Adaptive typhoon cloud image enhancement using genetic algorithm and non-linear gain operation in undecimated wavelet domain

被引:15
|
作者
Zhang, Changjiang [1 ,2 ,3 ]
Wang, Xiaodong [1 ]
Duanmu, Chunjiang [1 ]
机构
[1] Zhejiang Normal Univ, Coll Math Phys & Informat Engn, Jinhua 321004, Zhejiang, Peoples R China
[2] Beijing Normal Univ, Beijing 100101, Peoples R China
[3] Chinese Acad Sci, Inst Remote Sensing Applicat, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
关键词
Typhoon cloud image; De-noising; Enhancement; Genetic algorithm; Undecimated wavelet transform; SPECKLE REDUCTION; CROSS-VALIDATION; TRANSFORM; SHRINKAGE;
D O I
10.1016/j.engappai.2009.09.003
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
By combining discrete undecimated wavelet transform (UWT) with genetic algorithm (CA) an efficient enhancement algorithm for typhoon cloud image is proposed. Having implemented UWT to a typhoon cloud mage, noise in a typhoon cloud image is reduced by modifying the undecimated wavelet coefficients by combining with generalization cross validation at fine resolution levels. CA and nonlinear gain operation are used to modify the undecimated wavelet coefficients at coarse resolution levels in order to extrude the details of a typhoon cloud image. Experimental results show that the proposed algorithm can efficiently reduce the additive gauss white noise in a typhoon cloud image while well extruding the detail. In order to accurately assess an enhanced typhoon cloud image's quality, an overall score index is proposed based on information entropy, contrast measure and peak signal-noise ratio. Finally, comparisons between the proposed algorithm and five other similar methods, are carried out. Crown Copyright (C) 2009 Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:61 / 73
页数:13
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