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Adaptive Switching Median Filter with Neural Network Impulse Detection Step

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Artificial Neural Networks: Biological Inspirations – ICANN 2005 (ICANN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3696))

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Abstract

A new neural network adaptive switching median (NASM) filter is proposed to remove salt-and-pepper impulse noise from corrupted image. The algorithm is developed by combining advantages of the known median-type filters with impulse detection scheme and the neural network was included into impulse detection step to improve its characteristics. Comparison of the given method with traditional filters is provided.

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Author information

Authors and Affiliations

  1. Digital Circuits and Signals Laboratory, Department of Physics, Yaroslavl State University, 150000, Sovetskaya st., 14, Yaroslavl, Russia

    Pavel S. Zvonarev, Ilia V. Apalkov, Vladimir V. Khryashchev & Andrey L. Priorov

Authors
  1. Pavel S. Zvonarev
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  2. Ilia V. Apalkov
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  3. Vladimir V. Khryashchev
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  4. Andrey L. Priorov
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Editor information

Editors and Affiliations

  1. Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

    Włodzisław Duch

  2. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01–447, Warsaw, Poland

    Janusz Kacprzyk

  3. Adaptive Informatics Research Centre, Helsinki University of Technology, P.O. Box 5400, 02015 HUT, Finland

    Erkki Oja

  4. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Sławomir Zadrożny

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© 2005 Springer-Verlag Berlin Heidelberg

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Zvonarev, P.S., Apalkov, I.V., Khryashchev, V.V., Priorov, A.L. (2005). Adaptive Switching Median Filter with Neural Network Impulse Detection Step. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Biological Inspirations – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550822_84

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  • DOI: https://doi.org/10.1007/11550822_84

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28752-0

  • Online ISBN: 978-3-540-28754-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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