Graduated adaptive image denoising: local compromise between total variation and isotropic diffusion |
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Authors: | Erik M Bollt Rick Chartrand Selim Esedoḡlu Pete Schultz Kevin R Vixie |
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Institution: | 1. Clarkson University, P.O. Box 5815, Potsdam, NY, 13699, USA 2. Los Alamos National Laboratory, Theoretical Division, MS B284, Los Alamos, NM, 87545, USA 3. Department of Mathematics, University of Michigan, 2074 East Hall 530 Church Street, Ann Arbor, MI, 48109, USA
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Abstract: | We introduce variants of the variational image denoising method proposed by Blomgren et al. (In: Numerical Analysis 1999 (Dundee), pp. 43–67. Chapman & Hall, Boca Raton, FL, 2000), which interpolates between total-variation denoising and isotropic diffusion denoising. We study how parameter choices affect results and allow tuning between TV denoising and isotropic diffusion for respecting texture on one spatial scale while denoising features assumed to be noise on finer spatial scales. Furthermore, we prove existence and (where appropriate) uniqueness of minimizers. We consider both L 2 and L 1 data fidelity terms. |
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