An Optimal Fuzzy System for Color Image Enhancement

A Gaussian membership function is proposed to fuzzify the image information in spatial domain. We introduce a global contrast intensification operator (GINT), which contains three parameters, viz., intensification parameter t, fuzzifier f_h, and the crossover point mu_c, for enhancement of color images. We define fuzzy contrast-based quality factor Q_f and entropy-based quality factor Q_e and the corresponding visual factors for the desired appearance of images. By minimizing the fuzzy entropy of the image information with respect to these quality factors, the parameters t, f_h, and mu_c are calculated globally. By using the proposed technique, a visible improvement in the image quality is observed for under exposed images, as the entropy of the output image is decreased. The terminating criterion is decided by both the visual and quality factors. For over exposed and under plus over exposed images, the proposed fuzzification function needs to be modified by taking maximum intensity as the fourth parameter. The type of the images is indicated by the visual factor which is less than 1 for under exposed images and more than 1 for over exposed images