Comparative analysis of evolutionary algorithms for image enhancement. (1st January 2012)

• Record Type: Journal Article
• Authors: Gogna, Anupriya; Tayal, Akash
• Is Part Of: International journal of metaheuristics. Volume 2:Number 1(2012)
• Page Start: 80
• Page End: 100
• Publication Date: 2012-01-01
• Subjects: automatic image enhancement -- comparative analysis -- evolutionary algorithms -- metaheuristic -- self-organising migration algorithm; Heuristic algorithms -- Periodicals; 006.3105
• Languages: English
• ISSNs: 1755-2176

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.