Acceleration methods for total variation-based image denoising
Resource
SIAM Journal on Scientific Computing 25 (3): 982-994
Journal
SIAM Journal on Scientific Computing
Journal Volume
25
Journal Issue
3
Pages
982-994
Date Issued
2003
Author(s)
Abstract
In this paper, we apply a fixed point method to solve the total variation-based image denoising problem. An algebraic multigrid method is used to solve the corresponding linear equations. Krylov subspace acceleration is adopted to improve convergence in the fixed point iteration. A good initial guess for this outer iteration at finest grid is obtained by combining fixed point iteration and geometric multigrid interpolation successively from the coarsest grid to the finest grid. Numerical experiments demonstrate that this method is efficient and robust even for images with large noise-to-signal ratios.
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Type
journal article
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