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Linear Hyperbolic Diffusion-Based Image Denoising Technique

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Book cover Neural Information Processing (ICONIP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9491))

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Abstract

A novel PDE-based image restoration approach is proposed in this article. The provided PDE model is based on a linear second-order hyperbolic diffusion equation. The well-posedness of the proposed differential model and some nonlinear PDE schemes derived from it are also discussed. A consistent and fast-converging numerical approximation scheme using finite differences is then constructed for the continuous hyperbolic PDE model. Some image restoration experiments using this approach and several method comparisons are also described.

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Acknowledgments

The research of this work was mainly supported by the project PN-II-ID-PCE-2011-3-0027-160/5.10.2011, financed by UEFSCDI Romania. It was supported also by the Institute of Computer Science of the Romanian Academy, Iași, Romania.

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Authors and Affiliations

  1. Institute of Computer Science of the Romanian Academy, Iaşi, Romania

    Tudor Barbu

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  1. Tudor Barbu
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Correspondence to Tudor Barbu .

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Editors and Affiliations

  1. University of Istanbul, Istanbul, Turkey

    Sabri Arik

  2. University at Qatar, Doha, Qatar

    Tingwen Huang

  3. Tunku Abdul Rahman University College, Kuala Lumpur, Malaysia

    Weng Kin Lai

  4. University of Science Technology, Wuhan, China

    Qingshan Liu

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Barbu, T. (2015). Linear Hyperbolic Diffusion-Based Image Denoising Technique. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9491. Springer, Cham. https://doi.org/10.1007/978-3-319-26555-1_53

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  • DOI: https://doi.org/10.1007/978-3-319-26555-1_53

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26554-4

  • Online ISBN: 978-3-319-26555-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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