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Two Novel Image Filters Based on Canonical Piecewise Linear Networks

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3497))

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Abstract

Although many filters have been proposed,image denoising is still worth further studying. In this paper, two novel image filters based on canonical piecewise linear networks are presented. They have the advantages of both linear filters and nonlinear filters. The former filter removes noises through the estimation of local structure, while the latter one accomplishes that by approximating the mapping from degraded images to clear images. They can remove noises effectively and preserve the details well. Finally, simulation results are shown to support their effectiveness.

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Author information

Authors and Affiliations

  1. Department of Automation, Tsinghua University, Beijing, 100084, China

    Xusheng Sun, Shuning Wang & Yuehong Wang

Authors
  1. Xusheng Sun
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  2. Shuning Wang
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  3. Yuehong Wang
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiao-Feng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Sun, X., Wang, S., Wang, Y. (2005). Two Novel Image Filters Based on Canonical Piecewise Linear Networks. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_111

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  • DOI: https://doi.org/10.1007/11427445_111

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25913-8

  • Online ISBN: 978-3-540-32067-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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