Radar shadow detection in SAR images using DEM and projections

TL;DR

This paper presents an automatic method for detecting radar shadows in SAR images by combining geometric projections with DEM data, improving shadow extraction accuracy in high-resolution SAR imagery.

Contribution

The novel approach integrates DEM rotation and row-wise processing to enhance radar shadow detection in SAR images, validated on simulated and real data.

Findings

Effective shadow detection in high-resolution SAR images

Robust performance across different DEMs and simulated terrains

Improved accuracy over existing methods

Abstract

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.