POINT CLOUD DECODING METHOD, POINT CLOUD ENCODING METHOD, AND DECODER

    公开(公告)号:US20230326090A1

    公开(公告)日:2023-10-12

    申请号:US18335714

    申请日:2023-06-15

    IPC分类号: G06T9/40 G06T17/00

    摘要: A point cloud decoding method, a point cloud encoding method, and a decoder are provided in implementation of the disclosure. The decoding method includes the following. A bitstream of a point cloud is parsed to obtain an initial reconstructed value of attribute information of a target point in the point cloud. The initial reconstructed value is converted into an initial luma value and an initial chroma value. A final chroma value is obtained by filtering the initial chroma value with a Kalman filtering algorithm. A final reconstructed value of the attribute information of the target point is obtained based on the final chroma value and the initial luma value. A decoded point cloud is obtained according to the final reconstructed value of the attribute information of the target point.

    POINT CLOUD CODING METHOD, ENCODER AND DECODER

    公开(公告)号:US20230316586A1

    公开(公告)日:2023-10-05

    申请号:US18329927

    申请日:2023-06-06

    IPC分类号: G06T9/00 G06T9/40

    CPC分类号: G06T9/001 G06T9/40

    摘要: A point cloud coding method is provided. The method includes the following. Occupancy bit information of neighbouring nodes of a current node is obtained. A context model is determined according to the occupancy bit information of the neighbouring nodes. Related information of the current node is entropy encoded with the context model and signalled into a bitstream, where the related information includes at least one of flag information of a single child node or coordinate information of the single child node.

    DATA COMPRESSION
    29.
    发明公开
    DATA COMPRESSION 审中-公开

    公开(公告)号:US20230267650A1

    公开(公告)日:2023-08-24

    申请号:US17676706

    申请日:2022-02-21

    摘要: The present concepts relate to lossless data compression techniques for reducing the size of a data structure. Certain data in the data structure that can be either recovered from another source or rebuilt from other available information may be removed from the data structure. To further reduce data size, the retained data in the data structure may be packed into a smaller-bit encoding data type. Additionally, to reduce the data size even more, the packed data may be zipped using a lossless data compression algorithm. To regain the original data structure, the process may be reversed. The zipped data may be unzipped using a lossless data decompression algorithm. The packed data may be unpacked into the original bit-sized data encoding. The removed data may be restored by either recovering it from another source or rebuilding it from other available information.