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Multidimensional Noise Removal Method Based on PARAFAC Decomposition

  • Conference paper
Advanced Concepts for Intelligent Vision Systems (ACIVS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5259))

Abstract

Multicomponent sensors are more and more developed since they allow to measure simultaneously several parameters. Thus, new kind of processing have been developed for some years. In this paper, we are particularly concerned with tensor signal processing for noise removal in multidimensional images. We adapt a PARAFAC based method to remove noise from multidimensional images. Some results on hyperspectral images and comparisons with a TUCKER3 based method are given.

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Author information

Authors and Affiliations

  1. Institut Fresnel (CNRS UMR 6133),Univ. Paul Cézanne, Ecole Centrale Marseille, Dom. Univ. de Saint Jérôme, 13013, Marseille Cedex, France

    Florian Joyeux, Damien Letexier & Salah Bourennane

  2. DGA/MRIS, Arcueil, France

    Jacques Blanc-Talon

Authors
  1. Florian Joyeux
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  2. Damien Letexier
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  3. Salah Bourennane
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  4. Jacques Blanc-Talon
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Editor information

Editors and Affiliations

  1. DGA/D4S/MRIS, 94114, Arcueil, France

    Jacques Blanc-Talon

  2. Ecole Centrale de Marseille, 13451, Marseille, France

    Salah Bourennane

  3. Ghent University, 9000, Gent, Belgium

    Wilfried Philips

  4. CSIRO ICT Centre, NSW 1710, Sydney, Australia

    Dan Popescu

  5. University of Antwerp, 2610, Wilrijk, Belgium

    Paul Scheunders

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© 2008 Springer-Verlag Berlin Heidelberg

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Joyeux, F., Letexier, D., Bourennane, S., Blanc-Talon, J. (2008). Multidimensional Noise Removal Method Based on PARAFAC Decomposition. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2008. Lecture Notes in Computer Science, vol 5259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88458-3_42

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  • DOI: https://doi.org/10.1007/978-3-540-88458-3_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88457-6

  • Online ISBN: 978-3-540-88458-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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