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International Conference on Knowledge-Based and Intelligent Information and Engineering Systems

KES 2005: Knowledge-Based Intelligent Information and Engineering Systems pp 589–595Cite as

Color Image Restoration Using Explicit Local Segmentation

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3681))

Abstract

A local segmentation structure is proposed for color image denoising and restoration. Most state-of-the-art filters suppression impulse noise well but tends to destroy thin lines, edges and high image details. The proposed filters facilitate local segmentation technique to preserve image structures and noise reduction. Firstly, the K-VMF is used for local segmentation and then the selection of vector filters for reconstruction of the current pixel. The proposed filters demonstrated acceptable results for both objective and subjective assessments.

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Author information

Authors and Affiliations

  1. Faculty of Information Technology, Monash University, Clayton Campus, Victoria, 3800, Australia

    Mieng Quoc Phu & Peter Tischer

  2. Software and Network Engineering, RMIT, City Campus, Victoria, 3001, Australia

    Hon Ren Wu

Authors
  1. Mieng Quoc Phu
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  2. Peter Tischer
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  3. Hon Ren Wu
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Editor information

Editors and Affiliations

  1. School of Business, La Trobe University, 3086, Melbourne, Victoria, Australia

    Rajiv Khosla

  2. Centre for SMART systems Engineering Research Centre, University of Brighton, Moulsecoomb, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2005 Springer-Verlag Berlin Heidelberg

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Cite this paper

Phu, M.Q., Tischer, P., Wu, H.R. (2005). Color Image Restoration Using Explicit Local Segmentation. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552413_85

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  • DOI: https://doi.org/10.1007/11552413_85

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28894-7

  • Online ISBN: 978-3-540-31983-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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