Dual Formulation of the TV-Stokes Denoising Model for Multidimensional Vectorial Images

The TV-Stokes denoising model for a vectorial image defines a denoised vector field in the form of the gradient of a scalar function. The dual formulation naturally leads to a Chambolle-type algorithm, where the most time consuming part is application of the orthogonal projector onto the range space...

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Autor principal: Malyshev, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302564/
http://dx.doi.org/10.1007/978-3-030-50426-7_43
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author Malyshev, Alexander
author_facet Malyshev, Alexander
author_sort Malyshev, Alexander
collection PubMed
description The TV-Stokes denoising model for a vectorial image defines a denoised vector field in the form of the gradient of a scalar function. The dual formulation naturally leads to a Chambolle-type algorithm, where the most time consuming part is application of the orthogonal projector onto the range space of the gradient operator. This application can be efficiently executed by the fast cosine transform taking advantage of the fast Fourier transform. Convergence of the Chambolle-type iteration can be improved by Nesterov’s acceleration.
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spelling pubmed-73025642020-06-19 Dual Formulation of the TV-Stokes Denoising Model for Multidimensional Vectorial Images Malyshev, Alexander Computational Science – ICCS 2020 Article The TV-Stokes denoising model for a vectorial image defines a denoised vector field in the form of the gradient of a scalar function. The dual formulation naturally leads to a Chambolle-type algorithm, where the most time consuming part is application of the orthogonal projector onto the range space of the gradient operator. This application can be efficiently executed by the fast cosine transform taking advantage of the fast Fourier transform. Convergence of the Chambolle-type iteration can be improved by Nesterov’s acceleration. 2020-05-25 /pmc/articles/PMC7302564/ http://dx.doi.org/10.1007/978-3-030-50426-7_43 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Malyshev, Alexander
Dual Formulation of the TV-Stokes Denoising Model for Multidimensional Vectorial Images
title Dual Formulation of the TV-Stokes Denoising Model for Multidimensional Vectorial Images
title_full Dual Formulation of the TV-Stokes Denoising Model for Multidimensional Vectorial Images
title_fullStr Dual Formulation of the TV-Stokes Denoising Model for Multidimensional Vectorial Images
title_full_unstemmed Dual Formulation of the TV-Stokes Denoising Model for Multidimensional Vectorial Images
title_short Dual Formulation of the TV-Stokes Denoising Model for Multidimensional Vectorial Images
title_sort dual formulation of the tv-stokes denoising model for multidimensional vectorial images
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302564/
http://dx.doi.org/10.1007/978-3-030-50426-7_43
work_keys_str_mv AT malyshevalexander dualformulationofthetvstokesdenoisingmodelformultidimensionalvectorialimages

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