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Proceedings Paper

ICA-based multi-temporal multi-spectral remote sensing images change detection
Author(s): Juan Gu; Xin Li; Chunlin Huang; Yiu Yu Ho
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Paper Abstract

Change detection is the process of identifying difference in the scenes of an object or a phenomenon, by observing the same geographic region at different times. Many algorithms have been applied to monitor various environmental changes. Examples of these algorithms are difference image, ratio image, classification comparison, and change vector analysis. In this paper, a change detection approach for multi-temporal multi-spectral remote sensing images, based on Independent Component Analysis (ICA), is proposed. The environmental changes can be detected in reduced second and higher-order dependencies in multi-temporal remote sensing images by ICA algorithm. This can remove the correlation among multi-temporal images without any prior knowledge about change areas. Different kinds of land cover changes are obtained in these independent source images. The experimental results in synthetic and real multi-temporal multi-spectral images show the effectiveness of this change detection approach.

Paper Details

Date Published: 15 April 2008
PDF: 10 pages
Proc. SPIE 6960, Space Exploration Technologies, 69600R (15 April 2008); doi: 10.1117/12.783807
Show Author Affiliations
Juan Gu, Cold and Arid Region Environmental and Engineering Research Institute (China)
Xin Li, Cold and Arid Region Environmental and Engineering Research Institute (China)
Chunlin Huang, Cold and Arid Region Environmental and Engineering Research Institute (China)
Yiu Yu Ho, Univ. of Central Florida (United States)

Published in SPIE Proceedings Vol. 6960:
Space Exploration Technologies
Wolfgang Fink, Editor(s)

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