Multisource Fusion/Classification Using ICM and DSmT with New Decision Rule

In this paper we introduce a new procedure for classification and change detection by the integration in a fusion process using hybrid DSmT model, both, the contextual information obtained from a supervised ICM classification with constraints and the temporal information with the use of two images taken at two different dates. Secondly, we have proposed a new decision rule based on the DSmP transformation, which is as an alternative and extension and overcoming the inherent limitations of the decision rules thus use the maximum of generalized belief functions. The approach is evaluated on two LANDSAT ETM+ images, the results are promising.