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Estimating the information available from colored surfaces in natural scenes
Iván Marín-Franch
David H. Foster
  DOI :  10.2352/CGIV.2006.3.1.art00009  Published Online :  January 2006
Abstract

The information preserved in identifying surfaces solely by their color can be quantified by measures defined by Shannon, including capacity and mutual information. The aim of this study was (1) to determine whether the capacity of an additive Gaussian channel provides an asymptotic upper bound to mutual information estimated for natural scenes under different illuminants, and (2) to explore the effect of different color representations on mutual-information estimates.

Journal Title : Conference on Colour in Graphics, Imaging, and Vision
Publisher Name : Society of Imaging Science and Technology
Publisher Location : 7003 Kilworth Lane, Springfield, VA 22151, USA
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 DOI 10.2352/CGIV.2006.3.1.art00009
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Iván Marín-Franch, David H. Foster, "Estimating the information available from colored surfaces in natural scenes"  in Proc. IS&T CGIV 2006 3rd European Conf. on Colour in Graphics, Imaging, and Vision,  2006,  pp 44 - 47,  https://doi.org/10.2352/CGIV.2006.3.1.art00009

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Copyright © Society for Imaging Science and Technology 2006
72010351
Conference on Colour in Graphics, Imaging, and Vision
conf colour graph imag vis
2158-6330
Society of Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151, USA
2158-6330(20060101)2006:1L.44;1-
cgiv_v2006n1/splitsection9.xml
/ist/cgiv/2006/00002006/00000001/art00009
Articles
Estimating the information available from colored surfaces in natural scenes
Marín-FranchIván
FosterDavid H.
01012006
2006
1
44
47
2006
The information preserved in identifying surfaces solely by their color can be quantified by measures defined by Shannon, including capacity and mutual information. The aim of this study was (1) to determine whether the capacity of an additive Gaussian channel provides an asymptotic upper bound to mutual information estimated for natural scenes under different illuminants, and (2) to explore the effect of different color representations on mutual-information estimates.