Prediction Residual Encoding With Adaptive Side Information Coding
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Solution Overview
Problem
Conventional lossless compression encoding methods for time-series signals do not effectively compress side information, such as the Rice parameter, leading to suboptimal encoding efficiency.
Innovation Solution
A method that performs prediction analysis on time-series signals to generate prediction residuals and sets an integer separation parameter based on their magnitude, using a side information code table that varies with prediction effectiveness for variable length coding of side information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional lossless compression encoding methods are used for time-series signals, then the original signal can be reproduced losslessly, but the side information such as Rice parameter is not effectively compressed leading to suboptimal encoding efficiency
Solution Approach 1:
The patent applies parameter changes by selecting different side information code tables based on prediction gain values. Instead of using a fixed code table for encoding side information, the system dynamically changes the code table selection according to the prediction effectiveness, thereby optimizing the compression ratio for side information while maintaining lossless reconstruction capability
Solution Approach 2:
The patent implements dynamics by making the code table selection adaptive and variable rather than static. The side information code table is selected dynamically based on the calculated prediction gain, allowing the encoding system to adapt to different signal characteristics and prediction effectiveness levels, thus improving overall encoding efficiency
2Ease of manufacture
If a fixed code table is used for variable length coding of side information, then the encoding process is simple, but the average code length for side information is not minimized
Solution Approach 1:
The patent changes the parameter of code table selection based on prediction gain. By selecting different code tables corresponding to different prediction gain ranges, the system optimizes the average code length for side information without significantly complicating the encoding process, as the selection is based on a straightforward prediction analysis
Data Source
AI summary
To improve the encoding compressibility of prediction residuals. An encoder performs prediction analysis of input time-series signals to generate prediction residuals expressed by integers, and sets an integer separation parameter that depends on the amplitude of the prediction residuals for each certain time segment. The encoder selects a side information code table corresponding to an index representing the prediction effectiveness of the time-series signals from a set of side information code tables including a side information code table used for variable length coding of side information corresponding to the separation parameter. A decoder selects a side information code table corresponding to the index representing the prediction effectiveness of the time-series signals from a set of side information code tables including a side information code table used for decoding of a code corresponding to the side information corresponding to the integer separation parameter corresponding to the magnitude of the prediction residuals.