I ' ABSTRACTA new methodolo& is presented for classifying remotelysensed imagery. This technique is meant to be locally-adaptive, supports non-gaussiarl statistics, and still allows one to generate an automatic classification. The new methodology requires training data, just as the standard technique does, but it uses an unsupervised techniqhe (ISODATA) with which to first classify the data. The clusters from the unsupervised step are used
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