Synthetic aperture radar (SAR) images are widely used in target recognition tasks nowadays. In this letter, we propose an automatic approach for radar shadow detection and extraction from SAR images utilizing geometric projections along with the digital elevation model (DEM) which corresponds to the given geo-referenced SAR image. First, the DEM is rotated into the radar geometry so that each row would match that of a radar line of sight. Next, we extract the shadow regions by processing row by row until the image is covered fully. We test the proposed shadow detection approach on different DEMs and a simulated 1D signals and 2D hills and volleys modeled by various variance based Gaussian functions. Experimental results indicate the proposed algorithm produces good results in detecting shadows in SAR images with high resolution.
Shadow Detection - Examples:
V. B. S. Prasath$ and O Haddad; "Radar shadow detection in synthetic aperture radar images using digital elevation model and projections," Journal of Applied Remote Sensing, 8(1), 083628 (2014). doi:10.1117/1.JRS.8.083628. Preliminary version at arXiv, September 2013, doi:10.48550/arXiv.1309.1830.
Supplementary images, movies, data-sets and MATLAB files are available at figshare:10.6084/m9.figshare.659896
$This work was done while the author was visiting IPAM, University of California Los Angeles, CA, USA. The author thanks the IPAM institute for their great hospitality and support during the visit.