Evolutionary image enhancement with user behaviour modeling
Cristian Munteanu, Agostinho C. Rosa · 2001
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 behaviour) 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 th e test set our method obtains better results than the classical histogra equalization technique. Extensive statistics performed, show that multiple regression can be effectively applied to model the user behaviour. 1. INTRODUCTION Genetic Algorithms (GAs) are stochastic search strategies that mimic the evolution of populations of individuals. GAs have been applied in solving difficult optimization tasks pertaining to fields such as pattern recognition, signal processing, image processing, robust c...