SAR Signal Compression Using Block DCT and Parallel Arithmetic Coding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for compressing raw synthetic aperture radar (SAR) data face challenges in achieving high compression ratios without degrading image quality, particularly in low complexity devices, due to the noisy nature of SAR data and high computational complexity of existing techniques.
Innovation Solution
The method involves sampling SAR data into blocks, transforming them into coefficients using a 1D discrete cosine transform, quantizing these coefficients with an adaptive quantization parameter, and applying parallel arithmetic encoding to produce a compressed bitstream, which can be decoded to reconstruct high-resolution SAR images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If block adaptive quantization (BAQ) is used to compress raw SAR data, then compression ratio can be achieved, but image quality degrades substantially when compression ratio exceeds 2:1
Solution Approach 1:
The patent divides the raw SAR data into multiple blocks and applies different quantization strategies to different blocks. By segmenting the data, the system can maintain higher quality in important regions while achieving better compression in less critical areas, thus improving overall compression ratio without uniform quality degradation.
Solution Approach 2:
The patent implements adaptive quantization where the quantization step size varies locally across different blocks based on their statistical properties. This local adaptation allows the system to preserve image quality in regions requiring it while applying more aggressive compression in other regions, resolving the contradiction between compression ratio and quality.
2Loss of substance
If wavelet transform-based compression is applied to raw SAR data, then compression efficiency improves, but computational complexity and memory requirements increase significantly
Solution Approach 1:
The patent employs simpler, computationally less intensive transform methods compared to wavelet transforms. By using more straightforward algorithms that require less computational resources and memory, the system achieves acceptable compression ratios without the high complexity overhead of wavelet-based approaches.
Solution Approach 2:
The patent modifies the transform parameters and block sizes to optimize the balance between compression efficiency and computational complexity. By adjusting these parameters, the system achieves effective compression while keeping the computational burden manageable for low-complexity devices.
3Manufacturing precision
If sampling rate is increased to achieve higher resolution SAR images, then image quality improves, but transmission bandwidth requirements increase
Solution Approach 1:
The patent applies compression techniques to the raw SAR data before transmission. By performing compression in advance, the system reduces the bandwidth requirements for transmitting high-resolution data, allowing high sampling rates to be used for image quality without proportionally increasing transmission bandwidth demands.
Data Source
AI summary
A method compresses synthetic aperture radar (SAR) data by sampling the SAR data into blocks and transforming each block to a corresponding block of transform coefficients. Each block of transform coefficient is quantized according to a quantization parameter to obtain a corresponding block of quantized transform coefficients, which are demultiplexed into sets of blocks of quantized transform coefficients. The quantized transform coefficients in the blocks in each set are arithmetically encoding in parallel according to a probability model to produce an intermediate bitstream for each set of blocks. The encoding of the quantized transform coefficients of one block is independent of the quantized transform coefficients of a successive block. The intermediate of bitstreams are then multiplexed to a compressed bitstream, which can be transmitted, or stored, for subsequent decoding to construct an SAR image.