文章基本信息

标题：Synthetic Aperture Radar Images Segmentation Using Minimum Crossentropy with Gamma Distribution
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作者：Ali El-Zaart
期刊名称：Signal & Image Processing : An International Journal (SIPIJ)
印刷版ISSN：2229-3922
电子版ISSN：0976-710X
出版年度：2015
卷号：6
期号：4
页码：19
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Computer apparition plays the most important role in human perception, which is limited to only the visualband of the electromagnetic spectrum. The need for Radar imaging systems, to recover some sources thatare not within human visual band, is raised. This paper present new algorithm for Synthetic ApertureRadar (SAR) images segmentation based on thresholding technique. Entropy based image thresholding hasreceived 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-modalimages. Our method is derived from Pal method that segment images using cross entropy thresholdingbased on Gamma distribution and can handle bi-modal and multimodal images. Our method is tested usingSynthetic Aperture Radar (SAR) images and it gave good results for bi-modal and multimodal images. Theresults obtained are encouraging.
关键词：SAR images; Segmentation; Gamma distribution; Cross-Entropy.