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A Novel Variational PDE Technique for Image Denoising

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Neural Information Processing (ICONIP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8228))

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Abstract

A robust variational PDE model for image noise removal is proposed in this paper. One considers an energy functional to be minimized, based on a novel smoothing constraint. Then, the corresponding Euler-Lagrange equation is determined. The obtained PDE model is solved, by using a numerical discretization scheme. Some results of our image denoising experiments and method comparisons are also described in this article.

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Author information

Authors and Affiliations

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

    Tudor Barbu

Authors
  1. Tudor Barbu
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Editor information

Editors and Affiliations

  1. Kyungpook National University, 1370 Sankyuk-Dong, Puk-Gu, 702-701, Taegu, Korea

    Minho Lee

  2. The University of Tokyo, 7-3-1 Hongo, 113-8656, Bunkyo-ku, Tokyo, Japan

    Akira Hirose

  3. Institute of Automation, Key Laboratory of Complex Systems and Intelligence Science, Chinese Academy of Sciences, 100190, Beijing, China

    Zeng-Guang Hou

  4. Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, 440-746, Suwon, Korea

    Rhee Man Kil

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Barbu, T. (2013). A Novel Variational PDE Technique for Image Denoising. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8228. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42051-1_62

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  • DOI: https://doi.org/10.1007/978-3-642-42051-1_62

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-42050-4

  • Online ISBN: 978-3-642-42051-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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