Sixth Mississippi State Conference on Differential Equations and Computational Simulations.
Electron. J. Diff. Eqns., Conference 15 (2007), pp. 175-192.

A non-convex diffusion model for simultaneous image denoising and edge enhancement

Seongjai Kim, Hyeona Lim

Abstract:
Mathematical restoration models, in particular, total variation-based models can easily lose fine structures during image denoising. In order to overcome the drawback, this article introduces two strategies: the non-convex (NC) diffusion and the texture-free residual (TFR) parameterization. A non-standard numerical procedure is suggested and its stability is analyzed to effectively solve the NC diffusion model which is mathematically unstable. It has been numerically verified that the resulting algorithm incorporating the NC diffusion and TFR parameterization is able to not only reduce the noise satisfactorily but also enhance edges effectively, at the same time. Various numerical examples are shown to confirm the claim.

Published February 28, 2007.
Math Subject Classifications: 35K55, 65M06, 65M12.
Key Words: Fine structures; denoising; edge enhancement; nonphysical dissipation; total variation (TV) model; non-convex (NC) diffusion model; texture-free residual (TFR) parameterization.

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Seongjai Kim
Department of Mathematics and Statistics
Mississippi State University
Mississippi State, MS 39762-5921, USA
email: skim@math.msstate.edu
Hyeona Lim
Department of Mathematics and Statistics
Mississippi State University
Mississippi State, MS 39762-5921, USA
email: hlim@math.msstate.edu

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