Fuzzy Rules and Evidence Theory for Satellite Image Analysis

Design of a fuzzy rule based classifier is proposed. The performance of the classifier for multispectral satellite image classification is improved using DempsterShafer theory of evidence that exploits information of the neighboring pixels. The classifiers are tested rigorously with two known images and their performance are found to be better than the results available in the literature. We also demonstrate the improvement of performance while using D-S theory along with fuzzy rule based classifiers over the basic fuzzy rule based classifiers for all the test cases.