Joint SAR image compression and coherent change detection

Fine details revealed by synthetic aperture radar (SAR) coherent change detection (CCD), such as foot prints, require SAR imagery with both high resolution and precision. These large data requirements are at odds with the low bandwidths often available for SAR change detection systems such as those that utilize small unmanned aerial vehicles (UAVs). Here we investigate the interplay between SAR data compression and SAR CCD performance. As the data are compressed further, the ability to detect changes decreases. However, there is redundant information contained in SAR imagery that is not necessary for change detection, and removing it makes SAR compression possible. In this paper, we introduce a new model-based compression method that leverages the known distribution of SAR data for a compact storage, while improving change detection performance. We show experimentally that the CCD using the decompressed SAR pair after our proposed method not only yields significant improvement in change detection over the CCD using the decompressed SAR after block adaptive quantization (BAQ) method, but also over the CCD using the original SAR data. Experimental results are presented to show the effectiveness and robustness of the proposed algorithm for SAR compression and change detection.