Point Cloud Residual Encoding with Geometric Sign Constraints
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Solution Overview
Problem
Existing point cloud encoding methods require a high number of bits for encoding residual values due to the inefficient process of first arithmetically encoding the sign bit and then the absolute value, leading to low encoding efficiency.
Innovation Solution
A method that calculates distances between points, determines the closest un-encoded point, encodes absolute values, and then encodes signs of residual values based on these distances, optimizing the encoding process by utilizing geometry position relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the sign bit and absolute value of residual values are encoded separately using arithmetic encoding, then the encoding process is simple to implement, but the number of bits required for encoding increases and encoding efficiency decreases
Solution Approach 1:
The patent merges the encoding of sign bits and absolute values into a single unified arithmetic encoding process. Instead of performing separate arithmetic encodings for sign bits and absolute values, the method combines both into one encoding operation that directly produces the encoded residual value, thereby reducing the total number of bits required while maintaining implementation feasibility.
Solution Approach 2:
The patent changes the encoding parameters by using a unified arithmetic encoding model that considers both sign and magnitude together. This involves modifying the probability distribution modeling to account for the joint distribution of sign bits and absolute values, allowing for more efficient bit representation through optimized probability estimates.
2Ease of manufacture
If the sign bit and absolute value of residual values are encoded separately using arithmetic encoding, then the encoding process is simple to implement, but encoding efficiency decreases
Solution Approach 1:
The patent merges the encoding of sign bits and absolute values into a single unified arithmetic encoding process. Instead of performing separate arithmetic encodings for sign bits and absolute values, the method combines both into one encoding operation that directly produces the encoded residual value, thereby reducing the total number of bits required while maintaining implementation feasibility.
Solution Approach 2:
The patent changes the encoding parameters by using a unified arithmetic encoding model that considers both sign and magnitude together. This involves modifying the probability distribution modeling to account for the joint distribution of sign bits and absolute values, allowing for more efficient bit representation through optimized probability estimates.
Data Source
AI summary
A point cloud encoding method, decoding method, encoding device, and decoding device are disclosed. The point cloud encoding method includes calculating a distance from a first point to a parent point of the first point as a first distance; determining a point in un-encoded points closest to the first point as a second point, and calculating residual values on N coordinate components from the second point to the first point; encoding absolute values of the residual values on the N coordinate components from the second point to the first point; encoding signs of the residual values of the second point based on the residual values of the second point and the first distance. The present disclosure utilizes the geometry position relationship between points in a point cloud to encode the absolute values of residual values and the feasible signs of residual values, thereby improving the encoding efficiency of residual values. At the same time, by optimizing the encoding efficiency of residual values, the performance of point cloud prediction tree encoding is improved.