Hybrid Ant Colony Optimization, Genetic Algorithm, and Simulated Annealing for image contrast enhancement

In this paper, we propose a hybrid algorithm including Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Simulated Annealing (SA) metaheuristics for increasing the contrast of images. In this way, the contrast enhancement is obtained by globally transformation of the input intensities. ACO is used to generate the transfer functions which map the input intensities to the output intensities. SA as a local search method is utilized to modify the transfer functions generated by ACO. GA has the responsibility of evolutionary process of ants' characteristics. The results indicate that the new method performs better than the previously presented methods from the subjective and objective viewpoints.

I. Introduction

CONTRAST enhancement is one of the key steps in image enhancement. It is used for expanding the range of intensities in a gray scale image, revealing parts of image which are seen difficult, or changing the histogram of images so that they can be interpreted more easily by human. In addition to improve visual perception of an image, contrast increasing is a common preprocessing stage of many image processing applications.