3D Point Cloud Encoding and Decoding With Adaptive Quantization
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Solution Overview
Problem
Existing three-dimensional data encoding and decoding methods lack efficiency in compressing and transmitting massive point cloud data, necessitating improved coding techniques to reduce data amount and enhance transmission efficiency.
Innovation Solution
A method involving calculating a prediction residual, quantizing it with a first quantization parameter, and generating a bitstream with specific information components based on the difference between quantization parameters, allowing selective inclusion or exclusion of additional data to optimize bitstream size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If point cloud data is compressed using existing encoding methods, then data amount is reduced, but coding efficiency is insufficient
Solution Approach 1:
The patent applies dynamic quantization parameter adjustment where the quantization parameter is not fixed but varies based on the difference between actual and predicted quantization parameters. When the difference exceeds a threshold, a specific flag is set to indicate that the quantization parameter should be adjusted, enabling adaptive compression that balances data reduction with coding efficiency.
Solution Approach 2:
The patent changes the quantization parameter dynamically during encoding based on the difference between actual and predicted values. By adjusting the quantization parameter according to the calculated difference and comparing it against a threshold, the system optimizes the balance between compression ratio and coding efficiency, resolving the contradiction between reducing data amount and maintaining coding efficiency.
2Quantity of substance
If quantization parameter is adjusted to reduce bitstream size, then data compression is improved, but decoding complexity increases
Solution Approach 1:
The patent implements a feedback mechanism where the difference between actual and predicted quantization parameters is calculated and used to determine whether to set a specific flag. This feedback loop allows the decoder to understand the encoding process by comparing expected versus actual quantization parameters, reducing decoding complexity while still achieving compression benefits.
Solution Approach 2:
The patent performs preliminary calculation of the difference between actual and predicted quantization parameters before finalizing the bitstream. By preparing this difference information in advance and using it to set appropriate flags, the decoder can efficiently process the bitstream without complex real-time calculations, thus reducing decoding complexity while maintaining compression efficiency.
3Measurement precision
If prediction residual is quantized with higher precision, then reconstruction accuracy is improved, but bitstream data amount increases
Solution Approach 1:
The patent dynamically adjusts the quantization parameter based on the difference between actual and predicted values. When the difference is small, a coarser quantization can be used to reduce bitstream data amount while maintaining sufficient reconstruction accuracy. When the difference is large, the quantization parameter is adjusted to preserve accuracy, thus resolving the contradiction between precision and data amount through adaptive parameter changes.
Solution Approach 2:
The patent applies dynamic quantization where the quantization parameter is not static but adapts based on the prediction residual characteristics. By making the quantization process dynamic and responsive to the actual data characteristics, the system achieves optimal balance between reconstruction accuracy and bitstream size, preventing both over-compression (losing accuracy) and over-encoding (increasing data amount unnecessarily).
Data Source
AI summary
A three-dimensional data encoding method includes: calculating a prediction residual that is a difference between geometry information of a three-dimensional point included in point cloud data and a predicted value; quantizing the prediction residual using a first quantization parameter; and generating a bitstream including (i) first information indicating the prediction residual quantized, (ii) second information indicating a second quantization parameter, (iii) third information indicating a first difference between the second quantization parameter and the first quantization parameter, (iv) fourth information indicating a first bit count of the first information, and (v) fifth information indicating a second bit count of the fourth information. When the first difference is not zero, the bitstream further includes sixth information indicating an amount of change in the fifth information that is in accordance with the first difference, and when the first difference is zero, the bitstream does not include the sixth information.