MULTISPECTRAL IMAGE SEGMENTATION USING ART1/ART2 NEURAL NETWORKS

摘要

In this research, remote-sensing multispectral images are analyzed and interpreted by means of a neural network approach. In particular, the advantages found by using Adaptive Resonance Theory network of the data are shown and commented. We used the ART1 and ART2 structures that accept binary data and continuous-value data, so that each input can be for each pixel directly the vector of the gray level values at each band. This choice is due to the attempt to simplify algorithm as much as possible. Experiments carried out with ADEOS and LANDSAT-5 images are given.