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Connections Between ICA and Sparse Coding Revisited

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Computational Intelligence and Bioinspired Systems (IWANN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3512))

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Abstract

Recently, the application of Independent Component Analysis (ICA) to natural images has raised a great interest. Some outstanding features have been observed, like the sparse distribution of the independent components and the special appearance of the ICA bases (most of them look like edges). This paper provides a new insight on this behaviour, being supported by experimental results. In particular, a mathematical proof of the relation between ICA and sparse coding is given.

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References

  1. Barlow, H.: Sensory Communication. Possible Principles Underlying the Transformation of Sensory Messages, pp. 217–234. MIT Press, Cambridge (1961)

    Google Scholar 

  2. Bell, A., Sejnowski, T.: The “Independent Components” of Natural Scenes are Edge Filters. Vision Research 37(23), 3327–3338 (1997)

    Article  Google Scholar 

  3. Cao, X., Liu, R.: General Approach to Blind Source Separation. IEEE Transactions on Signal Processing 44(3), 562–571 (1996)

    Article  Google Scholar 

  4. Cichocki, A., Amari, S.I.: Adaptive Blind Signal and Image Processing. John Willey & Sons, West Sussex (2002)

    Book  Google Scholar 

  5. Field, F.: What is the Goal of Sensory Coding? Neural Computation 6, 559–601 (1994)

    Article  Google Scholar 

  6. Hornillo-Mellado, S., Martín-Clemente, R., Puntonet, C.G., Acha, J.I.: Application of Independent Component Analysis to Edge Detection. In: Proc. World Automation Congress (WAC 2004), Sevilla, Spain (2004)

    Google Scholar 

  7. Hornillo-Mellado, S., Martín-Clemente, R., Acha, J.I., Puntonet, C.G.: Application of Independent Component Analysis to Edge Detection and Watermarking. In: Mira, J., Álvarez, J.R. (eds.) IWANN 2003. LNCS, vol. 2687, pp. 273–280. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  8. Hyvärinen, A., Hoyer, P.O., Hurri, J.: Extensions of ICA as Models of Natural Images and Visual Processing. In: Proc. International Symposium on Independent Component Analysis and Blind Signal Separation (ICA 2003), Nara, Japan, pp. 963–974 (2003)

    Google Scholar 

  9. Hyvärinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. Wiley-Interscience, John Wiley & Sons (2001)

    Google Scholar 

  10. Hyvärinen, A., Oja, E.: A Fast Fixed-Point Algorithm for Independent Component Analysis. Neural Computation 6, 1484–1492 (1997)

    Google Scholar 

  11. Olshausen, B.A., Field, D.J.: Sparse Coding with an Overcomplete Basis Set: A Strategy Employed by V1? Vision Research 37(23), 3311–3325 (1997)

    Article  Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Hornillo-Mellado, S., Martín-Clemente, R., Górriz-Sáez, J.M. (2005). Connections Between ICA and Sparse Coding Revisited. In: Cabestany, J., Prieto, A., Sandoval, F. (eds) Computational Intelligence and Bioinspired Systems. IWANN 2005. Lecture Notes in Computer Science, vol 3512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494669_127

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  • DOI: https://doi.org/10.1007/11494669_127

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26208-4

  • Online ISBN: 978-3-540-32106-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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