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| HAL : inria-00516333, version 1 |
| DOI : 10.1117/12.865023 |
| Voir la fiche détaillée |  BibTeX,EndNote,... |
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| SPIE Remote Sensing, Toulouse : France (2010) |
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| Classification of very high resolution SAR images of urban areas by dictionary-based mixture models, copulas and Markov random fields using textural features |
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Aurélie Voisin 1Gabriele Moser 2 |
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| (2010) |
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| This paper addresses the problem of the classification of very high resolution (VHR) SAR amplitude images of urban areas. The proposed supervised method combines a finite mixture technique to estimate class-conditional probability density functions, Bayesian classification, and Markov random fields (MRFs). Textural features, such as those extracted by the greylevel co-occurrency method, are also integrated in the technique, as they allow to improve the discrimination of urban areas. Copulas are applied to estimate bivariate joint class-conditional statistics, merging the marginal distributions of both textural and SAR amplitude features. The resulting joint distribution estimates are plugged into a hidden MRF model, endowed with a modified Metropolis dynamics scheme for energy minimization. Experimental results with COSMO-SkyMed and TerraSAR-X images point out the accuracy of the proposed method, also as compared with previous contextual classifiers. |
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| 1 : | ARIANA (INRIA Sophia Antipolis / Laboratoire I3S) |
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INRIA – Université Nice Sophia Antipolis [UNS] – CNRS : UMR7271 |
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| 2 : | Department of Biophysical and Electronic Engineering [Genoa] (DIBE) |
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University of Genoa |
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| 3 : | Faculty of Computational Mathematics and Cybernetics (Lomonosov Moscow State University) |
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Moscow State University |
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| Domaine | : | Informatique/Traitement du signal et de l'image Mathématiques/Statistiques Statistiques/Théorie Sciences de l'ingénieur/Traitement du signal et de l'image |
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| inria-00516333, version 1 | |
| http://hal.inria.fr/inria-00516333 | |
| oai:hal.inria.fr:inria-00516333 | |
| Contributeur : Aurélie Voisin | |
| Soumis le : Jeudi 9 Septembre 2010, 11:50:44 | |
| Dernière modification le : Lundi 19 Novembre 2012, 10:35:19 | |
