FAST MULTILEVEL ALGORITHM FOR A MINIMIZATION PROBLEM IN IMPULSE NOISE REMOVAL

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

4 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)1474-1489
Journal / PublicationSIAM Journal on Scientific Computing
Volume30
Issue number3
Online published9 Apr 2008
Publication statusPublished - 2008
Externally publishedYes

Abstract

An effective 2-phase method for removing impulse noise was recently proposed. Its phase 1 identifies noisy pixel candidates by using median-type filters. Then in phase 2, it restores only the noisy pixel candidates by some variational methods. The resulting method can handle saltand-pepper noise and random-valued impulse noise at a level as high as 90% and 60%, respectively. The aim of this paper is to generalize a fast multilevel method for Gaussian denoising to solving the minimization problem arising in phase 2 of the 2-phase method. The multilevel algorithm gives better images than standard optimization methods such as the Newton method or the conjugate gradient method. Also it can handle more general regularization functionals than the smooth ones previously considered. Supporting numerical experiments on two-dimensional gray-scale images are presented.

Research Area(s)

  • Image restoration, Impulse noise, Multilevel methods, Regularization