Point Cloud Context Coding Using Reference Child Node Occupancy
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Solution Overview
Problem
In existing point cloud coding frameworks, context information lacks actual meaning, leading to reduced encoding performance due to the use of invalid information.
Innovation Solution
Determine occupancy information of reference child nodes, identify preset identifier information based on this, and use it to construct accurate context information for encoding and decoding syntax elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If context information is constructed using existing methods, then encoding is performed, but the context information lacks actual meaning and reduces encoding performance
Solution Approach 1:
The patent changes the parameters used to construct context information from arbitrary or invalid identifiers to meaningful occupancy information of reference child nodes. By modifying what data is used (from invalid identifiers to actual occupancy patterns), the context information gains real meaning that improves encoding performance.
Solution Approach 2:
The patent extracts only the meaningful occupancy information from the node structure to form context information, discarding invalid or meaningless identifier data. This extraction of essential meaningful data while removing useless information resolves the contradiction by ensuring context contains only relevant, meaningful content.
2Measurement precision
If occupancy information of reference child nodes is used to construct context information, then encoding accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent performs preliminary determination of occupancy information for reference child nodes before constructing the final context information. By pre-calculating and storing the occupancy patterns of neighboring nodes, the system prepares meaningful context data in advance, which simplifies the main encoding process while maintaining high accuracy.
Solution Approach 2:
The patent segments the context construction process into distinct steps: determining occupancy information of individual reference child nodes, then combining these to form preset identifier information, and finally using this to construct the complete context information. This segmentation makes the complex process more manageable and systematic.
Data Source
AI summary
Embodiments of this application disclose an encoding method, a decoding method, a code stream, an encoder, a decoder, and a storage medium. The decoding method comprises: determining occupancy information of reference child nodes of a current child node; determining preset identification information of the current child node on the basis of the occupancy information of the reference child nodes; determining context information of the current child node on the basis of the preset identification information; and decoding, on the basis of the context information, a syntactic element to be decoded of the current child node, and determining the value of said syntactic element.


