Invention Grant
- Patent Title: Point cloud attribute compression method based on deleting 0 elements in quantisation matrix
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Application No.: US17045894Application Date: 2018-05-15
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Publication No.: US11216985B2Publication Date: 2022-01-04
- Inventor: Ge Li , Qi Zhang , Yiting Shao , Wen Gao
- Applicant: Peking University Shenzhen Graduate School
- Applicant Address: CN Guangdong
- Assignee: Peking University Shenzhen Graduate School
- Current Assignee: Peking University Shenzhen Graduate School
- Current Assignee Address: CN Guangdong
- Agency: The Belles Group, P.C.
- Priority: CN201810412818.2 20180503
- International Application: PCT/CN2018/086793 WO 20180515
- International Announcement: WO2019/210531 WO 20191107
- Main IPC: G06T9/00
- IPC: G06T9/00 ; G06T3/40 ; G06T9/40

Abstract:
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.
Public/Granted literature
- US20210142522A1 POINT CLOUD ATTRIBUTE COMPRESSION METHOD BASED ON DELETING 0 ELEMENTS IN QUANTISATION MATRIX Public/Granted day:2021-05-13
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