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

Author

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

Author_Institution

Inst. of Autom., Chinese Acad. of Sci., Beijing, China

Volume

2

fYear

2009

fDate

12-17 July 2009

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 Â¿mixed stateÂ¿ 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.

Keywords

geophysical image processing; image reconstruction; maximum likelihood estimation; Hammersley-Clifford theorem; Quickbird images; conditional mixed-state model; earth observation images; maximum a posteriori estimation; random field modeling; structural change analysis; very high resolution optical images; visual information reconstruction; Earth; Energy resolution; Image analysis; Image reconstruction; Image resolution; Image segmentation; Layout; Random variables; Remote sensing; Satellites; Change detection; Conditional random fields; Image analysis; Mixed-state model; Remote sensing;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009

Conference_Location

Cape Town

Print_ISBN

978-1-4244-3394-0

Electronic_ISBN

978-1-4244-3395-7

Type

conf

DOI

10.1109/IGARSS.2009.5418267

Filename

5418267