A nonlinear total variation-based denoising method with two regularization parameters

Corina S. Drapaca

doi:10.1109/TBME.2008.2011561

A nonlinear total variation-based denoising method with two regularization parameters

Corina S. Drapaca

Research output: Contribution to journal › Article › peer-review

30 Scopus citations

Abstract

The aim of the present paper is to study the effect of the regularization parameter used in the numerical implementation of the Rudin - Osher - Fatemi denoising model. By using two different regularization parameters in the numerical scheme of the Rudin - Osher - Fatemi model, we will show experimentally that when a particular relationship between the sizes of these parameters holds, the quality of the denoised image and the speed of convergence of the numerical scheme are both much improved in comparison with the classic numerical scheme of the Rudin - Osher - Fatemi model where only one regularization parameter is used.

Original language	English (US)
Article number	4760229
Pages (from-to)	582-586
Number of pages	5
Journal	IEEE Transactions on Biomedical Engineering
Volume	56
Issue number	3
DOIs	https://doi.org/10.1109/TBME.2008.2011561
State	Published - Mar 2009

All Science Journal Classification (ASJC) codes

Biomedical Engineering

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10.1109/TBME.2008.2011561

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A nonlinear total variation-based denoising method with two regularization parameters

Abstract

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