Radial basis function for classification of remote sensing images

This work presents a hybrid classifier for multispectral images using radial basis function networks (RBF). A Kohonen self-organization-map is used in substitution of the k-means algorithm in unsupervised stage of training. The algorithm of the pseudo-inverse is used for the determination of the weights of the supervised stage. The architecture proposed reduces the time required for processing. Also, it presents satisfactory results with small training samples. A practical application is accomplished and the results obtained between the classifier of maximum likelihood and the proposed hybrid classifier are compared