Document Detail


Color-opponent receptive fields derived from independent component analysis of natural images.
MedLine Citation:
PMID:  10958917     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Independent Component Analysis (ICA) of images of natural scenes has been shown to generate basis functions, or filters, which resemble spatial [Bell & Sejnowski (1997). Vision Research, 37, 3327-3338; van Hateren & van der Schaaf (1998). Proceedings of the Royal Society of London B, 265, 359-366] and spatiotemporal [van Hateren & Ruderman (1998) Proceedings of the Royal Society of London B, 265, 2315-2320] receptive fields of simple cells of the striate cortex. ICA yields statistically independent components which provide for a redundancy-reduced representation of the data. Using one of several published algorithms [Lee (1998). Independent component analysis: theory and applications. Boston; Kluwer Academic], we applied linear ICA to color images of natural scenes. The resulting independent component filters (ICFs) separate into either luminance or color filters. The luminance filters are localized and oriented edge detectors as reported previously. The color filters resemble either blue-yellow or red-green double-opponent receptive fields with various orientations. An equal number of each type of filter (luminance, red-green, and blue-yellow) is obtained. Thus, ICA predicts that spatiochromatic information is coded in statistically independent luminance, blue-yellow, and red-green opponent pathways with a relatively equal representation and specific spatial profiles at the cortical level.
Authors:
D R Tailor; L H Finkel; G Buchsbaum
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Vision research     Volume:  40     ISSN:  0042-6989     ISO Abbreviation:  Vision Res.     Publication Date:  2000  
Date Detail:
Created Date:  2000-09-15     Completed Date:  2000-09-15     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  0417402     Medline TA:  Vision Res     Country:  ENGLAND    
Other Details:
Languages:  eng     Pagination:  2671-6     Citation Subset:  IM    
Affiliation:
Department of Bioengineering and the Institute for Neurological Sciences, University of Pennsylvania, 3320 Smith Walk, 19104-6392, Philadelphia, PA, USA.
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Color Perception*
Humans
Image Processing, Computer-Assisted*
Linear Models
Visual Cortex / physiology

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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