AUTOMATIC SELECTION OF OBJECT ENHANCEMENT OPERATOR WITH QUANTITATIVE JUSTIFICATION BASED ON FUZZY SET THEORETIC MEASURES

An algorithm for automatic selection of a nonlinear function appropriate for object enhancement of a given image is described. The algorithm does not need iterative visual interaction and prior knowledge of image statistics in order to select the transformation function for its optimal enhancement. A quantitative measure for evaluating enhancement equality has been provided based on fuzzy geometry. The concept of minimizing fuzziness (ambiguity) in both grayness and in spatial domain, as used by Pal and Rosenfeld [4], has been adopted. The selection criteria are further justified from the point of bounds of the membership function. The effectiveness of the algorithm is demonstrated for unimodal, multimodal and right skewed images when possible nonlinear transformation functions are taken into account.