Classification of multispectral remote-sensing images by neural networks

Abstract

This paper addresses the classification of multispectral remote-sensing images by the neural-network approach. In particular, an experimental comparison on the performances provided by different neural models for classifying multisensor remote-sensing data is reported. Four neural classifiers are considered in the comparison: the Multilayer Perceptron, Probabilistic Neural Networks, Radial Basis Function networks and a kind of Structured Neural Networks.