Graduated adaptive image denoising: local compromise between total variation and isotropic diffusion

Cite Details

Peter F. Scultz, Erik M. Bollt, Rick Chartrand, Selim Esedoğlu and Kevin R. Vixie, "Graduated adaptive image denoising: local compromise between total variation and isotropic diffusion", Submitted., 2005

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Abstract

We introduce variants of the variational image denoising method proposed by Blomgren, Mulet, Chan, and Wong, 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.

BibTeX Entry

@unpublished{schultz-2005-graduated,

author = {Peter F. Scultz and Erik M. Bollt and Rick Chartrand and Selim Esedoğlu and Kevin R. Vixie},

title = {Graduated adaptive image denoising: local compromise between total variation and isotropic diffusion},

year = {2005},

urlpdf = {http://math.lanl.gov/Research/Publications/Docs/schultz-2005-graduated.pdf},

note = {Submitted.}

}