KR102549617B1 - 3d point cloud data encoding/decoding method and apparatus - Google Patents

Abstract

A point cloud data encoding/decoding method and apparatus are disclosed. The decoding method includes decoding information about properties of point cloud data from a bitstream, acquiring properties of the point cloud data using the information about the decoded properties, and using the acquired properties to determine the point cloud data. The method may include restoring cloud data, and the property-related information may include bit-depth information about the property of the point cloud data.

Description

Method and apparatus for encoding/decoding 3D point cloud data {3D POINT CLOUD DATA ENCODING/DECODING METHOD AND APPARATUS}

The present invention relates to a method and apparatus for encoding/decoding point cloud data. Specifically, it relates to a method and apparatus for encoding/decoding attribute information of 3D point cloud data.

A conventional method of encoding/decoding 3D point cloud attribute information performs fixed bit depth processing. For example, by encoding/decoding by fixing the value of the reflectivity attribute to 16 bits, encoding/decoding performance may be limited when the range of actual attribute information is smaller than 16 bits or when compression is required in the range of 16 bits or less.

Also, the conventional method does not perform error correction of semi-lossless/lossy compressed attribute information. For example, attribute information is compressed by quantization and reconstructed by inverse quantization. In the process of quantization/inverse quantization, loss may occur and an error may occur in the restored attribute information. However, in the conventional method, correction for minimizing such an error is not considered.

An object of the present invention is to provide a method and apparatus for encoding/decoding 3D point cloud attribute information.

Another object of the present invention is to provide a recording medium storing a bitstream generated by the encoding/decoding method or apparatus of the present invention.

According to the present invention, decoding information about attributes of point cloud data from a bitstream; obtaining attributes of the point cloud data by using information on the decrypted attributes; and restoring the point cloud data using the acquired attribute, wherein the information on the attribute includes bit depth information on the attribute of the point cloud data. .

The bit depth information according to an embodiment may be signaled in a sequence parameter set.

Attributes of the point cloud data according to an embodiment may be obtained by performing a clipping operation based on the bit depth information.

Acquiring the attribute of the point cloud data according to an embodiment may include converting a bit depth of the attribute of the point cloud data using the bit depth information.

Acquiring attributes of the point cloud data according to an embodiment may include generating an error correction table; and acquiring properties of the point cloud data using the error correction table.

The generating of the error correction table may include configuring a first column of the error correction table based on attributes of point cloud data whose bit depth is converted; and decoding the bitstream to construct a second column of the error correction table.

The configuring of the first column of the error correction table may include restoring an attribute value of the point cloud data whose bit depth is converted; removing redundant values among attribute values of the restored point cloud data; The first column of the error correction table may be configured by arranging the attribute values from which the redundant values have been removed.

Acquiring attributes of the point cloud data using the error correction table according to an embodiment includes restoring attributes of the point cloud data using information in a first column and information in a second column of the error correction table. steps may be included.

In addition, according to the present invention, the step of receiving an attribute of the point cloud data; encoding a property of the point cloud data using information about the property of the point cloud data; and adding information about attributes of the point cloud data to a bitstream, wherein the information about attributes includes bit depth information about attributes of the point cloud data. there is.

The bit depth information according to an embodiment may be signaled in a sequence parameter set.

Encoding the attribute of the point cloud data according to an embodiment may include converting a bit depth of the attribute of the point cloud data using the bit depth information.

Encoding attributes of the point cloud data according to an embodiment may include generating an error correction table; and encoding attributes of the point cloud data using the error correction table.

The generating of the error correction table may include configuring a first column of the error correction table based on attributes of point cloud data whose bit depth is converted; and constructing a second column of the error correction table based on attributes of the point cloud data and attributes of the point cloud data whose bit depth is converted.

The configuring of the first column of the error correction table may include restoring an attribute value of the point cloud data whose bit depth is converted; removing redundant values among attribute values of the restored point cloud data; and constructing a first column of the error correction table by arranging attribute values from which duplicate values have been removed.

In addition, according to the present invention, the inverse transform unit; and a restoration unit, wherein the inverse transformation unit decodes information about properties of point cloud data from a bitstream, the restoration unit obtains properties of the point cloud data using the information about the decoded properties, and the obtained An apparatus for decoding point cloud data may be provided that restores the point cloud data using attributes, and the information on the attributes includes bit depth information on attributes of the point cloud data.

The bit depth information according to an embodiment may be signaled in a sequence parameter set.

Attributes of the point cloud data according to an embodiment may be obtained by performing a clipping operation based on the bit depth information.

The inverse transform unit according to an embodiment may convert a bit depth of an attribute of the point cloud data using the bit depth information.

The point cloud data decoding apparatus according to an embodiment may further include a table generator, and the table generator may generate an error correction table and acquire attributes of the point cloud data using the error correction table.

In addition, according to the present invention, in a computer-readable non-transitory recording medium storing data received and decoded by a point cloud data decoding apparatus and used for restoring a point cloud, the data is information about attributes of the point cloud data. wherein the information about the decrypted attribute is used to acquire attributes of the point cloud data, the acquired attributes are used to restore the point cloud data, and the information about the attributes is used to obtain attributes of the point cloud data. A computer-readable non-transitory recording medium characterized in that it includes bit-depth information for attributes may be provided.

The features briefly summarized above with respect to the disclosure are merely exemplary aspects of the detailed description of the disclosure that follows, and do not limit the scope of the disclosure.

According to the present invention, an object of the present invention is to provide a method and apparatus for encoding/decoding 3D point cloud attribute information.

Another object of the present invention is to provide a recording medium storing a bitstream generated by the encoding/decoding method or apparatus of the present invention.

In addition, according to the present invention, encoding/decoding efficiency of 3D point cloud attribute information can be improved.

Effects obtainable in the present disclosure are not limited to the effects mentioned above, and other effects not mentioned may be clearly understood by those skilled in the art from the description below. will be.

1A is an example of a block diagram for explaining the operation of a conventional encoder.
1B is an example of a block diagram for explaining the operation of a conventional decoder.
2A is a block diagram for explaining the operation of an encoder according to an embodiment of the present invention.
2B is a block diagram for explaining the operation of a decoder according to an embodiment of the present invention.
3 is a flowchart illustrating a process of generating a table in an encoder according to an embodiment of the present invention.
4 is a flowchart illustrating a process of generating a table in a decoder according to an embodiment of the present invention.
5 to 8 show syntax element information required to implement a method and apparatus for encoding/decoding 3D point cloud attribute information in an encoder/decoder according to an embodiment of the present invention, and the meaning of the information of the syntax element (semantics), a diagram for explaining the encoding/decoding process.
9 is a diagram for explaining a comparison result between the operation of a 3D point cloud attribute information encoding/decoding method and apparatus according to an embodiment of the present invention and the operation of a conventional encoding/decoding method and apparatus.
10 is a flowchart of a point cloud data decoding method according to an embodiment of the present invention.
11 is a flowchart of a point cloud data encoding method according to an embodiment of the present invention.

Since the present invention can make various changes and have various embodiments, specific embodiments will be illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the present invention to specific embodiments, and should be understood to include all modifications, equivalents, and substitutes included in the spirit and scope of the present invention. Like reference numbers in the drawings indicate the same or similar function throughout the various aspects. The shapes and sizes of elements in the drawings may be exaggerated for clarity. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS For detailed descriptions of exemplary embodiments described below, reference is made to the accompanying drawings, which illustrate specific embodiments by way of example. These embodiments are described in sufficient detail to enable those skilled in the art to practice the embodiments. It should be understood that the various embodiments are different, but need not be mutually exclusive. For example, specific shapes, structures, and characteristics described herein may be implemented in one embodiment in another embodiment without departing from the spirit and scope of the invention. Additionally, it should be understood that the location or arrangement of individual components within each disclosed embodiment may be changed without departing from the spirit and scope of the embodiment. Accordingly, the detailed description set forth below is not to be taken in a limiting sense, and the scope of the exemplary embodiments, if properly described, is limited only by the appended claims, along with all equivalents as claimed by those claims.

In the present invention, terms such as first and second may be used to describe various components, but the components should not be limited by the terms. These terms are only used for the purpose of distinguishing one component from another. For example, a first element may be termed a second element, and similarly, a second element may be termed a first element, without departing from the scope of the present invention. The terms and/or include any combination of a plurality of related recited items or any of a plurality of related recited items.

When a component of the present invention is referred to as “connected” or “connected” to another component, it may be directly connected or connected to the other component, but there may be other components in the middle. It should be understood that it may be On the other hand, when an element is referred to as “directly connected” or “directly connected” to another element, it should be understood that no other element exists in the middle.

Components appearing in the embodiments of the present invention are shown independently to represent different characteristic functions, and do not mean that each component is composed of separate hardware or a single software component. That is, each component is listed and included as each component for convenience of explanation, and at least two components of each component can be combined to form a single component, or one component can be divided into a plurality of components to perform a function, and each of these components can be divided into a plurality of components. Integrated embodiments and separated embodiments of components are also included in the scope of the present invention as long as they do not depart from the essence of the present invention.

Terms used in the present invention are only used to describe specific embodiments, and are not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly dictates otherwise. In the present invention, terms such as "comprise" or "having" are intended to designate that there is a feature, number, step, operation, component, part, or combination thereof described in the specification, but one or more other features It should be understood that the presence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded. That is, the description of "including" a specific configuration in the present invention does not exclude configurations other than the corresponding configuration, and means that additional configurations may be included in the practice of the present invention or the scope of the technical spirit of the present invention.

Some of the components of the present invention are not essential components that perform essential functions in the present invention, but may be optional components for improving performance. The present invention can be implemented by including only components essential to implement the essence of the present invention, excluding components used for performance improvement, and a structure including only essential components excluding optional components used for performance improvement. Also included in the scope of the present invention.

EMBODIMENT OF THE INVENTION Hereinafter, embodiment of this invention is described concretely with reference to drawings. In describing the embodiments of this specification, if it is determined that a detailed description of a related known configuration or function may obscure the gist of the present specification, the detailed description will be omitted, and the same reference numerals will be used for the same components in the drawings. and duplicate descriptions of the same components are omitted.

1A is an example of a block diagram for explaining the operation of a conventional encoder.

1A may be an embodiment of an encoder of PCC categories 1 and 3.

Point cloud data to be described later in the present invention may mean 3D point cloud data.

Referring to FIG. 1A , the encoder 1 may divide input point cloud data 100 into location information 110 and attribute information 120 and encode them. The location information 110 may be compressed through quantization 111 , removal of redundant values after quantization 113 , octree encoding 115 , and/or arithmetic encoding 118 . At this time, the process of removing redundant values after quantization (113) is not necessarily performed as an option.

Meanwhile, the number of attribute information 120 may correspond 1:1 to the number of location information 110 in the compression process. When redundant values are removed after quantization (113), position information may be changed. For example, the number of location information may be reduced. Accordingly, the attribute information 120 may be reconstructed into attribute information corresponding to the changed location information using the attribute converter 121 . For example, the attribute information 120 may be reconstructed into attribute information corresponding to the reduced location information using the attribute converter 121 . Location information is grouped and sorted for each level using level of detail generation 122, and reconstructed attribute information 123 can be compressed using interpolation-based prediction 125 according to the grouping and sorting order. there is. Interpolation-based prediction (125) predicts the current attribute value based on the interpolation technique from the already compressed attribute value using the high correlation between adjacent attribute values, and calculates the difference (126) between the current attribute value and the predicted attribute value. can be saved Thereafter, the difference 126 between the current attribute value and the predicted attribute value may be compressed through quantization 127 and arithmetic encoding 118.

1B is an example of a block diagram for explaining the operation of a conventional decoder.

1B may be an embodiment of a decoder of PCC categories 1 and 3.

Referring to FIG. 1B , the decoder 2 may output the compressed bitstream 150 as compressed location information 161 and attribute information 171 using arithmetic decoding 160 . The decoder 2 may obtain reconstructed position information 165 by performing octree decoding 162 and inverse quantization 164 on the compressed position information 161 . The decoder 2 performs inverse quantization (172) on the compressed attribute information (171), groups it by level by level of detail generation (175), and performs inverse interpolation-based prediction (174) according to the sorted order. The restored attribute information 177 can be obtained using Point cloud data may be restored (190) by adding the restored location information 165 and the restored attribute information 177 corresponding thereto.

2A is a block diagram for explaining the operation of an encoder according to an embodiment of the present invention.

2B is a block diagram for explaining the operation of a decoder according to an embodiment of the present invention.

Referring to FIG. 2A, compared to the encoder 1 of FIG. 1A, the encoder 3 includes a bit-depth-based converter 230, a bit-depth-based inverse converter 233, and/or a table generator in the process of encoding attribute information. (235) may be further included.

The bit depth-based converter 230 may convert input attribute information into a predetermined bit depth. Information on the predetermined bit depth may be signaled from an encoder to a decoder. Also, information on the predetermined bit depth may be derived using a value preset in an encoder/decoder. In this case, information on the predetermined bit depth may be signaled through a sequence parameter set.

For example, the bit depth-based converter 230 may perform conversion using the example of Equation 1. That is, transformation can be performed by using shift operations on input attributes.

은 변환된 속성값이다. 또한, n은 포인트 수에 따른 인덱스로서, 예를 들어 포인트 클라우드 데이터가 10,000개라면 0에서 9,999의 값을 가질 수 있다. 또한, i는 입력 비트 깊이이고, d는 정해진 비트 깊이를 나타낸다. 이때, 획득시의 예를 들면, 입력된 속성 정보가 0에서 65,535의 값의 범위를 갖는 16비트인 경우에 정해진 비트 깊이 d가 8비트이면 입력된 속성 정보를 256(= 2^(16-8))의 값으로 나누어 변환할 수 있고, 정해진 비트 깊이 d가 10비트이면 입력된 속성 정보를 64(= 2^(16-10))의 값으로 나누어 변환할 수 있다. In Equation 1, a _n is an input attribute value,

is the converted attribute value. In addition, n is an index according to the number of points, and may have a value of 0 to 9,999, for example, if there are 10,000 point cloud data. In addition, i is an input bit depth, and d represents a predetermined bit depth. At this time, for example, when the input attribute information is 16 bits having a value range of 0 to 65,535 and the determined bit depth d is 8 bits, the input attribute information is 256 (= 2 ^(16-8) ), and if the predetermined bit depth d is 10 bits, the input attribute information can be converted by dividing by a value of 64 (= 2 ^(16-10) ).

The bit depth-based inverse converter 233 may inversely transform attribute information converted to a predetermined bit depth into an original bit depth. For example, the bit depth-based inverse transformer 233 may perform inverse transformation using the example of Equation 2. That is, attribute information may be obtained by performing a shift operation on depth information.

는 정해진 비트 깊이로 변환된 속성값이고,

는 원래의 비트 깊이로 역변환된 속성값이다. 또한, n은 포인트 수에 따른 인덱스를 나타낸다. 또한, i는 원래의 비트 깊이이고, d는 정해진 비트 깊이를 나타낸다.In Equation 2,

is an attribute value converted to a predetermined bit depth,

is an attribute value inversely converted to the original bit depth. Also, n represents an index according to the number of points. Also, i is the original bit depth, and d represents the set bit depth.

Since the restored value of the semi-lossless/lossy compressed attribute information based on the predetermined bit depth information may be different from the value of the original attribute information, the table generator 235 makes the restored value more similar to the original attribute information. You can create a table that compensates for the approximation. Here, the restored value of the semi-lossless/lossy compressed attribute information is obtained through a first process 229 including a bit depth-based converter 230, interpolation-based prediction 225, and/or quantization 227, and bit depth can be obtained using the inverse transformer 233 based on Since inverse quantization 272 and inverse interpolation-based prediction 274, which can be included in the decoder 4, are included in the first process 229, the encoder 3 of the present disclosure The same information as the attribute information restored in step (4) can be obtained.

3 is a flowchart illustrating a process of generating a table in an encoder according to an embodiment of the present invention.

An operation of the encoder described later in FIG. 3 may be performed by a table generator included in the encoder.

Referring to FIGS. 2A and 3 , in step S310, the encoder may store original attribute values input to the bit depth-based converter 230.

In step S320, the encoder may store the restored attribute values using the first process 229 and the bit depth-based inverse transformer 233.

In step S330, the encoder may configure the first column of the table by removing duplicated values from among the restored attribute values and arranging them in ascending order. Alternatively, you can sort in descending order.

In step S340, the encoder may configure the second column of the table as an average value of difference values between each restored attribute value and original attribute values corresponding thereto.

A first column of the two-column table constructed in the encoder is information that can be reconstructed in the decoder. Accordingly, only the table information 236 of the second column may be transmitted to the decoder without transmitting the table information of the first column to the decoder.

Referring again to FIG. 2B, compared to the decoder 2 of FIG. 1B, the decoder 4 has a bit depth-based inverse transformer 280, a table generator 283, and/or the original attribute information more A corrector 284 for correcting the inversely transformed attribute information 281 based on bit depth to be approximated may be further included.

The bit-depth-based inverse converter 280 may inverse-convert the attribute information converted to a predetermined bit depth to the original bit depth using Equation 2 described above.

Information on the predetermined bit depth may be signaled from an encoder to a decoder. Also, information on the predetermined bit depth may be derived using a value preset in an encoder/decoder. In this case, information on the predetermined bit depth may be signaled through a sequence parameter set. In addition, the attribute information may be obtained by obtaining an upper limit value of the attribute information through a shift operation or the like for the information on the predetermined bit depth and performing a clipping operation based thereon. Since the attribute information can know the range of valid values that can be represented through the predetermined bit depth, it can be corrected when it is out of the range of valid values.

4 is a flowchart illustrating a process of generating a table in a decoder according to an embodiment of the present invention.

An operation of a decoder described later in FIG. 4 may be performed by a table generator included in the decoder.

Referring to FIGS. 2B and 4 , in step S410, the decoder may store attribute values restored to the original bit depth using the bit depth based inverse transformer 280.

In step S420, the decoder may configure the first column of the table by removing duplicated values from among the restored attribute values and arranging them in ascending order. Or you can sort in descending order.

In step S430, the decoder may construct a second column using information on average values of difference values between each restored attribute value and original attribute values corresponding thereto. A decoder may receive the information from an encoder.

The decoder may find attribute information 281 inversely transformed through the bit depth-based inverse transformer 280. Also, the decoder can find the first column and the second column of the table through the table generator 283. The decoder may finally restore attribute information by performing correction by adding a value of a second column corresponding to the inverse transformed attribute information 281 to the inverse transformed attribute information 281 . The correction operation may be performed by the corrector 284 .

5 to 8 show syntax element information necessary for implementing a method and apparatus for encoding/decoding 3D point cloud attribute information in an encoder/decoder according to an embodiment of the present invention, and the meaning of the information of the syntax element (semantics), a diagram for explaining the encoding/decoding process.

5 to 8, compared to the conventional encoding/decoding process required to compress 3D point cloud attribute information, syntax elements such as inputBitDepth, bitDepth, ect_flag, ectSize, ectElementBitDepth, signOfEctElement, and ectValue are added. Able to know. Meanwhile, the name of each syntax element is an example and may vary depending on the embodiment.

9 is a diagram for explaining a comparison result between the operation of a 3D point cloud attribute information encoding/decoding method and apparatus according to an embodiment of the present invention and the operation of a conventional encoding/decoding method and apparatus.

For comparison between the two methods, two different test sequences, citytunnel_q1mm and tollbooth_q1mm, which contain 16-bit reflectivity attribute values, were used.

In FIG. 9 , Sequence may mean the name of a test sequence, and No input inputs may mean the number of point clouds included in each test sequence. Reference is the performance result of the conventional encoding/decoding method, and Proposed is the performance result of the encoding/decoding method of the present disclosure. For example, a conventional encoding/decoding method may be MPEG PCC Test Model Category 1,3 reference software. In addition, the encoding/decoding method of the present disclosure may be based on MPEG PCC Test Model Category 1 and 3 reference software with the above-described configurations in FIGS. 2A to 8 added.

Encoded size is the result of compressing reflectivity attribute information. For example, in the case of the citytunnel_q1mm test sequence, if the encoded size is 171672112 bits, the amount of information of the reflectivity attribute included in the test sequence before compression is 19948121 times 16 bits, which is 319169936 bits. Therefore, using the conventional encoding/decoding method, a compression rate of approximately 54%, which is 171672112 divided by 319169936, can be achieved. Bits per input point (bpp) is the number of bits per compressed point. For example, in the case of the citytunnel_q1mm test sequence, if the encoded size is 171672112 bits, bpp is 171672112 divided by 19948121, which is 8.61 bpp. 8.61 bpp may mean that 16-bit attribute information per point before compression is compressed to 8.61 bits. Reflectance PSNR is a value that measures the difference between the test sequence before compression and the sequence compressed and restored through the encoder/decoder. The higher the value of PSNR, the smaller the difference from the original data, so the restored sequence matches the sequence before compression. It can mean that it has been restored more similarly.

Referring to FIG. 9 , it can be seen that the encoding/decoding method of the present disclosure improves the compression ratio and PSNR of attribute information compared to the conventional compression method. The encoding/decoding method of the present disclosure may use predetermined bit depth information of attribute information and correct errors in semi-lossless/lossy compressed attribute information.

For example, in the case of the conventional encoding/decoding method, the PSNR was 76.16 dB when compressed to 8.61 bpp, but in the case of the encoding/decoding method of the present disclosure, when compressed to 5.03 bpp, which has a higher compression ratio than the conventional encoding/decoding method PSNR was measured inf (infinity). Here, inf may mean that the sequence before compression and the restored sequence completely match without a difference. In addition, in the case of the conventional encoding / decoding method, the PSNR was 50.98 dB when compressed to 4.07 bpp, but in the case of the encoding / decoding method of the present disclosure, the PSNR is compressed to 4.02 bpp, which has a higher compression rate than the conventional encoding / decoding method It was measured higher at 54.24.

10 is a flowchart of a point cloud data decoding method according to an embodiment of the present invention.

In step S1001, information about attributes of point cloud data may be decoded from the bitstream.

Meanwhile, the information about the attribute may include bit depth information about the attribute of the point cloud data.

Here, the bit depth information may be signaled in a sequence parameter set.

In step S1002, attributes of point cloud data may be acquired using information on decoded attributes.

In this case, the attribute of the point cloud data may be obtained by performing a clipping operation based on the bit depth information.

Meanwhile, acquiring the attribute of the point cloud data may include converting a bit depth of the attribute of the point cloud data using bit depth information.

Meanwhile, acquiring the attributes of the point cloud data may include generating an error correction table and acquiring attributes of the point cloud data using the error correction table.

On the other hand, generating the error correction table configures the first column of the error correction table based on the attribute of point cloud data whose bit depth is converted, and configures the second column of the error correction table by decoding the bitstream. may include

Meanwhile, constructing the first column of the error correction table restores attribute values of point cloud data whose bit depth is converted, removes duplicate values among attribute values of the restored point cloud data, and removes duplicate values. and configuring the first column of the error correction table by sorting the removed attribute values.

Meanwhile, acquiring the attribute of the point cloud data using the error correction table may include restoring the attribute of the point cloud data using information in a first column and information in a second column of the error correction table.

In step S1003, point cloud data may be restored using the acquired attributes.

11 is a flowchart of a point cloud data encoding method according to an embodiment of the present invention.

In step S1101, attributes of point cloud data may be input.

Meanwhile, the attribute information may include bit depth information on attributes of point cloud data.

Here, the bit depth information may be signaled in a sequence parameter set.

In step S1102, attributes of the point cloud data may be encoded using information about attributes of the point cloud data.

Meanwhile, encoding the attribute of the point cloud data may include converting the bit depth of the attribute of the point cloud data using bit depth information.

Meanwhile, encoding the attribute of the point cloud data may include generating an error correction table and encoding the attribute of the point cloud data using the error correction table.

On the other hand, generating the error correction table configures the first column of the error correction table based on the attribute of the point cloud data whose bit depth is converted, and the attribute of the point cloud data and the point cloud data whose bit depth is converted. Constructing the second column of the error correction table based on the attribute.

Meanwhile, constructing the first column of the error correction table restores attribute values of point cloud data whose bit depth is converted, removes duplicate values among attribute values of the restored point cloud data, and removes duplicate values. and constructing the first column of an error correction table by sorting these removed attribute values.

According to the present invention, a method and apparatus for encoding/decoding 3D point cloud attribute information may be provided.

In addition, according to the present invention, a recording medium storing a bitstream generated by the encoding/decoding method or apparatus of the present invention may be provided.

In addition, according to the present invention, encoding/decoding efficiency of 3D point cloud attribute information can be improved.

Also, according to the present invention, compression performance can be improved by using predetermined bit depth information of attribute information. For example, the value of a 16-bit attribute has a range of 0 to 65,535 and may include 65,536 pieces of information. In this case, if the actual attribute information range is smaller than 16 bits, and only 256 pieces of information in the range of 0 to 65,535 are used, the size of the bit stream during compression can be reduced by converting the depth of the attribute information to an 8-bit depth.

Also, according to the present invention, errors in semi-lossless/lossy compressed attribute information can be corrected. A restored value of semi-lossless/lossy compressed attribute information based on predetermined bit depth information may be different from a value of original attribute information.

The correction may be performed as follows. The encoder may obtain a restored attribute value after compressing the input original attribute. The encoder may form the first column of the table by removing redundancy of the restored attribute values. The encoder may construct the second column of the table by obtaining an average of difference values between original attribute values corresponding to each first restored attribute value. The encoder may transmit information about the configured column to the decoder. On the other hand, the decoder can construct the first column of the table by obtaining the restored attributes and removing redundancy. The decoder may construct a second column using an average value of difference values between original attribute values corresponding to each restored attribute value received from the encoder. The decoder may correct the error by adding the inverse transformed attribute information and the average value using the completed table.

In the foregoing embodiments, the methods are described on the basis of a flow chart as a series of steps or units, but the present invention is not limited to the order of steps, and some steps may occur in a different order or concurrently with other steps as described above. can In addition, those skilled in the art will understand that the steps shown in the flow chart are not exclusive, that other steps may be included, or that one or more steps of the flow chart may be deleted without affecting the scope of the present invention. You will understand.

The foregoing embodiment includes examples of various aspects. It is not possible to describe all possible combinations to represent the various aspects, but those skilled in the art will recognize that other combinations are possible. Accordingly, it is intended that the present invention cover all other substitutions, modifications and variations falling within the scope of the following claims.

Embodiments according to the present invention described above may be implemented in the form of program instructions that can be executed through various computer components and recorded on a computer-readable recording medium. The computer readable recording medium may include program instructions, data files, data structures, etc. alone or in combination. Program instructions recorded on the computer-readable recording medium may be specially designed and configured for the present invention, or may be known and usable to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical recording media such as CD-ROMs and DVDs, and magneto-optical media such as floptical disks. media), and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language codes that can be executed by a computer using an interpreter or the like as well as machine language codes such as those produced by a compiler. The hardware device may be configured to act as one or more software modules to perform processing according to the present invention and vice versa.

In the above, the present invention has been described by specific details such as specific components and limited embodiments and drawings, but these are provided to help a more general understanding of the present invention, and the present invention is not limited to the above embodiments. , Those skilled in the art to which the present invention pertains may seek various modifications and variations from these descriptions.

Therefore, the spirit of the present invention should not be limited to the above-described embodiments, and not only the claims described later, but also all modifications equivalent or equivalent to these claims belong to the scope of the spirit of the present invention. will do it

Claims (20)

Decoding information about attributes of point cloud data from a bitstream;
obtaining attributes of the point cloud data by using information on the decrypted attributes; and
Restoring the point cloud data using the acquired attributes;
The information about the attribute includes bit depth information about the reflectivity of the point cloud data. According to claim 1,
The bit depth information is signaled in a sequence parameter set. According to claim 1,
Attributes of the point cloud data are obtained by performing a clipping operation based on the bit depth information. Decoding information about attributes of point cloud data from a bitstream;
obtaining attributes of the point cloud data by using information on the decrypted attributes; and
Restoring the point cloud data using the acquired attributes;
The information about the attribute includes bit depth information about the attribute of the point cloud data,
Acquiring the properties of the point cloud data,
and converting a bit depth of an attribute of the point cloud data using the bit depth information. According to claim 4,
Acquiring the properties of the point cloud data,
generating an error correction table; and
The point cloud data decoding method further comprising acquiring attributes of the point cloud data using the error correction table. According to claim 5,
The step of generating the error correction table,
constructing a first column of the error correction table based on attributes of the bit-depth-converted point cloud data; and
and constructing a second column of the error correction table by decoding the bitstream. According to claim 6,
The step of constructing the first column of the error correction table,
restoring attribute values of the point cloud data whose bit depth is converted;
removing redundant values among attribute values of the restored point cloud data; and
and constructing a first column of the error correction table by arranging attribute values from which the redundant values have been removed. According to claim 6,
Acquiring attributes of the point cloud data using the error correction table,
and restoring attributes of the point cloud data using information in a first column and information in a second column of the error correction table. Receiving attributes of point cloud data;
encoding a property of the point cloud data using information about the property of the point cloud data; and
Adding information about attributes of the point cloud data to a bitstream;
The information about the attribute includes bit depth information about the reflectivity of the point cloud data. According to claim 9,
The bit depth information is signaled in a sequence parameter set. Receiving attributes of point cloud data;
encoding a property of the point cloud data using information about the property of the point cloud data; and
Adding information about attributes of the point cloud data to a bitstream;
The information about the attribute includes bit depth information about the attribute of the point cloud data,
The step of encoding the attribute of the point cloud data,
and converting a bit depth of an attribute of the point cloud data using the bit depth information. According to claim 11,
The step of encoding the attribute of the point cloud data,
generating an error correction table; and
The method of encoding point cloud data further comprising encoding attributes of the point cloud data using the error correction table. According to claim 12,
The step of generating the error correction table,
constructing a first column of the error correction table based on attributes of the bit-depth-converted point cloud data; and
and constructing a second column of the error correction table based on attributes of the point cloud data and attributes of the point cloud data whose bit depth is converted. According to claim 13,
The step of constructing the first column of the error correction table,
restoring attribute values of the point cloud data whose bit depth is converted;
removing redundant values among attribute values of the restored point cloud data; and
and constructing a first column of the error correction table by arranging attribute values from which the redundant values have been removed. inverse conversion unit; and
Including the restoration part,
The inverse transformation unit decodes information about attributes of point cloud data from a bitstream;
The restoring unit acquires attributes of the point cloud data using the information on the decrypted attributes, and restores the point cloud data using the acquired attributes;
The information about the attribute includes bit depth information about the attribute of the point cloud data. According to claim 15,
The bit depth information is signaled in a sequence parameter set. According to claim 15,
The attribute of the point cloud data is obtained by performing a clipping operation based on the bit depth information. According to claim 15,
The inverse transform unit,
Point cloud data decoding apparatus for converting a bit depth of an attribute of the point cloud data using the bit depth information. According to claim 18,
Further comprising a table creation unit,
The point cloud data decoding apparatus of claim 1, wherein the table generator generates an error correction table and acquires attributes of the point cloud data using the error correction table. A computer-readable non-transitory recording medium storing data received and decoded by a point cloud data decoding apparatus and used to restore a point cloud,
The data includes information about attributes of point cloud data;
Information about the decrypted attribute is used to obtain attributes of the point cloud data;
The acquired attribute is used to restore the point cloud data;
The information on the attribute comprises bit depth information about reflectivity of the point cloud data.

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