KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Change Detection in Bitemporal Remote Sensing Images by using Feature Fusion and Fuzzy C-Means

  • Wang, Xin (College of Computer and Information, Hohai University) ;
  • Huang, Jing (Business School of Hohai University) ;
  • Chu, Yanli (College of Computer and Information, Hohai University) ;
  • Shi, Aiye (College of Computer and Information, Hohai University) ;
  • Xu, Lizhong (College of Computer and Information, Hohai University)
  • Received : 2017.06.14
  • Accepted : 2017.11.02
  • Published : 2018.04.30
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Abstract

Change detection of remote sensing images is a profound challenge in the field of remote sensing image analysis. This paper proposes a novel change detection method for bitemporal remote sensing images based on feature fusion and fuzzy c-means (FCM). Different from the state-of-the-art methods that mainly utilize a single image feature for difference image construction, the proposed method investigates the fusion of multiple image features for the task. The subsequent problem is regarded as the difference image classification problem, where a modified fuzzy c-means approach is proposed to analyze the difference image. The proposed method has been validated on real bitemporal remote sensing data sets. Experimental results confirmed the effectiveness of the proposed method.

Keywords

References

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