Point Cloud Chroma Subsampling for Lower Attribute Data Volume
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Solution Overview
Problem
Existing point cloud encoding methods encode all 3-channel color information for each point, leading to an increase in data volume, which is inefficient.
Innovation Solution
Implement chroma subsampling in point clouds by preserving chroma signals at a predetermined ratio for specific points and discarding others, while encoding luma signals for all points, and using interpolation to reconstruct full-resolution chroma signals at the decoder.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If chroma signals of all points are encoded, then color information completeness is improved, but data volume increases
Solution Approach 1:
The patent extracts and encodes only the chroma signals from points satisfying a predetermined condition (e.g., points at specific spatial locations or points with high color significance), while discarding chroma signals from other points. This selective extraction reduces the quantity of encoded data while preserving essential color information where it matters most.
Solution Approach 2:
The patent applies different encoding strategies to different regions or types of points in the point cloud. Points satisfying the predetermined condition receive full chroma signal encoding, while other points use interpolated or discarded chroma signals. This local differentiation optimizes the balance between color information quality and data volume.
2Measurement precision
If chroma signals of all points are encoded, then color accuracy is improved, but encoding complexity increases
Solution Approach 1:
The encoding device extracts only chroma signals from points satisfying the predetermined condition, avoiding the complexity of encoding all chroma signals while maintaining color accuracy at critical locations. The extraction criterion filters out redundant encoding operations.
Solution Approach 2:
The patent performs preliminary classification of points to identify which points satisfy the predetermined condition before encoding. This preliminary action organizes the encoding process, allowing the device to focus computational resources on critical points and reduce overall encoding complexity.
3Quantity of substance
If chroma signals are subsampled at a predetermined ratio, then data volume is reduced, but color information completeness deteriorates
Solution Approach 1:
The patent applies chroma signal preservation selectively to points satisfying the predetermined condition, while allowing subsampling or discarding for other points. This local quality approach ensures color information completeness is maintained where it matters most while achieving data volume reduction overall.
Solution Approach 2:
The patent uses an intermediary mechanism (the predetermined condition criterion) to mediate between the need for color information completeness and data volume reduction. Points satisfying the condition act as intermediaries that preserve color fidelity, while the overall system achieves compression through selective processing.
Data Source
AI summary
Encoding efficiency for attribute information in point cloud information is improved.A point cloud encoding device includes a subsampling unit configured to preserve chroma signals of some points in a point cloud to be encoded and discard chroma signals of remaining points other than those points, and an attribute information encoding unit configured to encode the chroma signals of those points in the point cloud to be encoded and luma signals of all points.