The full text of this article
Comparative analysis of evolutionary algorithms for image enhancement
by Anupriya Gogna; Akash Tayal
International Journal of Metaheuristics (IJMHEUR), Vol. 2, No. 1, 2012
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.
Online publication date: Sun, 29-Jul-2012
is only available to individual subscribers or to users at subscribing institutions.
Go to Inderscience Online Journals to access the Full Text of this article.
Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.
Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Metaheuristics (IJMHEUR):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable).
See our Orders page to subscribe.
If you still need assistance, please email email@example.com