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Image Denoising Using Backward Stochastic Differential Equations

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Man-Machine Interactions 5 (ICMMI 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 659))

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Abstract

In this paper we explore the problem of reconstruction of RGB images with additive Gaussian noise. In order to solve this problem we use backward stochastic differential equations. The reconstructed image is characterized by smoothing noisy pixels and at the same time enhancing and sharpening edges. This novel look on the reconstruction is fruitful, gives encouraging results and can be successfully applied to denoising of high ISO images.

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Acknowledgements

This research was supported by the National Science Centre (Poland) under decision number DEC-2012/07/D/ST6/02534.

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Authors and Affiliations

  1. Faculty of Mathematics and Computer Science, Nicolaus Copernicus University, Chopina 12/18, 87-100, Toruń, Poland

    Dariusz Borkowski

  2. Institute of Mathematics and Physics, University of Science and Technology, al. prof. S. Kaliskiego 7, 85-796, Bydgoszcz, Poland

    Katarzyna Jańczak-Borkowska

Authors
  1. Dariusz Borkowski
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  2. Katarzyna Jańczak-Borkowska
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Corresponding author

Correspondence to Dariusz Borkowski .

Editor information

Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Aleksandra Gruca

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Tadeusz Czachórski

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Katarzyna Harezlak

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  5. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Agnieszka Piotrowska

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Borkowski, D., Jańczak-Borkowska, K. (2018). Image Denoising Using Backward Stochastic Differential Equations. In: Gruca, A., Czachórski, T., Harezlak, K., Kozielski, S., Piotrowska, A. (eds) Man-Machine Interactions 5. ICMMI 2017. Advances in Intelligent Systems and Computing, vol 659. Springer, Cham. https://doi.org/10.1007/978-3-319-67792-7_19

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  • DOI: https://doi.org/10.1007/978-3-319-67792-7_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67791-0

  • Online ISBN: 978-3-319-67792-7

  • eBook Packages: EngineeringEngineering (R0)

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