Point Cloud Decoding Context Selection for Azimuth Step Thresholds
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Solution Overview
Problem
The existing method for determining the context in point cloud decoding, specifically in the Angular mode and adaptive azimuth angle quantization mode of Predictive geometry coding, is not optimal for various data sequences, leading to inefficiencies in coding efficiency.
Innovation Solution
A point cloud decoding device and method that utilize a tree synthesizing unit to determine a context based on a threshold related to the number of azimuth angle steps and decoded number of azimuth angle steps, and perform inverse quantization of the radius residual, selecting a 0-th predictor index as a parent node or a correlation predictor, and calculating an optimal predictor for improved coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the context for decoding radius residual is determined using a fixed condition (whether decoded number of azimuth angle steps is 0), then the decoding process is simple, but coding efficiency is not optimized for various data sequences
Solution Approach 1:
The patent introduces dynamic context determination by comparing the decoded number of azimuth angle steps with a threshold value. Instead of using a fixed condition (whether the number is 0), the system adaptively selects context based on the actual data characteristics, allowing the context selection to vary dynamically with different data sequences while maintaining a manageable decision process through threshold-based comparison
2Measurement precision
If inverse quantization of radius residual is performed, then decoding precision is improved, but computational complexity increases
Solution Approach 1:
The patent performs inverse quantization of the radius residual as a preliminary step in the decoding process. By pre-processing the radius residual through inverse quantization before subsequent decoding operations, the system improves the precision of subsequent processing steps while organizing the computational workload in a structured sequence that manages overall complexity
3Measurement precision
If a 0-th predictor index is selected as parent node or correlation predictor, then prediction accuracy is improved, but selection complexity increases
Solution Approach 1:
The patent segments the predictor selection process by introducing a 0-th predictor index that specifically designates parent node or correlation predictor as the prediction target. This segmentation allows the system to focus prediction resources on the most relevant nodes, improving accuracy by isolating and prioritizing specific predictor types while simplifying the overall selection framework through indexed categorization
Data Source
AI summary
The purpose of the present invention is to enable improvement in coding efficiency in an Angular mode and an adaptive azimuth angle quantization mode of Predictive geometry coding. A point cloud decoding device according to the present invention includes: a tree synthesizing unit configured to perform determination based on a threshold related to the number of azimuth angle steps and the decoded number of azimuth angle steps in an Angular mode and an adaptive azimuth angle quantization mode of Predictive geometry coding, and to determine a context to be used for decoding a radius residual based on a result of the determination.