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Change detection in multisensor SAR images using bivariate gamma distributions

Chatelain, Florent and Tourneret, Jean-Yves and Inglada, Jordi Change detection in multisensor SAR images using bivariate gamma distributions. (2008) IEEE Transactions on Image Processing, 1 (3). 249-258. ISSN 1057-7149

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Official URL: http://dx.doi.org/10.1109/TIP.2008.916047


This paper studies a family of distributions constructed from multivariate gamma distributions to model the statistical properties of multisensor synthetic aperture radar (SAR) images. These distributions referred to as multisensor multivariate gamma distributions (MuMGDs) are potentially interesting for detecting changes in SAR images acquired by different sensors having different numbers of looks. The first part of the paper compares different estimators for the parameters of MuMGDs. These estimators are based on the maximum likelihood principle, the method of inference function for margins and the method of moments. The second part of the paper studies change detection algorithms based on the estimated correlation coefficient of MuMGDs. Simulation results conducted on synthetic and real data illustrate the performance of these change detectors.

Item Type:Article
Additional Information:The original publication is available on http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=83
HAL Id:hal-03579543
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
French research institutions > Centre National d'Études Spatiales - CNES (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Laboratory name:
Deposited On:13 May 2008 07:42

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