Title: Comparative analysis of evolutionary algorithms for image enhancement

Authors: Anupriya Gogna; Akash Tayal

Addresses: ECE Department, Indira Gandhi Institute of Technology, GGSIP University, Kashmere Gate, Delhi-110006, India. ' ECE Department, Indira Gandhi Institute of Technology, GGSIP University, Kashmere Gate, Delhi-110006, India

Abstract: Evolutionary algorithms are metaheuristic techniques that derive inspiration from the natural process of evolution. They can efficiently solve (generate acceptable quality of solution in reasonable time) complex optimisation (NP-hard) problems. In this paper, automatic image enhancement is considered as an optimisation problem and three evolutionary algorithms (genetic algorithm, differential evolution and self organising migration algorithm) are employed to search for an optimum solution. They are used to find an optimum parameter set for an image enhancement transfer function. The aim is to maximise a fitness criterion which is a measure of image contrast and the visibility of details in the enhanced image. The enhancement results obtained using all three evolutionary algorithms are compared amongst themselves and also with the output of histogram equalisation method.

Keywords: automatic image enhancement; comparative analysis; evolutionary algorithms; metaheuristics; self-organising migration algorithm; genetic algorithms; differential evolution.

DOI: 10.1504/IJMHEUR.2012.048219

International Journal of Metaheuristics, 2012 Vol.2 No.1, pp.80 - 100

Received: 11 May 2012
Accepted: 26 Jun 2012
Published online: 22 Oct 2014 *

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