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Second-order TGV model for Poisson noise image restoration

Restoring Poissonian noise images have drawn a lot of attention in recent years. There are many regularization methods to solve this problem and one of the most famous methods is the total variation model. In this paper, by adding a quadratic regularization on TGV regularization part, a new image re...

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Detalles Bibliográficos
Autores principales: Li, Hou-biao, Wang, Jun-yan, Dou, Hong-xia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4975743/
https://www.ncbi.nlm.nih.gov/pubmed/27540505
http://dx.doi.org/10.1186/s40064-016-2929-3
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author Li, Hou-biao
Wang, Jun-yan
Dou, Hong-xia
author_facet Li, Hou-biao
Wang, Jun-yan
Dou, Hong-xia
author_sort Li, Hou-biao
collection PubMed
description Restoring Poissonian noise images have drawn a lot of attention in recent years. There are many regularization methods to solve this problem and one of the most famous methods is the total variation model. In this paper, by adding a quadratic regularization on TGV regularization part, a new image restoration model is proposed based on second-order total generalized variation regularization. Then the split Bregman iteration algorithm was used to solve this new model. The experimental results show that the proposed model and algorithm can deal with Poisson image restoration problem well. What’s more, the restoration model performance is significantly improved both in visual effect and objective evaluation indexes.
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spelling pubmed-49757432016-08-18 Second-order TGV model for Poisson noise image restoration Li, Hou-biao Wang, Jun-yan Dou, Hong-xia Springerplus Research Restoring Poissonian noise images have drawn a lot of attention in recent years. There are many regularization methods to solve this problem and one of the most famous methods is the total variation model. In this paper, by adding a quadratic regularization on TGV regularization part, a new image restoration model is proposed based on second-order total generalized variation regularization. Then the split Bregman iteration algorithm was used to solve this new model. The experimental results show that the proposed model and algorithm can deal with Poisson image restoration problem well. What’s more, the restoration model performance is significantly improved both in visual effect and objective evaluation indexes. Springer International Publishing 2016-08-05 /pmc/articles/PMC4975743/ /pubmed/27540505 http://dx.doi.org/10.1186/s40064-016-2929-3 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Li, Hou-biao
Wang, Jun-yan
Dou, Hong-xia
Second-order TGV model for Poisson noise image restoration
title Second-order TGV model for Poisson noise image restoration
title_full Second-order TGV model for Poisson noise image restoration
title_fullStr Second-order TGV model for Poisson noise image restoration
title_full_unstemmed Second-order TGV model for Poisson noise image restoration
title_short Second-order TGV model for Poisson noise image restoration
title_sort second-order tgv model for poisson noise image restoration
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4975743/
https://www.ncbi.nlm.nih.gov/pubmed/27540505
http://dx.doi.org/10.1186/s40064-016-2929-3
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