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Multiresolution SAR data fusion for unsupervised change detection | IEEE Conference Publication | IEEE Xplore

Multiresolution SAR data fusion for unsupervised change detection


Abstract:

Satellite synthetic aperture radar (SAR) systems currently offer both very high resolutions and multiresolution acquisition capability, thus presenting a great potential ...Show More

Abstract:

Satellite synthetic aperture radar (SAR) systems currently offer both very high resolutions and multiresolution acquisition capability, thus presenting a great potential for environmental monitoring and damage assessment applications. In this framework, change detection methods play a central role. In this paper, a novel unsupervised change detection method is proposed for multitemporal SAR images acquired at multiple resolutions. The method combines Markov random field modeling, line processes, linear mixtures, Bayesian estimation, generalized Gaussian distributions, and graph cuts with the aim of fusing the available multiresolution information to generate a change map at the finest of the observed resolutions. The proposed method is experimentally validated with multitemporal COSMO-SkyMed stripmap and polarimetric data.
Date of Conference: 21-26 July 2013
Date Added to IEEE Xplore: 27 January 2014
Electronic ISBN:978-1-4799-1114-1

ISSN Information:

Conference Location: Melbourne, VIC, Australia

References

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