Adaptive Signal Encoding Mode Selection for Real-Time Compression
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Solution Overview
Problem
Existing lossless compression techniques face challenges in achieving a balance between coding efficiency and complexity, particularly in real-time transmission, as they often neglect signal characteristics, leading to inefficient compression modes and potential failure in encoding certain signals.
Innovation Solution
A generic encoding method that analyzes signal characteristics to select the most suitable encoding mode, estimating coding demand values for multiple modes and switching between them to optimize compression efficiency while maintaining lower complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If every sample of the signal is compressed and encoded using the same compression mode, then the compression process is simple, but the compression efficiency is degraded severely and signal characteristics are neglected
Solution Approach 1:
The patent segments the signal processing into multiple encoding modes (first encoding mode and second encoding mode) and divides the signal into frames. Different encoding modes are applied to different signal frames based on their characteristics, rather than using a single uniform encoding approach for all samples. This segmentation allows the system to adapt to varying signal characteristics while maintaining manageable complexity through structured mode selection.
Solution Approach 2:
The patent implements dynamic mode selection where the encoding mode is not fixed but changes based on signal characteristics analysis. The system dynamically switches between the first encoding mode and second encoding mode by analyzing signal properties and selecting the most appropriate mode for each signal frame, enabling adaptive compression that responds to changing signal conditions.
2Productivity
If a generic encoding method is introduced for different input signals, then the compression efficiency is enhanced, but the complexity increases
Solution Approach 1:
The patent changes the parameter of encoding mode selection based on signal characteristics. By analyzing properties such as signal variance, correlation, and other statistical features, the system adjusts which encoding mode is applied to each signal frame. This parameter-based adaptation enhances compression efficiency for different signal types while keeping the complexity increase manageable through systematic parameter analysis rather than complex algorithmic changes.
3Productivity
If lossless compression techniques are applied to enhance coding efficiency, then bandwidth is saved and lossless reconstruction is achieved, but the complexity requirement increases significantly for real-time transmission
Solution Approach 1:
The patent applies segmentation by dividing the signal into frames and further segmenting the encoding approaches into multiple modes. This frame-based segmentation with mode diversity allows lossless compression to be applied selectively rather than uniformly, reducing the overall computational burden while maintaining the lossless reconstruction capability where needed.
Solution Approach 2:
The patent creates a universal encoding framework that can handle different signal types and characteristics through multiple encoding modes. This multi-functional encoding system can adapt to various signal conditions (different correlation properties, variances, and characteristics) within a single unified architecture, achieving lossless compression across diverse signals without requiring separate specialized systems for each case.
Data Source
AI summary
The present invention relates to encoding technology. The encoding method includes selecting a second encoding mode for encoding an input frame signal according to an analysis on signal characteristic of the input frame signal; obtaining coding demand values for a preset first encoding mode and the second encoding mode which are used to encode the input frame signal; determining, from the above encoding modes based on the coding demand values, an encoding mode for encoding the input frame signal; and multiplexing information of the determined encoding mode and encoded data which are encoded according to the determined encoding mode. Hence, the compatibility and the prioritization in terms of the encoding modes can be achieved.