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Neighbor weight-based parameter selection and transmission point cloud attribute encoding and decoding method and equipment

An encoding method and attribute technology, which is applied in the field of point cloud processing, can solve the problems of low attribute prediction accuracy and lower encoding and decoding performance, and achieve the effect of improving attribute compression performance and improving utilization

Active Publication Date: 2019-12-13
PEKING UNIV SHENZHEN GRADUATE SCHOOL
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  • Abstract
  • Description
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Problems solved by technology

[0006] However, the above related technologies only consider the Euclidean distance when calculating the weight of each nearest neighbor point, and the Euclidean distance cannot represent the attribute correlation well, resulting in low attribute prediction accuracy and reducing the encoding and decoding performance.

Method used

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  • Neighbor weight-based parameter selection and transmission point cloud attribute encoding and decoding method and equipment
  • Neighbor weight-based parameter selection and transmission point cloud attribute encoding and decoding method and equipment
  • Neighbor weight-based parameter selection and transmission point cloud attribute encoding and decoding method and equipment

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Embodiment 1

[0041] Embodiment 1 of the method for encoding and decoding point cloud attributes based on neighbor weight parameter selection and transfer, including the following steps A and B:

[0042] A. Perform steps (1) to (3) on the encoding side, such as figure 1 Shown is a schematic flow chart of the attribute compression coding end of Embodiment 1, including:

[0043] (1) Determine the K nearest neighbors of the current point according to the spatial distance from the point in the point cloud to the current point.

[0044] (2) Determine the distance adjustment parameter θ when calculating the weight of the nearest neighbor point: that is, the parameter θ of the distance in the Z direction when calculating the neighbor weight. Selection method 1: According to different types of attributes, use a specific value of θ for a specific type of attribute. Specifically, for example, use θ value of 1 for the color attribute and 3 for the reflectance attribute; Method 2: Change the parameter...

Embodiment 2

[0052] Embodiment 2 of the method for point cloud encoding and decoding based on neighbor weight parameter selection and transfer includes the following steps C and D:

[0053] C. Perform steps (1) to (5) on the encoding side, such as image 3 Shown is a schematic flow chart of the attribute compression coding end of embodiment 2, including:

[0054] (1) Construct LOD and find neighbors for each point in it Traverse the points in the PointCloud, add them to the LOD respectively, and determine the K nearest neighbors of the current point according to the geometric information of the point cloud. The specific construction process is: sort all the points in the point cloud according to the Morton code sequence, that is, according to the preset LOD layer number, down-sample the sorted points, and the obtained points after each sampling constitute a Layer LOD, the sampling distance is from large to small, until the entire LOD is constructed, and the point cloud after LOD sorting i...

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Abstract

The invention provides a neighbor weight-based parameter selection and transmission point cloud attribute encoding and decoding method, encoding equipment and decoding equipment. The coding method comprises the following steps: determining K nearest neighbor points of a current point according to the spatial distance from the point in a point cloud to the current point; determining a distance adjustment parameter when the weight of the nearest neighbor point is calculated; carrying out entropy coding according to the distance adjustment parameter; determining an attribute prediction value of the current point according to the distance adjustment parameter; and performing encoding processing according to the attribute prediction value of the current point. The decoding method comprises thefollowing steps: determining K nearest neighbor points of a current point according to the spatial distance from the point in the point cloud to the current point; carrying out entropy decoding according to the point cloud attribute code stream to determine a distance adjustment parameter when the weight of the nearest neighbor point is calculated; and determining an attribute prediction value ofthe current point according to the distance adjustment parameter. Therefore, the point cloud coding performance can be improved by selecting proper distance adjustment parameters.

Description

technical field [0001] The invention belongs to the field of point cloud processing, and relates to a point cloud attribute compression method, in particular to a method and device for encoding and decoding point cloud attributes based on neighbor weight parameter selection and transfer. Background technique [0002] 3D point cloud is an important form of digitalization of the real world. With the rapid development of 3D scanning equipment (laser, radar, etc.), the accuracy and resolution of point clouds are higher. High-precision point clouds are widely used in the construction of urban digital maps, and play a technical supporting role in many popular researches such as smart cities, unmanned driving, and cultural relics protection. The point cloud is obtained by sampling the surface of an object by a 3D scanning device. The number of points in a frame of point cloud is generally in the millions, and each point contains geometric information, color, reflectivity and other...

Claims

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Application Information

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IPC IPC(8): H04N19/147H04N19/186H04N19/597H04N19/593H04N19/91H04N19/42
CPCH04N19/147H04N19/186H04N19/597H04N19/593H04N19/91H04N19/42
Inventor 李革张琦王静邵薏婷
Owner PEKING UNIV SHENZHEN GRADUATE SCHOOL
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