Point cloud attribute compression method based on deletion of 0 elements in quantization matrix

Abstract

The invention discloses a point cloud attribute compression method based on deletion of 0 elements in a quantization matrix. In view of the quantization matrix during the point cloud attribute compression process, the optimal traversal order is adopted at a coding end to enable 0 elements to be centrally distributed at a tail end in a generated data stream, entropy coding is carried out after the0 are deleted, the data volume of the data stream is reduced, a bit stream generated after coding is reduced, point cloud geometry information is combined at a decoding end to recover the deleted 0 elements, and the method is ensured not to introduce extra errors. The method comprises steps: the traversal order of the quantization matrix is optimized at the coding end; the 0 elements at the tail end of the data stream are deleted; the geometry information is consulted to recover the quantization matrix at the decoding end; and a point cloud attribute compression coding process and a decoding process are carried out. At the point cloud attribute compression coding end, seven traversal orders are adopted for the quantization matrix, and distribution of the 0 elements in the data stream is more centralized at the tail end; the 0 elements at the tail end of the data stream are deleted, redundant information is removed, and the data volume in need of entropy coding is reduced; and at the decoding end, the point cloud geometry information is combined to complete the deleted 0 elements, the quantization matrix is recovered according to the traversal order, and the compression performanceis improved on the premise of not introducing new errors.

Description

technical field [0001] The invention belongs to the technical field of point cloud data processing, and relates to a point cloud data compression method, in particular to a point cloud attribute compression method based on deleting 0 elements in a quantization matrix. 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, texture and other attribute information, a...

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Problems solved by technology

This method completely solves the subgraph problem, and at the same time, it has a greater improvement in compression perform

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