Method and device for encoding or decoding three-dimensional data point set

Abstract

The embodiment of the application provides a method and device for encoding or decoding a three-dimensional data point set, which can simplify an encoding method, reduce the time overhead of encodingand decoding, and improve the compression rate. The method comprises the following steps: carrying out position coordinate coding on the position coordinate of at least one three-dimensional data point in the three-dimensional data point set to obtain a first binary code stream; according to the position coordinate sequence of the at least one three-dimensional data point after the position coordinate coding, carrying out binarization coding on the attribute of the at least one three-dimensional data point to obtain a second binary code stream; and carrying out entropy coding on the first binary code stream and the second binary code stream.

Description

[0001] Copyright statement [0002] The content disclosed in this patent document contains copyrighted material. The copyright belongs to the copyright owner. The copyright owner does not object to anyone copying the patent document or the patent disclosure in the official records and archives of the Patent and Trademark Office. Technical field [0003] This application relates to the field of information processing, and more specifically, to a method and device for encoding or decoding a three-dimensional data point set. Background technique [0004] A three-dimensional data point set is a representation of a three-dimensional object or scene. It is composed of a set of discrete points that are randomly distributed in space and express the spatial structure and surface properties of the three-dimensional object or scene. The data of a three-dimensional data set can be It includes three-dimensional coordinates describing the coordinate information, and further includes attributes ...

AI Technical Summary

Problems solved by technology

[0005] However, this encoding method needs to build a hierarchical structure. When selecting the adjacent reference point for the position of each 3D data point set, it needs to traverse all the 3D data points multiple times. This method will have a large time in encoding and decoding. Overhead, especially when the amount of data in the three-dimensional data point set is large, the cost of this time complexity is particularly obvious

And the header information about the attributes in the encoded code stream needs to describe the relevant information about the layered coding attributes. When the number of three-dimensional data points is not very large, the proportion of the compressed code stream will be Relatively large, thus becoming a bottleneck restricting the compression rate

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