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Median Filtering of Tensor-Valued Images

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Pattern Recognition (DAGM 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2781))

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Abstract

Novel matrix-valued imaging techniques such as diffusion tensor magnetic resonance imaging require the development of edge-preserving nonlinear filters. In this paper we introduce a median filter for such tensor-valued data. We show that it inherits a number of favourable properties from scalar-valued median filtering, and we present experiments on synthetic as well as on real-world images that illustrate its performance.

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Author information

Authors and Affiliations

  1. Mathematical Image Analysis Group, Faculty of Mathematics and Computer Science, Bldg. 27, Saarland University, 66041, Saarbrücken, Germany

    Martin Welk, Christian Feddern, Bernhard Burgeth & Joachim Weickert

Authors
  1. Martin Welk
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  2. Christian Feddern
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  3. Bernhard Burgeth
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  4. Joachim Weickert
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Editor information

Editors and Affiliations

  1. Otto-von-Guericke University, 39106, Magdeburg, Germany

    Bernd Michaelis

  2. Institute for Electronics, Signal Processing and Communications (IESK), Otto-von-Guericke-University Magdeburg, P.O. Box 4120, D-39016, Magdeburg, Germany

    Gerald Krell

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© 2003 Springer-Verlag Berlin Heidelberg

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Welk, M., Feddern, C., Burgeth, B., Weickert, J. (2003). Median Filtering of Tensor-Valued Images. In: Michaelis, B., Krell, G. (eds) Pattern Recognition. DAGM 2003. Lecture Notes in Computer Science, vol 2781. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45243-0_3

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  • DOI: https://doi.org/10.1007/978-3-540-45243-0_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40861-1

  • Online ISBN: 978-3-540-45243-0

  • eBook Packages: Springer Book Archive

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