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Multisource classification using ICM and Dempster-Shafer theory

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4 Author(s)
Foucher, S. ; Centre d''Applications et de Recherche en Teledetection, Sherbrooke Univ., Que., Canada ; Germain, Mickael ; Boucher, J.-M. ; Benie, G.B.

We propose to use evidential reasoning in order to relax Bayesian decisions given by a Markovian classification algorithm, the multiscale iterated conditional mode (ICM) algorithm. 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

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Instrumentation and Measurement, IEEE Transactions on  (Volume:51 ,  Issue: 2 )