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An Easily Computable Eight Times Overcomplete ICA Method for Image Data

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Independent Component Analysis and Blind Signal Separation (ICA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3889))

Abstract

Here we present a procedure for finding an eight times overcomplete ICA description of image data using the symmetries defined by the rigid motions of a square. The procedure for estimating the basis requires only a small change to any classic ICA procedure and the data representation in this overcomplete description is unique. Coding and decoding in this description are essentially as easy as in classic ICA methods. We also show that this description is genuinely more sparse than a non-overcomplete ICA method.

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Author information

Authors and Affiliations

  1. Neural Networks Research Centre, Helsinki University of Technology, HUT, P.O. Box 5400, FI-02015, Finland

    Mika Inki

Authors
  1. Mika Inki
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Editor information

Editors and Affiliations

  1. Siemens Corporate Research, 755 College Road East, 08540, Princeton, NJ, USA

    Justinian Rosca

  2. Department of CSEE, Oregon Health and Science University, Portland, Oregon, USA

    Deniz Erdogmus

  3. Dep. of Electrical and Computer Engineering, University of Florida, Gainesville, Florida, USA

    José C. Príncipe

  4. McMaster University, 1280 Main Street West, L8S 4K1, Hamilton, Ontario, Canada

    Simon Haykin

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© 2006 Springer-Verlag Berlin Heidelberg

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Inki, M. (2006). An Easily Computable Eight Times Overcomplete ICA Method for Image Data. In: Rosca, J., Erdogmus, D., Príncipe, J.C., Haykin, S. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2006. Lecture Notes in Computer Science, vol 3889. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11679363_118

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  • DOI: https://doi.org/10.1007/11679363_118

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-32630-4

  • Online ISBN: 978-3-540-32631-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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