A descent spectral conjugate gradient method for impulse noise removal

被引:64
|
作者
Yu, Gaohang [1 ]
Huang, Finhong [1 ]
Zhou, Yi [2 ]
机构
[1] Gannon Normal Univ, Sch Math & Comp Sci, Ganzhou 341000, Peoples R China
[2] Sun Yat Sen Univ, Zhongshan Sch Med, Dept Biomed Engn, Guangzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
Image processing; Variational method; Optimization; Conjugate gradient method; ALGORITHM;
D O I
10.1016/j.aml.2010.01.010
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In most applications, denoising image is fundamental to subsequent image processing operations. This paper proposes a spectral conjugate gradient (CG) method for impulse noise removal, which is based on a two-phase scheme. The noise candidates are first identified by the adaptive (center-weighted) median filter; then these noise candidates are restored by minimizing an edge-preserving regularization functional, which is accomplished by the proposed spectral CG method. A favorite property of the proposed method is that the search direction generated at each iteration is descent. Under strong Wolfe line search conditions, its global convergence result could be established. Numerical experiments are given to illustrate the efficiency of the spectral conjugate gradient method for impulse noise removal. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:555 / 560
页数:6
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