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A robust iterative algorithm for image restoration

We present a new image restoration method by combining iterative VanCittert algorithm with noise reduction modeling. Our approach enables decoupling between deblurring and denoising during the restoration process, so allows any well-established noise reduction operator to be implemented in our model...

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Detalles Bibliográficos
Autores principales: Liu, Yuewei, Lu, Weiping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6979517/
https://www.ncbi.nlm.nih.gov/pubmed/32025231
http://dx.doi.org/10.1186/s13640-017-0201-6
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author Liu, Yuewei
Lu, Weiping
author_facet Liu, Yuewei
Lu, Weiping
author_sort Liu, Yuewei
collection PubMed
description We present a new image restoration method by combining iterative VanCittert algorithm with noise reduction modeling. Our approach enables decoupling between deblurring and denoising during the restoration process, so allows any well-established noise reduction operator to be implemented in our model, independent of the VanCittert deblurring operation. Such an approach has led to an analytic expression for error estimation of the restored images in our method as well as simple parameter setting for real applications, both of which are hard to attain in many regularization-based methods. Numerical experiments show that our method can achieve good balance between structure recovery and noise reduction, and perform close to the level of the state of the art method and favorably compared to many other methods.
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spelling pubmed-69795172020-02-03 A robust iterative algorithm for image restoration Liu, Yuewei Lu, Weiping EURASIP J Image Video Process Research We present a new image restoration method by combining iterative VanCittert algorithm with noise reduction modeling. Our approach enables decoupling between deblurring and denoising during the restoration process, so allows any well-established noise reduction operator to be implemented in our model, independent of the VanCittert deblurring operation. Such an approach has led to an analytic expression for error estimation of the restored images in our method as well as simple parameter setting for real applications, both of which are hard to attain in many regularization-based methods. Numerical experiments show that our method can achieve good balance between structure recovery and noise reduction, and perform close to the level of the state of the art method and favorably compared to many other methods. Springer International Publishing 2017-08-03 2017 /pmc/articles/PMC6979517/ /pubmed/32025231 http://dx.doi.org/10.1186/s13640-017-0201-6 Text en © The Author(s) 2017 Open Access This 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
Liu, Yuewei
Lu, Weiping
A robust iterative algorithm for image restoration
title A robust iterative algorithm for image restoration
title_full A robust iterative algorithm for image restoration
title_fullStr A robust iterative algorithm for image restoration
title_full_unstemmed A robust iterative algorithm for image restoration
title_short A robust iterative algorithm for image restoration
title_sort robust iterative algorithm for image restoration
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6979517/
https://www.ncbi.nlm.nih.gov/pubmed/32025231
http://dx.doi.org/10.1186/s13640-017-0201-6
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