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A fuzzy supervised classification method in which geographical information is represented as fuzzy sets is described. The algorithm consists of two major steps: the estimate of fuzzy parameters from fuzzy training data, and a fuzzy partition of spectral space. Partial membership of pixels allows component cover classes of mixed pixels to be identified and more accurate statistical parameters to be generated, resulting in a higher classification accuracy. Results of classifying a Landsat MSS image are presented, and their accuracy is analyzed.>
F. Wang (1990) studied this question.