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Image Processing Algorithms with Structure Transferring Properties on the Basis of Gamma-Normal Model

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Analysis of Images, Social Networks and Texts (AIST 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 661))

Abstract

Within the framework of the Bayesian approach, the general problem of image processing can be represented as a problem of estimation of the hidden component of the two-component random field on the basis of realization of its observable component, that is an analyzed image. Nonstationary gamma-normal model of the two-component random field showed good results in processing quality and computation time by solving the problem of image denoising. This paper proposes to extend the initial formulation for solving problems requiring transferring structure of the intermediate image on the processing result. Haze removal problem, HDR image compression and edges refinement of an image are considered as practical examples of such problems.

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Acknowledgements

This research is funded by RFBR grants, 16-07-01039 and 16-57-52042.

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Authors and Affiliations

  1. Tula State University, Tula, Russian Federation

    Inessa Gracheva & Andrey Kopylov

Authors
  1. Inessa Gracheva
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  2. Andrey Kopylov
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Corresponding author

Correspondence to Inessa Gracheva .

Editor information

Editors and Affiliations

  1. National Research University Higher School of Economics, Moscow, Russia

    Dmitry I. Ignatov

  2. Krasovsky Institute of Mathematics and Mechanics, Yekaterinburg, Russia

    Mikhail Yu. Khachay

  3. Ural Federal University, Yekaterinbug, Russia

    Valeri G. Labunets

  4. Research Computing Center, Lomonosov Moscow State University, Moscow, Russia

    Natalia Loukachevitch

  5. National Research University Higher School of Economics, St. Petersburg, Russia

    Sergey I. Nikolenko

  6. Technische Universität Darmstadt, Darmstadt, Germany

    Alexander Panchenko

  7. Laboratory of Algorithms and Technologies for Networks Analysis, National Research University Higher School of Economics, Nizhny Novgorod, Russia

    Andrey V. Savchenko

  8. Dorodnicyn Computing Centre of Russian Academy of Sciences, Moscow, Russia

    Konstantin Vorontsov

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Gracheva, I., Kopylov, A. (2017). Image Processing Algorithms with Structure Transferring Properties on the Basis of Gamma-Normal Model. In: Ignatov, D., et al. Analysis of Images, Social Networks and Texts. AIST 2016. Communications in Computer and Information Science, vol 661. Springer, Cham. https://doi.org/10.1007/978-3-319-52920-2_24

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  • DOI: https://doi.org/10.1007/978-3-319-52920-2_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52919-6

  • Online ISBN: 978-3-319-52920-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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