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      Target Segmentation Method in SAR Images Based on Appearance Conversion Machine

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          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.

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          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 August 2016
          : 5
          : 4
          : 402-409
          Affiliations
          [1 ] Harbin Institute of Technology, Harbin 150001, China
          Article
          eb0855a445ea4a73bc205ec1932c59c7
          10.12000/JR16066
          629042dd-3f40-4512-bd49-8658e6058747

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          History
          Categories
          Technology (General)
          T1-995

          Remote sensing,Electrical engineering
          Extreme Learning Machine (ELM),Appearance Conversion Machine (ACM),Target segmentation,Synthetic Aperture Radar (SAR)

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