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Computer Optics, 2015, Volume 39, Issue 4, Pages 564–571
DOI: https://doi.org/10.18287/0134-2452-2015-39-4-564-571
(Mi co18)
 

This article is cited in 15 scientific papers (total in 15 papers)

IMAGE PROCESSING, PATTERN RECOGNITION

Image noise removal based on total variation

D. N. Thanh, S. D. Dvoenko

Tula State University
References:
Abstract: Today, raster images are created by different modern devices, such as digital cameras, X-Ray scanners, and so on. Image noise deteriorates the image quality, thus adversely affecting the result of processing. Biomedical images are an example of digital images. The noise in such raster images is assumed to be a mixture of Gaussian noise and Poisson noise. In this paper, we propose a method to remove these noises based on the total variation of the image brightness function. The proposed model is a combination of two famous denoising models, namely, the ROF model and a modified ROF model.
Keywords: total variation, ROF model, Gaussian noise, Poisson noise, image processing, biomedical image, Euler-Lagrange equation.
Received: 14.07.2015
Revised: 28.07.2015
Document Type: Article
Language: Russian
Citation: D. N. Thanh, S. D. Dvoenko, “Image noise removal based on total variation”, Computer Optics, 39:4 (2015), 564–571
Citation in format AMSBIB
\Bibitem{ThaDvo15}
\by D.~N.~Thanh, S.~D.~Dvoenko
\paper Image noise removal based on total variation
\jour Computer Optics
\yr 2015
\vol 39
\issue 4
\pages 564--571
\mathnet{http://mi.mathnet.ru/co18}
\crossref{https://doi.org/10.18287/0134-2452-2015-39-4-564-571}
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  • https://www.mathnet.ru/eng/co/v39/i4/p564
  • This publication is cited in the following 15 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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