Single frame shadow segmentation based on image enhancement for video SAR

As Video synthetic aperture radar (SAR) technology has been developing rapidly in recent years, moving target detection and tracking has gradually become a research hotspot in the field of SAR. Since moving targets in Video SAR produce relatively clear shadows at their real locations, the shadow-based approach provides a new method for ground moving target detection. In this paper, a new approach based on image fusion enhancement is proposed to improve the extraction effect of target shadow in single frame Video SAR image, and the process of shadow segmentation is studied accordingly. First, we use Median Filter to denoise the image, and then use a variety of image enhancement methods to improve the contrast between shadows and background, including piecewise linear stretching, histogram specification, and S-curve enhancement, then use adaptive threshold segmentation algorithm to realize the separation of background and target shadow, finally use morphological processing method to further highlight the target shadow. The effectiveness of the proposed approach is verified on the Video SAR dataset published by Sandia Lab.