We apply independent component analysis (ICA) for learning an efficient color image representation of natural scenes. In the spectra of single pixels, the algorithm was able to find basis functions that had a broadband spectrum similar to natural daylight, as well as basis functions that coincided with the human cone sensitivity response functions. When applied to small image patches, the algorithm found homogeneous basis functions, achromatic basis functions, and basis functions with overall chromatic variation along lines in color space. Our findings suggest that ICA may be used to reveal the structure of color information in natural images.
CITATION STYLE
Lee, T. W., Wachtler, T., & Sejnowski, T. J. (2000). The spectral independent components of natural scenes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1811, pp. 527–534). Springer Verlag. https://doi.org/10.1007/3-540-45482-9_53
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