Compressive Sensing Compression With Joint Quality Control
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Solution Overview
Problem
Conventional signal compression systems, particularly those using compressive sensing, often require higher bit rates to achieve comparable image quality to traditional methods like JPEG, and lack efficient control over compression ratio and quantization level, leading to suboptimal data rate and quality tradeoffs.
Innovation Solution
Implementing joint image compression and quality control by determining a functional relationship between compression ratio and quantization level, allowing for reduced bit rates while maintaining image quality, using a target indicator to adjust these parameters non-linearly, and employing a sensing matrix to generate compressive sensing measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional compressive sensing is used for signal compression, then compression is achieved, but higher bit rates are required to maintain image quality compared to traditional methods
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the quantization level based on a functional relationship with the compression ratio. This allows the system to optimize the balance between bit rate reduction and image quality preservation by varying the quantization parameter according to the desired compression level, thereby achieving lower bit rates while maintaining acceptable quality.
Solution Approach 2:
The system implements dynamics by using a joint control mechanism that adaptively adjusts both compression ratio and quantization level based on a target indicator. This dynamic adjustment allows the encoder to respond to different quality requirements and transmission conditions, optimizing the bit rate-quality tradeoff in real-time rather than using fixed parameters.
2Ease of operation
If conventional compressive sensing is used, then compression is achieved, but efficient control over compression ratio and quantization level is lacking
Solution Approach 1:
The patent implements feedback control by using a joint control mechanism that monitors the target indicator (either quality or bit rate) and adjusts the compression ratio and quantization level accordingly. This feedback loop ensures that the system maintains optimal performance by continuously adapting parameters based on the desired outcome, providing both ease of operation and transmission efficiency.
Solution Approach 2:
The system achieves universality by designing a control mechanism that can operate with different target indicators (quality-based or bit-rate-based) and adapt to various compression scenarios. This multi-functional approach allows the same encoder to efficiently handle different application requirements without needing separate control systems, thereby improving both ease of operation and productivity.
3Quantity of substance
If quantization level is increased to reduce bit rate, then compression efficiency improves, but decoded signal quality deteriorates
Solution Approach 1:
The patent resolves this contradiction by dynamically changing the quantization level parameter based on its functional relationship with the compression ratio. Instead of using a fixed high quantization level, the system adjusts the quantization parameter adaptively, allowing for lower bit rates when quality requirements are less stringent and higher quality when needed, thereby optimizing the tradeoff between compressed data size and decoded signal quality.
Data Source
AI summary
An encoder determines a compression ratio for compressive sensing and a quantization level used to quantize a media signal based on a target indicator. The encoder accesses compressive sensing measurements performed using the compression ratio and quantizes the compressive sensing measurements based on the quantization level. A decoder receives a compressed signal generated from the signal acquired by the signal acquisition device using the compression ratio and the quantization level. The decoder also receives information indicating the compression ratio or the quantization level. The decoder decompresses the compressed signal based on the compression ratio and the quantization level.