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Proceedings Paper

Change detection in remote sensing imagery based on multisimilarity measures fusion
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Paper Abstract

Detecting regions of change in multitemporal remote-sensing images of the same scene taken at different times is of widespread interest in recent years. In this paper, we propose a new change detection method based on a fusion of multisimilarity measures. This fusion is performed in the framework of the Dempster-Shafer evidence theory, which allows you to combine evidence from different sources and arrive at a degree of belief (represented by a belief function) that takes into account all the available evidence. The proposed algorithm is applied to airport change evaluation based on two popular Gray-textural similarity measures: grayscale difference and grayscale ratio. Experimental results confirm the effectiveness of the proposed method.

Paper Details

Date Published: 30 October 2009
PDF: 7 pages
Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74980U (30 October 2009); doi: 10.1117/12.833931
Show Author Affiliations
Weilin Huang, Huazhong Univ. of Science and Technology (China)
Weidong Yang, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 7498:
MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

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