✦ LIBER ✦

A descent spectral conjugate gradient method for impulse noise removal

✍ Scribed by Gaohang Yu; Jinhong Huang; Yi Zhou

Publisher: Elsevier Science
Year: 2010
Tongue: English
Weight: 887 KB
Volume: 23
Category: Article
ISSN: 0893-9659
DOI: 10.1016/j.aml.2010.01.010

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✦ Synopsis

a b s t r a c t

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.

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