An automated GA-based fuzzy image enhancement method

Abstract

This paper presents an automated algorithm for image enhancement. A novel parametric indices of fuzziness (PIF) is introduced, which serves as the optimization criterion of the contrast enhancement procedure. The proposed PIF comprises the Sugeno class of involutive fuzzy complements and the first order fuzzy moment of the image. The PIF as the measure of fuzziness should be maximized, and the maximum of PIF is tuned based on the first-order fuzzy moment of the image. The parameters of the transformation function are found by the genetic algorithm aiming to maximize the PIF. Finally, several experiments are made to demonstrate the efficiency of the proposed method.