公开(公告)号：US11004240B2

公开(公告)日：2021-05-11

申请号：US16626907

申请日：2018-05-15

申请人： Peking University Shenzhen Graduate School

发明人： Ge Li ,  Yi Ting Shao ,  Qi Zhang ,  Rong Gang Wang ,  Tie Jun Huang ,  Wen Gao

IPC分类号： G06T9/40 ,  G06T7/90 ,  G06T7/60

摘要： Disclosed is a hierarchical division-based point cloud attribute compression method. For point cloud attribute information, a new hierarchical division based coding scheme is proposed, wherein a frame of point cloud is adaptively divided into a “stripe-macroblock-block” hierarchical structure according to the spatial position and color distribution of the point cloud, and stripes are coded independently from one another, increasing the coding efficiency, enhancing the fault tolerance of a system and improving the performance of point cloud attribute compression. The method comprises: (1) inputting a point cloud; (2) division of a k-dimension (KD) tree structure of the point cloud; (3) continuity analysis of point cloud attribute information; (4) stripe division of the point cloud; (5) division of macroblocks and coding blocks of the point cloud; and (6) intra-frame prediction, transformation, quantification and entropy coding based on a block structure.

公开(公告)号：US10939123B2

公开(公告)日：2021-03-02

申请号：US16626912

申请日：2018-05-15

申请人： Peking University Shenzhen Graduate School

发明人： Ge Li ,  Yi Ting Shao ,  Hong Lian Wei ,  Rong Gang Wang ,  Tie Jun Huang ,  Wen Gao

IPC分类号： H04N19/103 ,  H04N19/159 ,  H04N19/124 ,  H04N19/176 ,  H04N19/61 ,  H04N19/625 ,  H04N19/91 ,  H04N19/96

摘要： Disclosed is a multi-angle adaptive intra-frame prediction-based point cloud attribute compression method. A novel block structure-based intra-frame prediction scheme is provided for point cloud attribute information, where six prediction modes are provided to reduce information redundancy among different coding blocks and improve the point cloud attribute compression performance. The method comprises: (1) inputting a point cloud; (2) performing point cloud attribute color space conversion; (3) dividing a point cloud by using a K-dimensional (KD) tree to obtain coding blocks; (4) performing block structure-based multi-angle adaptive intra-frame prediction; (5) performing intra-frame prediction mode decision; and (6) performing conversion, uniform quantization, and entropy encoding.