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 .