Automatic image enhancement driven by evolution based on ridgelet frame in the presence of noise

Authors:
Tan Shan;Shuang Wang;Xiangrong Zhang;Licheng Jiao
Affiliations:
National Key Lab for Radar Signal Processing and Institute of Intelligent, Information Processing, Xidian University, Xi'an, China;National Key Lab for Radar Signal Processing and Institute of Intelligent, Information Processing, Xidian University, Xi'an, China;National Key Lab for Radar Signal Processing and Institute of Intelligent, Information Processing, Xidian University, Xi'an, China;National Key Lab for Radar Signal Processing and Institute of Intelligent, Information Processing, Xidian University, Xi'an, China
Venue:
EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Year:
2005

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Abstract

Many conventional and well-known image enhancement methods suffer from a tendency to increase the visibility of noise when they enhance the underlying details. In this paper, a new kind of image analysis tool — ridgelet frame is introduced into the arena of image enhancement. We design an enhancement operator with the advantages that it not only enhance image details but also avoid the amplification of noise within source image. Different from those published previously, our operator has more parameters, which results in more flexibility for different category images. Based on an objective criterion, we search the optimal parameters for each special image using Immune Clone Algorithm (ICA). Experimental results show the superiority of our method in terms of both subjective and objective evaluation.