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http://dx.doi.org/10.3837/tiis.2013.11.009

Optimal Scheme of Retinal Image Enhancement using Curvelet Transform and Quantum Genetic Algorithm  

Wang, Zhixiao (School of Electronic and Information Engineering, Xi'an Jiaotong University)
Xu, Xuebin (School of Electronic and Information Engineering, Xi'an Jiaotong University)
Yan, Wenyao (Xi'an Innovation College, Yan'an University)
Wei, Wei (School of Computer Science and Engineering, Xi'an University of Technology)
Li, Junhuai (School of Computer Science and Engineering, Xi'an University of Technology)
Zhang, Deyun (School of Electronic and Information Engineering, Xi'an Jiaotong University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.7, no.11, 2013 , pp. 2702-2719 More about this Journal
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.
Keywords
Retinal image enhancement; quantum genetic algorithm; sparse representation; curvelet;
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