首页> 外国专利> POINT CLOUD ATTRIBUTE COMPRESSION METHOD BASED ON DELETING 0 ELEMENTS IN QUANTISATION MATRIX

POINT CLOUD ATTRIBUTE COMPRESSION METHOD BASED ON DELETING 0 ELEMENTS IN QUANTISATION MATRIX

机译:基于删除量化矩阵中的0个元素的点云属性压缩方法

摘要

Disclosed in the present invention is a point cloud attribution compression method based on deleting 0 elements in a quantisation matrix, including optimizing a traversal sequence for a quantisation matrix and deleting the 0 elements at the end of the data stream. The present invention may use seven types of traversal sequences at the encoding end of the point cloud attribute compression, such that the distribution of the 0 elements in the data stream may be more concentrated at the end thereof. The 0 elements at the end of the data stream may be deleted, removing redundant information and reducing the quantity of data to be entropy encoded. At the decoding end, the point cloud geometric information may be incorporated to supplement the deleted 0 elements and the quantisation matrix may be restored according to the traversal sequence, thereby improving compression performance without introducing new errors.
机译:在本发明中公开了一种基于在量化矩阵中删除0元素的点云归因压缩方法,包括优化用于量化矩阵的遍历序列,并在数据流的末尾删除0个元素。本发明可以在点云属性压缩的编码结束处使用七种类型的遍历序列,使得数据流中的0个元素的分布可以在其末端更集中。可以删除数据流末尾的0个元素,删除冗余信息并减少要熵编码的数据量。在解码端,可以合并点云几何信息以补充删除的0元素,并且可以根据遍历序列恢复量化矩阵,从而提高压缩性能而不引入新的误差。

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