 1. Entropy decoding. Perform entropy decoding on the attribute bitstream to obtain the attribute prediction quantization residual. The entropy decoding method uses the color attribute adaptive compression run-length decoding method.

[0101] 2. Inverse quantization: Inverse quantize the attribute prediction quantization residual to obtain the attribute prediction residual.

[0102] 3. Attribute reconstruction: Attributes of points in the reconstructed point cloud are predicted using the residual prediction method. Finally, the attribute prediction residual of the point is added to obtain the attribute of the point in the point cloud.

[0103] 4. Inverse space transformation: Convert point cloud attributes from YUV color space to RGB color space.

[0104] For the color attribute adaptive compression run length coding method, the following describes in detail the specific steps of the prediction attribute quantization residual coding end, such as Figure 2 As shown, the specific steps include the following steps 1-4:

[0105] 1. Set the adaptive threshold based on the attribute quantization step size parameter. Based on experimental experience, set the threshold to 35 and adaptively select whether to use compressed run length encoding.

[0106] 2. Traverse the attribute prediction quantization residual Res of each point and count the number of points run_length where the continuous attribute prediction quantization residual value is 0;

[0107] 3. If compressed run length encoding is not used, directly encode the run length encoding value run_length. If compressed run length encoding is used, perform the following steps 3-1 and 3-2:

[0108] 3-1. Divide run_length by 2 and round down to get run_length_half, and finally encode run_length_half.

[0109] 3-2. Add a fixed context code. If the remainder after run_length is divided by 2 is 1, the fixed context code is 1; if the remainder after run_length is divided by 2 is 0, the fixed context code is 0;

[0110] 4. If the attribute prediction quantization residual Res is non-zero, the run_length value is first encoded, and the run_length value is set to 0 and counted again. Then the non-zero attribute prediction quantization residual encoding module is entered.

[0111] The non-zero attribute prediction quantization residual is encoded, specifically including the following steps 4-1 to 4-3:

[0112] 4-1. Use fixed context to encode a flag bit to indicate whether Y / R is equal to 0.

[0113] 4-2. If Y / R is equal to 0, continue to use the fixed context to encode a flag bit to indicate whether U / G is equal to 0;

[0114] 1) If U / G and Y / R are both equal to 0, use the fixed context to encode the absolute value of V / B minus 1 and encode its sign;

[0115] 2) If Y / R is equal to 0 but U / G is not equal to 0, use the fixed context to encode the absolute value of U / G minus 1 and its sign, and continue to use the fixed context to encode V / B and its sign;

[0116] 4-3. If Y / R is not equal to 0, use the fixed context to encode the absolute value of Y / R minus 1 and encode its sign, continue to use the fixed context to encode U / G and its sign; continue to use the fixed context to encode V / B and its sign.

[0117] The following is a detailed description of the specific steps of the prediction attribute quantization residual decoding end. Figure 3 As shown, the following steps are included: 1-3:

[0118] 1. Set the adaptive threshold based on the attribute quantization step size. Based on experimental experience, set the threshold to 35 and adaptively select whether to use compressed run decoding.

[0119] 2. Decode the zero attribute prediction quantization residual and the run-length code run_length. This means that the attribute prediction quantization residuals Res of consecutive run_length points are all 0. The run-length code decoding method includes the following steps 2-1 and 2-2:

[0120] 2-1. If compressed run-length encoding is not used, the run-length encoding value run_length is decoded directly;

[0121] 2-2. If compressed run-length coding is used for decoding, first decode the run-length coding half value run_length_half, then decode the fixed context r, where r takes the value 0 or 1. Finally, the run-length coding value run_length = 2*run_length_half + r is obtained.

[0122] 3. Decode the non-zero attribute prediction quantization residual Res to obtain the non-zero attribute prediction quantization residual Res of the current point.

[0123] In some optional embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the present invention is provided in an exemplary manner for the purpose of providing a more comprehensive understanding of the technology. The disclosed method is not limited to the operation and logic flow presented herein. Optional embodiments are contemplated in which the order of the various operations is changed and the sub-operations described as a part of a larger operation are performed independently.

[0124] Furthermore, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise indicated, one or more of the functions and / or features described may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It will also be understood that a detailed discussion of the actual implementation of each module is not necessary for understanding the present invention. More specifically, given the properties, functions, and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the module will be understood within the ordinary skill of an engineer. Therefore, a person skilled in the art using ordinary skill will be able to implement the present invention set forth in the claims without undue experimentation. It will also be understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0125] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the 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 for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0126] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0127] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0128] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0129] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0130] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the claims and their equivalents.

[0131] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A point cloud color attribute adaptive compression run length encoding method, characterized in that: include: Convert point cloud attributes from RGB color space to YUV color space; Perform Hilbert reordering on the point cloud data, perform differential prediction under the Hilbert order, and obtain the attribute prediction residual; quantizing the attribute prediction residual to obtain an attribute prediction quantized residual; The attribute prediction quantization residual is entropy coded using a color attribute adaptive compression run length coding method to obtain an attribute code stream, including: Configuring an adaptive threshold value according to the attribute quantization step size parameter; the adaptive threshold value is used to determine whether to use compressed run decoding; Traverse the attribute prediction quantization residual of each point and count the first point where the continuous attribute prediction quantization residual value is 0; Directly encoding a run length encoding value or using compressed run length encoding according to the first point number; When the attribute prediction quantization residual is non-zero, encoding the value of the first point number, setting the value of the first point number to 0 and restarting counting, and then encoding the non-zero attribute prediction quantization residual; The method of using compressed run length encoding according to the first number of points includes: Divide the first point number by 2 and round it down to obtain a second point number, and finally encode the second point number; A fixed context code is added. If the first point is divided by 2 and the remainder is 1, the fixed context code is 1; if the first point is divided by 2 and the remainder is 0, the fixed context code is 0. The encoding of the non-zero attribute prediction quantization residual includes: Use fixed context encoding to determine whether the first flag bit is equal to 0. If the first flag bit represents equal to 0, continue to use the fixed context to encode whether the second flag bit represents equal to 0; If the second flag bit representative and the first flag bit representative are both equal to 0, using the absolute value of the fixed context code minus 1, and encoding the fixed context code symbol; If the first flag bit represents a value equal to 0 but the second flag bit represents a value not equal to 0, subtract 1 from the absolute value of the fixed context encoding; If the first flag bit represents not equal to 0, use the fixed context to encode the absolute value of the first flag bit representative minus 1, and encode the symbol represented by the first flag bit, and continue to use the fixed context to encode the second flag bit representative and the symbol represented by the second flag bit.

2. The point cloud color attribute adaptive compression run length encoding method according to claim 1, characterized in that: The method further comprises: According to the changes in geometric information, when the operation of removing duplicate points is performed in the geometric encoding, the attribute interpolation operation is performed.

3. The point cloud color attribute adaptive compression run length encoding method according to claim 1, characterized in that: The method further comprises: The attribute code stream is entropy decoded using the color attribute adaptive compression run-length decoding method to obtain the attribute prediction quantization residual; Inverse quantize the attribute prediction quantization residual to obtain the attribute prediction residual; The attribute prediction of the points in the reconstructed point cloud is performed by the residual prediction method, and finally the attribute prediction residual corresponding to the point is added to obtain the attribute of the point in the point cloud; Convert point cloud attributes from YUV color space to RGB color space.

4. The point cloud color attribute adaptive compression run length encoding method according to claim 3, characterized in that: The method further comprises: Configuring an adaptive threshold according to the attribute quantization step size, wherein the adaptive threshold is used to determine whether to use compressed run decoding; Decode zero attribute prediction quantization residual and run length coding; Decode the non-zero attribute prediction quantization residual Res to obtain the non-zero attribute prediction quantization residual of the current point.

5. The point cloud color attribute adaptive compression run length encoding method according to claim 4, characterized in that: The decoding of the zero attribute prediction quantization residual and the decoding of the run length coding include: If compressed run-length encoding is not used, the run-length encoding value is decoded directly; If compressed run-length code decoding is used, the run-length code half value is decoded first, and then the fixed context is decoded. The fixed context takes the value 0 or 1 to obtain the run-length code value.

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