Abstract
The Human Visual System (HVS) presents some properties that are shared by the results obtained when Independent Component Analysis (ICA) is applied to natural images. Particularly, the special appearance of the ICA bases (they look like “edges”) and the sparse distribution of the independent components have been linked to the receptive fields of the simple neurons in the visual cortex and their way to codify the visual information, respectively. Nevertheless, no theoretical study has been provided so far to explain that behaviour of ICA. The objective of this paper is to analyze, both mathematical and experimentally, the results obtained when ICA is applied to natural images in order to supply a theoretical basis for the connection between ICA and the HVS.
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References
Barlow, H.: Sensory Communication. Possible Principles Underlying the Transformation of Sensory Messages, pp. 217–234. MIT Press, Cambridge (1961)
Bell, A., Sejnowski, T.: The “Independent Components” of Natural Scenes are Edge Filters. Vision Research 37(23), 3327–3338 (1997)
Cao, X., Liu, R.: General Approach to Blind Source Separation. IEEE Transactions on Signal Processing 44(3), 562–571 (1996)
Cichocki, A., Amari, S.I.: Adaptive Blind Signal and Image Processing. John Willey & Sons, West Sussex (2002)
Fastica algorithm, available at http://www.cis.hut.fi/projects/ica/fastica/
Field, F.: What is the Goal of Sensory Coding? Neural Computation 6, 559–601 (1994)
Guyton, A.C., Hall, J.E.: Textbook of Medical Physiology. W.B. Saunders, Philadelphia (2000)
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)
Hornillo-Mellado, S., Martín-Clemente, R., Acha, J.I., Puntonet, C.G.: Application of Independent Component Analysis to Edge Detection and Watermarking. In: Böhling, K.-H., Indermark, K. (eds.) GI-Fachtagung 1973. LNCS, vol. 2, pp. 273–280. Springer, Heidelberg (1973)
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)
Hyvärinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. Wiley-Interscience, John Wiley & Sons, Hoboken (2001)
Hyvärinen, A., Oja, E.: A Fast Fixed-Point Algorithm for Independent Component Analysis. Neural Computation 6, 1484–1492 (1997)
Olshausen, B.A.: Principles of Image Representation in Visual Cortex. In: Chalupa, L.M., Werner, J.S. (eds.) The Visual Neurosciences, pp. 1603–1615. MIT Press, Cambridge (2003)
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)
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Hornillo-Mellado, S., Martín-Clemente, R., Puntonet, C.G., Acha, J.I. (2005). On the Connection Between the Human Visual System and Independent Component Analysis. In: Mira, J., Álvarez, J.R. (eds) Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach. IWINAC 2005. Lecture Notes in Computer Science, vol 3562. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11499305_61
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DOI: https://doi.org/10.1007/11499305_61
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