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Improving ICA Performance for Modeling Image Appearance with the Kernel Trick

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3214))

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Abstract

Independent Component Analysis (ICA) is a popular method for modeling image appearance, but it is inadequate to describe complex nonlinear variations of real images due to illumination, distortion, and other variations because of its linear properties in nature. In this paper, we propose to combine the nonlinear kernel trick to improve the performance of ICA for modeling image appearance. First, the kernel trick is used to project the input data into a high-dimensional implicit feature space, and then ICA is performed in this implicit feature space to extract nonlinear independent components of input data. Extensive experiments show that the proposed method outperforms ICA for describing real images.

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Author information

Authors and Affiliations

  1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing, 100080, China

    Qingshan Liu, Jian Cheng, Hanqing Lu & Songde Ma

Authors
  1. Qingshan Liu
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  2. Jian Cheng
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  3. Hanqing Lu
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  4. Songde Ma
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Editor information

Editors and Affiliations

  1. KES International, 2nd Floor, 145-157 St John Street, EC1V 4PY, London, United Kingdom

    Mircea Gh. Negoita

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

    Robert J. Howlett

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

    Lakhmi C. Jain

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© 2004 Springer-Verlag Berlin Heidelberg

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Liu, Q., Cheng, J., Lu, H., Ma, S. (2004). Improving ICA Performance for Modeling Image Appearance with the Kernel Trick. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30133-2_44

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  • DOI: https://doi.org/10.1007/978-3-540-30133-2_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23206-3

  • Online ISBN: 978-3-540-30133-2

  • eBook Packages: Springer Book Archive

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