Conditional mixed-state model for structural change analysis from very high resolution optical images

Benjamin Belmudez; Veronique Prinet; Jian-Feng Yao; Patrick Bouthemy; Xavier Descombes

inria-00398062, version 1

Conditional mixed-state model for structural change analysis from very high resolution optical images

Benjamin Belmudez^a^, 1, Veronique Prinet () ¹, Jian-Feng Yao ², Patrick Bouthemy ()^b^, 3, Xavier Descombes ()^b^, 4

2009 IEEE International Geosciences and Remote Sensing Symposium (2009) nc

Résumé : The present work concerns the analysis of dynamic scenes from earth observation images. We are interested in building a map which, on one hand locates places of change, on the other hand, reconstructs a unique visual information of the non-change areas. We show in this paper that such a problem can naturally be takled with conditional mixed-state random field modeling (mixed-state CRF), where the "mixed state" refers to the symbolic or continous nature of the unknown variable. The maximum a posteriori (MAP) estimation of the CRF is, through the Hammersley-Clifford theorem, turned into an energy minimisation problem. We tested the model on several Quickbird images and illustrate the quality of the results.

a – Institute of Automation, Chinese Academy of Sciences
b – INRIA
1 : Laboratoire Franco-Chinois d'Informatique, d'Automatique et de Mathématiques Appliquées (LIAMA)
Institute of Automation, Chinese Academy of Sciences – Chinese Academy of Science (CAS) – Institut national de la recherche agronomique (INRA) – INRIA – Centre de coopération internationale en recherche agronomique pour le développement [CIRAD] – CNRS
2 : Institut de Recherche Mathématique de Rennes (IRMAR)
CNRS : UMR6625 – Université de Rennes 1 – École normale supérieure de Cachan - ENS Cachan – Institut National des Sciences Appliquées (INSA) : - RENNES – Université de Rennes II - Haute Bretagne
3 : VISTAS (INRIA - IRISA)
INRIA – Institut National des Sciences Appliquées (INSA) - Rennes – CNRS : UMR6074 – Université de Rennes 1 – École normale supérieure de Cachan - ENS Cachan
4 : ARIANA (INRIA Sophia Antipolis / Laboratoire I3S)
INRIA – Université Nice Sophia Antipolis [UNS] – CNRS : UMR7271

inria-00398062, version 1
http://hal.inria.fr/inria-00398062
oai:hal.inria.fr:inria-00398062
Contributeur : Xavier Descombes <>
Soumis le : Mercredi 24 Juin 2009, 11:07:59
Dernière modification le : Jeudi 31 Janvier 2013, 14:55:58

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