HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

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

Benjamin Belmudez 1 Veronique Prinet 1 Jian-Feng Yao 2 Patrick Bouthemy 3 Xavier Descombes 4
3 VISTAS - Spatio-Temporal Vision and Learning
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
4 ARIANA - Inverse problems in earth monitoring
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SIS - Signal, Images et Systèmes
Abstract : 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.
Document type :
Conference papers
Complete list of metadata

Cited literature [12 references]  Display  Hide  Download

Contributor : Xavier Descombes Connect in order to contact the contributor
Submitted on : Wednesday, June 24, 2009 - 11:07:59 AM
Last modification on : Sunday, May 1, 2022 - 3:14:33 AM
Long-term archiving on: : Monday, October 15, 2012 - 2:41:50 PM


Files produced by the author(s)


  • HAL Id : inria-00398062, version 1


Benjamin Belmudez, Veronique Prinet, Jian-Feng Yao, Patrick Bouthemy, Xavier Descombes. Conditional mixed-state model for structural change analysis from very high resolution optical images. 2009 IEEE International Geosciences and Remote Sensing Symposium, Jul 2009, Cape Town, South Africa. ⟨inria-00398062⟩



Record views


Files downloads