Paper
30 October 2009 Change detection in remote sensing imagery based on multisimilarity measures fusion
Author Affiliations +
Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 74980U (2009) https://doi.org/10.1117/12.833931
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China
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.
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Weilin Huang and Weidong Yang "Change detection in remote sensing imagery based on multisimilarity measures fusion", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74980U (30 October 2009); https://doi.org/10.1117/12.833931
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KEYWORDS
Image fusion

Remote sensing

Current controlled current source

Data processing

Probability theory

Artificial intelligence

Associative arrays

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