Target Segmentation Method in SAR Images Based on Appearance Conversion Machine

Abstract

Differences between the spatial pattern (pixel intensity and distribution) of targets and clutter allow target segmentation to be achieved by analyzing spatial patterns in Synthetic Aperture Radar (SAR) images. This paper thus proposes a target segmentation method for SAR images based on the appearance conversion machine theory. The proposed method analyses the spatial patterns in SAR images and calculates the degree of similarity between the SAR image and the reference clutter images. Subsequently, regions that show high similarity to reference clutter images are erased so that segmentation can be achieved. To evaluate the degree of similarity, we also use an automatic threshold selection method based on the cumulative histogram of the similarity imge. Experimental results using simulation and real data verify the effectiveness of the proposed method.

Keywords

• Synthetic Aperture Radar (SAR)
• Target segmentation
• Appearance Conversion Machine (ACM)
• Extreme Learning Machine (ELM)