This paper proposes an interactive change detection method in multitemporal remote sensing images. The user needs to input markers related to change and no-change classes in the Difference image. Then this information is used by a support vector machine classifier to generate a spectral-change map. Then two different solutions based on Markov Random Field or Level-Set methods are used to incorporate the spatial contextual information in the decision process. While the Markov Random Field method is region driven, the level-set method exploits both region and contour for performing the segmentation task. Experiments conducted on two real remote-sensing images confirm the promising capabilities of the proposed method.
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