Abstract

In the use of synthetic discriminant functions for the classification of scenes, the specification of output correlation values by the user is of utmost importance, since the filter performance significantly depends on these values. A systematic procedure for determining these values is developed in this paper. The proposed technique provides an optimal selection of the output correlation values in the sense that they result in a minimization of the probability of error in detection. Specific algorithms are developed for various situations of practical importance, which include the general multiple-class, multiple-training image problems. Several numerical examples are included to illustrate the performance improvements that result from employment of the proposed scheme.

© 1990 Optical Society of America

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