Mr. Arvind Thiagarajan Profile

Arvind Thiagarajan

at The Advanced Technology Group

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Proceedings Article | 3 May 2012 Paper

Preliminary results of SAR image compression using MatrixView on coherent change detection (CCD) analysis

Lawrence Gresko, LeRoy Gorham, Arvind Thiagarajan

Proceedings Volume 8394, 839405 (2012) https://doi.org/10.1117/12.925068

KEYWORDS: Image compression, Charge-coupled devices, Synthetic aperture radar, Chromium, Data modeling, Coherence (optics), Image processing, CCD image sensors, Image quality, Interferometry

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An investigation was made into the feasibility of compressing complex Synthetic Aperture Radar (SAR) images using MatrixView^TM compression technology to achieve higher compression ratios than previously achieved. Complex SAR images contain both amplitude and phase information that are severely degraded with traditional compression techniques. This phase and amplitude information allows interferometric analysis to detect minute changes between pairs of SAR images, but is highly sensitive to any degradation in image quality. This sensitivity provides a measure to compare capabilities of different compression technologies. The interferometric process of Coherent Change Detection (CCD) is acutely sensitive to any quality loss and, therefore, is a good measure by which to compare compression capabilities of different technologies. The best compression that could be achieved by block adaptive quantization (a classical compression approach) applied to a set of I and Q phased-history samples, was a Compression Ratio (CR) of 2x. Work by Novak and Frost [3] increased this CR to 3-4x using a more complex wavelet-based Set Partitioning In Hierarchical Trees (SPIHT) algorithm (similar in its core to JPEG 2000). In each evaluation as the CR increased, degradation occurred in the reconstituted image measured by the CCD image coherence. The maximum compression was determined at the point the CCD image coherence remained > 0.9. The same investigation approach using equivalent sample data sets was performed using an emerging technology and product called MatrixView^TM. This paper documents preliminary results of MatrixView's compression of an equivalent data set to demonstrate a CR of 10-12x with an equivalent CCD coherence level of >0.9: a 300-400% improvement over SPIHT.

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