Paper Info
Title
Optimal Scheme of Retinal Image Enhancement Using Curvelet Transform and Quantum Genetic Algorithm.
Abstract
A new optimal scheme based on curvelet transform is proposed for retinal image enhancement (RIE) using real-coded quantum genetic algorithm. Curvelet transform has better performance in representing edges than classical wavelet transform for its anisotropy and directional decomposition capabilities. For more precise reconstruction and better visualization, curvelet coefficients in corresponding subbands are modified by using a nonlinear enhancement mapping function. An automatic method is presented for selecting optimal parameter settings of the nonlinear mapping function via quantum genetic search strategy. The performance measures used in this paper provide some quantitative comparison among different RIE methods. The proposed method is tested on the DRIVE and STARE retinal databases and compared with some popular image enhancement methods. The experimental results demonstrate that proposed method can provide superior enhanced retinal image in terms of several image quantitative evaluation indexes.
Year
DOI
Venue
2013
10.3837/tiis.2013.11.009
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS
Keywords
Field
DocType
Retinal image enhancement,quantum genetic algorithm,sparse representation,curvelet
Nonlinear system,Computer science,Quantum genetic algorithm,Artificial intelligence,Distributed computing,Wavelet transform,Computer vision,Quantum,Pattern recognition,Visualization,Sparse approximation,Retinal image,Curvelet
Journal
Volume
Issue
ISSN
7
11
1976-7277
Citations 
PageRank 
References 
8
2.50
21
Authors
6
Name
Order
Citations
PageRank
Wang Zhi-xiao13712.28
Xuebin Xu2108.60
Wenyao Yan3123.95
Wei Wei450768.07
Junhuai Li53916.44
Deyun Zhang65214.54