Evolutionary image enhancement with user behavior modeling

In this paper we present a novel method for image enhancement of gray-scale images based on the simulation of evolution. Our method employs Genetic Algorithms to evolve the shape of the contrast curve in the image, while attempting to partially automate the subjective process of image evaluation (e.g. user behavior) by performing multiple regression on fitness values. Results obtained show the robustness and efficiency of the evolutive method for image enhancement. For several images in the test set our method obtains better results than the classical histogram equalization technique. Extensive statistics performed, shows that multiple regression can be effectively applied to model the user behavior.