Compressive Sensing Compression Ratio and Quantization Control
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Solution Overview
Problem
Conventional compressive sensing systems require a significantly higher bit rate than traditional compression techniques to achieve the same quality in reconstructed signals, and they lack effective control over the tradeoff between compression ratio and quantization level, leading to inefficiencies in data transmission and processing.
Innovation Solution
Implementing a joint image compression and quality control system that determines the compression ratio and quantization level based on a target indicator, using a functional relationship between these variables to optimize the product of quantization step size and compression ratio, or their quotient, to achieve reduced bit rates while maintaining image quality, specifically for compressive sensing systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional compressive sensing systems are used, then signal compression is achieved, but the bit rate is significantly higher than traditional compression techniques to achieve the same quality
Solution Approach 1:
The patent changes the fundamental parameters of the compressive sensing system by optimizing the sensing matrix design, measurement sampling rate, and quantization levels. By adjusting these parameters jointly rather than independently, the system achieves lower bit rates while maintaining reconstruction quality, directly resolving the contradiction between bit rate and signal quality.
Solution Approach 2:
The patent introduces dynamic adaptation in the compressive sensing process where the sensing matrix and measurement parameters are adjusted based on the signal characteristics and desired quality level. This dynamic approach allows the system to optimize the tradeoff between bit rate and reconstruction quality in real-time, rather than using fixed parameters.
2Adaptability or versatility
If compressive sensing is implemented, then data compression is achieved, but there is no effective control over the tradeoff between compression ratio and quantization level
Solution Approach 1:
The patent implements feedback mechanisms where the reconstruction quality is evaluated and used to adjust the compression parameters. The system monitors the relationship between compression ratio and quantization level, and dynamically adjusts these parameters to maintain the desired quality while optimizing compression, providing effective control over the tradeoff.
Solution Approach 2:
The patent creates a universal control framework that can manage multiple compression parameters (compression ratio, quantization level, sensing matrix properties) through a unified approach. This multi-functional control system allows users to specify quality requirements and have the system automatically optimize all relevant parameters, simplifying the complexity of managing multiple interdependent parameters.
3Manufacturing precision
If higher quantization levels are used to maintain image quality, then the compressed data size increases, but this leads to higher transmission and processing costs
Solution Approach 1:
The patent optimizes the quantization level parameter in conjunction with other sensing parameters rather than using high quantization levels independently. By changing multiple parameters jointly, the system achieves the required image quality with lower quantization levels, thereby reducing the compressed data size and associated transmission and processing costs.
Solution Approach 2:
The patent applies partial quantization strategies where full high-precision quantization is applied only to the most critical signal components, while less critical components use lower quantization levels. This selective approach maintains perceived image quality while significantly reducing the overall compressed data size.
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.