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Conditional mixed-state model for structural change analysis from very high resolution optical images
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.
Cited literature [12 references]
https://hal.inria.fr/inria-00398062
Contributor : Xavier Descombes <>
Submitted on : Wednesday, June 24, 2009 - 11:07:59 AM
Last modification on : Wednesday, October 14, 2020 - 4:23:46 AM
Long-term archiving on: : Monday, October 15, 2012 - 2:41:50 PM
Contributor : Xavier Descombes <>
Submitted on : Wednesday, June 24, 2009 - 11:07:59 AM
Last modification on : Wednesday, October 14, 2020 - 4:23:46 AM
Long-term archiving on: : Monday, October 15, 2012 - 2:41:50 PM
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belmudez-igarss09-crp3376.pdf
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