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Image Statistics for Surface Reflectance Perception

Lavanya Sharan, Yuanzhen Li, Isamu Motoyoshi, Shin'ya Nishida, and Edward H. Adelson


Abstract

Human observers can distinguish the albedo of real-world surfaces even when the surfaces are viewed in isolation, contrary to the Gelb effect. We sought to measure this ability and to understand the cues that might underlie it. We took photographs of complex surfaces such as stucco and asked observers to judge their diffuse reflectance by comparing them to a physical Munsell scale. Their judgments, while imperfect, were highly correlated with the true reflectance. The judgments were also highly correlated with certain image statistics, such as moment and percentile statistics of the luminance and subband histograms. When we digitally manipulated these statistics in an image, human judgments were correspondingly altered. Moreover, linear combinations of such statistics allow a machine vision system (operating within the constrained world of single surfaces) to estimate albedo with an accuracy similar to that of human observers. Taken together, these results indicate that some simple image statistics have a strong influence on the judgment of surface reflectance.

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Information

title:
Image Statistics for Surface Reflectance Perception
author:
Lavanya Sharan,
Yuanzhen Li,
Isamu Motoyoshi,
Shin'ya Nishida,
and Edward H. Adelson.
citation:
Journal of the Optical Society of America A, Vol. 25, Issue 4, pp. 846-865
shortcite:
JOSA A
year:
2008
created:
2008-01-01
keyword:
sharan,
li,
motoyoshi,
nishida,
adelson,
materialperception
summary:
imagestatisticssrp
pdf:
http://persci.mit.edu/pub_pdfs/ImageStatisticsSRP.pdf
pageid:
ImageStatisticsSRP
type:
publication
 
publications/imagestatisticssrp.1363282817.txt.gz · Last modified: 2013/03/14 13:40 by lavanya