Selecting parameter values for mahalanobis distance fuzzy classifiers

The fuzzy c-means clustering algorithm, and a related supervised classifier, require the a priori selection of a weighting parameter called the fuzzy exponent. This paper investigates suitable values of this fuzzy exponent using the criterion that fuzzy set memberships reflect class proportions in the mixed pixels of a remotely sensed image.