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Computer Optics, 2018, Volume 42, Issue 5, Pages 838–845
DOI: https://doi.org/10.18287/2412-6179-2018-42-5-838-845
(Mi co568)
 

This article is cited in 1 scientific paper (total in 1 paper)

IMAGE PROCESSING, PATTERN RECOGNITION

Tree-serial parametric dynamic programming with flexible prior model for image denoising

Ph. C. Thangab, A. V. Kopylovc

a National Research University Higher School of Economics, 20Myasnitskaya Street, Moscow, Russia
b The University of Da Nang – University of Science and Technology, 54 Nguyen Luong Bang Street, Da Nang, Viet Nam
c Tula State University, pr. Lenina 92, Tula, Russia
Full-text PDF (375 kB) Citations (1)
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Abstract: We consider here image denoising procedures, based on computationally effective tree-serial parametric dynamic programming procedures, different representations of an image lattice by the set of acyclic graphs and non-convex regularization of a new type which allows to flexibly set a priori preferences. Experimental results in image denoising, as well as comparison with related methods, are provided. A new extended version of multi quadratic dynamic programming procedures for image denoising, proposed here, shows an improved accuracy for images of a different type.
Keywords: Image denoising, Dynamic programming, Bayesian optimization, Markov random fields (MRFs), Gauss-Seidel iteration method.
Funding agency Grant number
Тульский государственный университет 2017-21-PUBL
The results of the research project are published with the financial support of Tula State University within the framework of the scientific project № 2017-21-PUBL
Received: 27.11.2017
Accepted: 27.07.2018
Document Type: Article
Language: English
Citation: Ph. C. Thang, A. V. Kopylov, “Tree-serial parametric dynamic programming with flexible prior model for image denoising”, Computer Optics, 42:5 (2018), 838–845
Citation in format AMSBIB
\Bibitem{ThaKop18}
\by Ph.~C.~Thang, A.~V.~Kopylov
\paper Tree-serial parametric dynamic programming with flexible prior model for image denoising
\jour Computer Optics
\yr 2018
\vol 42
\issue 5
\pages 838--845
\mathnet{http://mi.mathnet.ru/co568}
\crossref{https://doi.org/10.18287/2412-6179-2018-42-5-838-845}
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  • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Optics
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    Abstract page:154
    Full-text PDF :82
    References:28
     
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