Evidential Reasoning Based Classifier Combination for an Optimal Remote Sensing Image Classification

The work presented here addresses the problem of the enhancement of the remote sensing image classification. For that, an evidential reasoning based classifier combination method is proposed. The originality of the work lies in the fact that the method treats the outputs of the classifiers by completely ignoring the internal characteristics of the latter. The method is thus general and applicable to any type of classifier. It cumulates the advantages of each classifier without cumulating the disadvantages of them. It overcomes the disadvantages of the remote sensing image classification methods developed in the literature. Thus, it constitutes a powerful tool for several remote sensing image processing applications