Synthetic Aperture Radar Images Segmentation Using Minimum Crossentropy with Gamma Distribution

Abstract

Computer apparition plays the most important role in human perception, which is limited to only the visual band of the electromagnetic spectrum. The need for Radar imaging systems, to recover some sources that are not within human visual band, is raised. This paper present new algorithm for Synthetic Aperture Radar (SAR) images segmentation based on thresholding technique. Entropy based image thresholding has received sustainable interest in recent years. It is an important concept in the area of image processing. Pal (1996) proposed a cross entropy thresholding method based on Gaussian distribution for bi-modal images. Our method is derived from Pal method that segment images using cross entropy thresholding based on Gamma distribution and can handle bi-modal and multimodal images. Our method is tested using Synthetic Aperture Radar (SAR) images and it gave good results for bi-modal and multimodal images. The results obtained are encouraging.