NDLI: Nonlinear multigrid methods for total variation image denoising

Content Provider	Springer Nature Link
Author	Frohn Schauf, Claudia Henn, Stefan Witsch, Kristian
Copyright Year	2004
Abstract	The classical image denoising technique introduced by Rudin, Osher, and Fatemi [17] a decade ago, leads to solve a constrained minimization problem for the total variation (TV) of the image. The formal first variation of the minimization problem is a nonlinear and highly anisotropic boundary value problem. In this paper, a computational PDE method based on a nonlinear multigrid scheme for restoring noisy images is suggested. Here, we examine different discretizations for the Euler–Lagrange equation as well as different smoothers within the multigrid scheme. Then we describe the iterative total variation regularization scheme, which starts with an isotropic (“smooth”) problem and leads to smooth edges in the image. Within the iteration the problem becomes more and more anisotropic and converges to an image with sharp edges. Finally, we present some experimental results for synthetic and real images.
Starting Page	199
Ending Page	206
Page Count	8
File Format	PDF
ISSN	14329360
Journal	Computing and Visualization in Science
Volume Number	7
Issue Number	3-4
e-ISSN	14330369
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2004-10-01
Publisher Place	Berlin, Heidelberg
Access Restriction	Subscribed
Subject Keyword	Computational Mathematics and Numerical Analysis Computer Applications in Chemistry Algorithms Visualization Numerical Analysis Calculus of Variations and Optimal Control; Optimization
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Engineering Computational Theory and Mathematics Computer Vision and Pattern Recognition Modeling and Simulation Software

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