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

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5 Author(s)
Belmudez, B. ; Inst. of Autom., Chinese Acad. of Sci., Beijing, China ; Prinet, V. ; Jian-Feng Yao ; Bouthemy, P.
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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.

Published in:

Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009  (Volume:2 )

Date of Conference:

12-17 July 2009