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      Change Detection and Analysis of High Resolution Synthetic Aperture Radar Images Based on Bag-of-words Model

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          Abstract

          This paper discusses the change detection in high-resolution SAR image interpretation. Referring to the unfavorable elements in the change detection and the status quo, this paper focuses on resolving the semantic information deficiency problem in SAR image change detection. A method named change detection base on Bag of Words Model (BoWM) is proposed. By using the BoWM, two visual histograms of two different temporal images are obtained, and the histogram difference, which contains semantic information, is defined as the change vector. By analyzing the change vector and combining it with the statistical change detection method, the semantic analysis and interest change-type detection of the change area can be obtained. Experiments show that the proposed method may be applicable to the semantic analysis of the change area in high-resolution SAR images.

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          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 February 2014
          : 3
          : 1
          : 101-110
          Affiliations
          [1 ] Shanghai Jiao Tong University Institute for Sensing and Navigation
          Article
          389475c6c01c4ae695b77c6cde4541a1
          10.3724/SP.J.1300.2014.13134

          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/

          Categories
          Technology (General)
          T1-995

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