Image Enhancement Using Robust Meta Heuristic Computing Algorithm

Abstract

In this paper, we propose a Simulated Annealing (SA) and Differential Evolution (DE) algorithm metaheuristics for increasing the contrast of images. In this way, contrast enhancement is obtained by global transformation of the input intensities. Here these algorithms are used to generate the transfer functions which map the input intensities to the output intensities. Comparison with other conventional optimization algorithm, like GA (Genetic Algorithm), PSO (Particle Swarm Optimization) etc. these meta heuristic algorithm (SA & DE) are very robust and takes very less computational time to achieve the global optimal value Simulated annealing as a local search method is utilized to revise the transfer functions of the image. The employed fitness function operates automatically and tends to provide a balance between contrast and naturalness of images. The results indicate that the new method achieves images with higher contrast with minimal CPU time and may be suitable option for the current industrial need.