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文章基本信息

  • 标题:Soft Computing Techniques for Change Detection in remotely sensed images : A Review
  • 本地全文:下载
  • 作者:Madhu Khurana ; Vikas Saxena
  • 期刊名称:International Journal of Computer Science Issues
  • 印刷版ISSN:1694-0784
  • 电子版ISSN:1694-0814
  • 出版年度:2015
  • 卷号:12
  • 期号:2
  • 出版社:IJCSI Press
  • 摘要:With the advent of remote sensing satellites, a huge repository of remotely sensed images is available. Change detection in remotely sensed images has been an active research area as it helps us understand the transitions that are taking place on the Earths surface . This paper discusses the methods and their classifications proposed by various researchers for change detection. Since use of soft computing based techniques are now very popular among research community, this paper also presents a classification based on learning techniques used in soft-computing methods for change detection.
  • 关键词:change detection; COP;kmeans; constrained k;means;k;means; fuzzy k;means; ISODATA; Semi supervised SVM; remote sensing; soft;computing; HMRF
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