3D Point Cloud Encoding and Decoding With Parent-Aware Tables
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Solution Overview
Problem
Existing methods for encoding and decoding three-dimensional data, such as point cloud data, require significant processing resources due to the large amount of data involved, necessitating more efficient compression techniques.
Innovation Solution
A method and device that utilize a three-dimensional data encoding and decoding system which dynamically selects coding tables based on whether a node in an n-ary tree structure refers to a parent node, reducing the number of coding tables needed by using different coding tables for nodes with and without parent references, thereby optimizing processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single coding table is used for all nodes in the n-ary tree structure, then the device complexity is reduced, but the coding efficiency deteriorates due to inability to optimize for different node types
Solution Approach 1:
The patent segments the coding process by dividing nodes into different categories based on their parent node relationships. Nodes are classified as either having a parent node or not having a parent node, and different coding tables are assigned to each category. This segmentation allows the system to use multiple specialized coding tables instead of a single general-purpose table, thereby improving coding efficiency while keeping the complexity manageable through systematic classification.
Solution Approach 2:
The patent implements a dynamic coding table selection mechanism where the appropriate coding table is chosen based on the current node's characteristics (whether it has a parent node or not). This dynamic adaptation allows the encoding process to optimize for each specific node type, improving overall coding efficiency. The decoder similarly dynamically selects the appropriate coding table based on the same node characteristics, ensuring synchronized decoding.
2Productivity
If multiple coding tables are used to optimize coding efficiency for different node types, then the coding efficiency is improved, but the device complexity increases due to managing multiple coding tables
Solution Approach 1:
The patent applies local quality by assigning different coding table characteristics to different node types. Each coding table is optimized for its specific node category (nodes with parent nodes vs. nodes without parent nodes), allowing each table to have specialized properties suited to its intended use. This local optimization improves coding efficiency for each node type while the overall system complexity is managed by limiting the number of distinct table types to match the node categories.
Solution Approach 2:
The patent changes the parameter of coding table selection based on the node's parent node status. By varying which coding table is used according to the node type parameter, the system achieves optimized coding efficiency for different node categories. The encoder and decoder both use this parameter (node type) to select the appropriate coding table, ensuring consistent and efficient processing without requiring complex management of numerous tables.
3Measurement precision
If the coding table selection is based on detailed occupancy states of neighboring nodes, then the coding precision is improved, but the amount of processing increases
Solution Approach 1:
The patent applies partial action by using a flag parameter that indicates whether to perform detailed occupancy state checking of neighboring nodes. When the flag is set to indicate detailed checking is not required, the system uses a simplified coding path that maintains acceptable precision while significantly reducing processing overhead. When high precision is needed, the detailed occupancy state checking is performed. This partial application of the detailed analysis allows the system to balance precision requirements with processing speed based on the specific encoding context.
Data Source
AI summary
A three-dimensional data encoding method includes: encoding a first flag indicating whether a node having a parent node different from a parent node of a current node is to be referred to in encoding of the current node included in an n-ary tree structure of three-dimensional points included in three-dimensional data; selecting a coding table from N coding tables according to occupancy states of neighboring nodes of the current node, and performing arithmetic encoding on information of the current node using the coding table selected, when the first flag indicates that the node is to be referred to; and selecting a coding table from M coding tables according to the occupancy states of the neighboring nodes of the current node, and performing arithmetic encoding on information of the current node using the coding table selected, when the first flag indicates that the node is not to be referred to.