SIAM Journal on Scientific Computing ~ Volume 30, Issue 3, pp. 1474-1489
By addebook • Aug 28th, 2008 • Category: Mathematics •
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SIAM Journal on Scientific Computing ~ Volume 30, Issue 3, pp. 1474-1489 (2008) Fast Multilevel Algorithm for a Minimization Problem in Impulse Noise Removal
by Raymond H. Chan and Ke Chen
Fast Multilevel Algorithm for a Minimization
Problem in Impulse Noise Removal
Raymond H. Chan and Ke Chen
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 salt-and-pepper noise and random-valued
impulse noise of noise 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 method
such as the Newton method or conjugate gradient method. Also it can handle more general regularization
functionals than the smooth ones previously considered. Supporting numerical experiments on 2D gray
scale images are presented.
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