Radar shadow detection in SAR images using DEM and projections
This work addresses shadow detection for SAR image analysis, which is incremental as it builds on existing methods using DEMs.
The authors tackled the problem of automatically detecting radar shadows in SAR images by using geometric projections and a digital elevation model (DEM), and the results showed good performance in detecting shadows with high resolution.
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.