An adaptive image contrast enhancement based on differential evolution

Tubbs proposed a regularized incomplete beta function to represent some nonlinear transform functions most commonly used in image contrast enhancement. But how to define the coefficients of the beta function adaptively is still a problem. Applying the differential evolution in image contrast enhancement, we utilize the global quickly search ability of the differential evolution algorithm, adaptive mutation, search, at last searches the optimal α, β values of beta function and gets an adaptive contrast enhanced image. To avoid trapping into local optimum, a chaotic differential evolution algorithm is proposed. Experimental results show that the proposed algorithm can find the global optimal α, β in few iterations and save largely computational time and complexity.