DocumentCode
1851290
Title
Intensity-Preserving Contrast Enhancement for Gray-Level Images using Multi-objective Particle Swarm Optimization
Author
Kwok, N.M. ; Ha, Q.P. ; Liu, D.K. ; Fang, G.
Author_Institution
ARC Centre of Excellence for Autonomous Syst., Univ. of Technol., Sydney, NSW
fYear
2006
fDate
8-10 Oct. 2006
Firstpage
21
Lastpage
26
Abstract
This paper addresses the enhancement of the contrast of gray-level digital images while preserving the mean image intensity, thus, providing better viewing consistency and effectiveness. The contrast enhancement is achieved by maximizing the information content carried in the image with a continuous intensity transform function and the mean image intensity is preserved, by using the gamma-correction approach. Since the contrast enhancement and intensity preservation are contradicting, a multi-objective particle swarm optimization (MPSO) algorithm is developed to resolve this trade-off. Benchmark images, street senses and skyline images are included to illustrate the effectiveness of the proposed approach
Keywords
computer vision; image enhancement; particle swarm optimisation; benchmark images; continuous intensity transform function; digital images; gamma correction; gray-level images; intensity-preserving contrast enhancement; mean image intensity; multi-objective particle swarm optimization; skyline images; street senses; Australia; Automation; Biomedical engineering; Content addressable storage; Digital images; Histograms; Image processing; Optimization methods; Particle swarm optimization; Pixel;
fLanguage
English
Publisher
ieee
Conference_Titel
Automation Science and Engineering, 2006. CASE '06. IEEE International Conference on
Conference_Location
Shanghai
Print_ISBN
1-4244-0310-3
Electronic_ISBN
1-4244-0311-1
Type
conf
DOI
10.1109/COASE.2006.326849
Filename
4120315
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