The Spectral Independent Components of Natural Scenes

Abstract. 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. 1 Learning Codes for Color Images The efficient encoding of visual sensory information is an important task for image processing systems as well as for the understanding of coding principles in the visual cortex. Barlow [1] proposed that the goal of sensory information processing is to transform the input signals such that it reduces ...

• Type: Conference
• Year: 2000
• Where: BMCV
• Authors: Te-Won Lee, Thomas Wachtler, Terrence J. Sejnowski
• Keywords: Basis Functions, BMCV 2000, Color Images, Computer Vision, Efficient Color Image