Adaptive Frame Encoding Mode Selection for Compression Efficiency
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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 and may not be suitable for all input signals, leading to degraded compression efficiency or failure in encoding.
Innovation Solution
A generic encoding method and apparatus that dynamically switch among different encoding modes based on input signal frames and policies, estimating coding demand values for various modes to select the optimal encoding mode, thereby enhancing compression efficiency while maintaining lower complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If every sample of the signal is compressed and encoded using the same compression mode, then a larger compression ratio can be achieved, but the signal characteristics are neglected and compression efficiency is degraded severely
Solution Approach 1:
The patent segments the signal into multiple frames and further divides each frame into multiple sub-frames. This segmentation allows different encoding modes to be applied to different segments based on their specific characteristics, resolving the contradiction between achieving high compression ratio and adapting to signal characteristics. The signal is processed in manageable chunks rather than as a whole, enabling localized optimization.
Solution Approach 2:
The patent implements dynamic mode selection where the encoding mode is not fixed but changes adaptively based on the characteristics of each signal frame. The system dynamically switches between different encoding modes (e.g., ACELP, FBLP, SMG) according to the signal properties detected in each frame, making the compression process flexible and adaptive rather than static and uniform.
2Productivity
If lossless compression technique is used to enhance coding efficiency, then bandwidth is saved and lossless re-constructed signal is generated, but the inherent entropy between signals causes significant variation in compression efficiency and high complexity is required for real-time transmission
Solution Approach 1:
The patent creates a universal encoding framework that can handle multiple types of signals and multiple encoding modes within a single system. The ACELP encoder can operate in different modes (standard mode, low complexity mode, very low complexity mode) and the system can also switch to FBLP or SMG modes as needed. This multi-functionality allows the system to maintain high coding efficiency across different signal types while managing complexity through mode selection.
Solution Approach 2:
The patent changes operational parameters dynamically by switching between different encoding modes with varying complexity levels. The system can adjust the encoding parameters based on the signal characteristics and requirements, selecting from multiple complexity levels (standard, low, very low) to optimize the trade-off between coding efficiency and device complexity for real-time transmission.
3Loss of substance
If existing lossless compress technique is applied to audio storage to acquire higher compression ratio, then compression efficiency is improved, but the complexity is significantly increased
Solution Approach 1:
The patent implements dynamic mode selection that adapts to signal characteristics, allowing the system to achieve high compression ratios only when appropriate modes are selected rather than applying complex algorithms universally. The complexity is dynamically adjusted based on the signal type and characteristics, avoiding unnecessary computational overhead for signals that don't benefit from complex processing.
Solution Approach 2:
The patent provides multiple encoding modes including very low complexity mode and low complexity mode that use simpler, less computationally intensive algorithms. These simpler modes serve as alternatives to the full-featured standard mode, allowing the system to achieve adequate compression with reduced complexity when appropriate, effectively providing a simplified version for cases where high compression ratio is less critical than computational efficiency.
Data Source
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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.