Combining multiobjective fuzzy clustering and probabilistic ANN classifier for unsupervised pattern classification: Application to satellite image segmentation

An important approach to unsupervised pixel classification in remote sensing satellite imagery is to use clustering in the spectral domain. In this article, a recently proposed multiobjective fuzzy clustering scheme has been combined with artificial neural networks (ANN) based probabilistic classifier to yield better performance. The multiobjective technique is first used to produce a set of non-dominated solutions. A part of these solutions having high confidence level are then used to train the ANN classifier. Finally the remaining solutions are classified using the trained classifier. The performance of this technique has been compared with that of some other well- known algorithms for two artificial data sets and a IRS satellite image of the city of Calcutta.

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