Multisource classification using ICM and Dempster-Shafer theory

We propose to use evidential reasoning in order to relax Bayesian decisions given by a Markovian classification algorithm (ICM). The Dempster–Shafer rule of combination enables us to fuse decisions in a local spatial neighborhood which we further extend to be multisource. This approach enables us to more directly fuse information. Application to the classification of very noisy images produces interesting results.