Literature DB >> 9425544

Adaptation and the color statistics of natural images.

M A Webster1, J D Mollon.   

Abstract

Color perception depends profoundly on adaptation processes that adjust sensitivity in response to the prevailing pattern of stimulation. We examined how color sensitivity and appearance might be influenced by adaptation to the color distributions characteristic of natural images. Color distributions were measured for natural scenes by sampling an array of locations within each scene with a spectroradiometer, or by recording each scene with a digital camera successively through 31 interference filters. The images were used to reconstruct the L, M and S cone excitation at each spatial location, and the contrasts along three post-receptoral axes [L + M, L - M or S - (L + M)]. Individual scenes varied substantially in their mean chromaticity and luminance, in the principal color-luminance axes of their distributions, and in the range of contrasts in their distributions. Chromatic contrasts were biased along a relatively narrow range of bluish to yellowish-green angles, lying roughly between the S - (L + M) axis (which was more characteristic of scenes with lush vegetation and little sky) and a unique blue-yellow axis (which was more typical of arid scenes). For many scenes L - M and S - (L + M) signals were highly correlated, with weaker correlations between luminance and chromaticity. We use a two-stage model (von Kries scaling followed by decorrelation) to show how the appearance of colors may be altered by light adaptation to the mean of the distributions and by contrast adaptation to the contrast range and principal axes of the distributions; and we show that such adjustments are qualitatively consistent with empirical measurements of asymmetric color matches obtained after adaptation to successive random samples drawn from natural distributions of chromaticities and lightnesses. Such adaptation effects define the natural range of operating states of the visual system.

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Year:  1997        PMID: 9425544     DOI: 10.1016/s0042-6989(97)00125-9

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  51 in total

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3.  Nonlinearities in color coding: compensating color appearance for the eye's spectral sensitivity.

Authors:  Yoko Mizokami; John S Werner; Michael A Crognale; Michael A Webster
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4.  Spatial ensemble statistics are efficient codes that can be represented with reduced attention.

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5.  Microcircuitry and mosaic of a blue-yellow ganglion cell in the primate retina.

Authors:  D J Calkins; Y Tsukamoto; P Sterling
Journal:  J Neurosci       Date:  1998-05-01       Impact factor: 6.167

6.  Visualizing Visual Adaptation.

Authors:  Michael A Webster; Katherine E M Tregillus
Journal:  J Vis Exp       Date:  2017-04-24       Impact factor: 1.355

7.  Emergence of Binocular Disparity Selectivity through Hebbian Learning.

Authors:  Tushar Chauhan; Timothée Masquelier; Alexandre Montlibert; Benoit R Cottereau
Journal:  J Neurosci       Date:  2018-09-21       Impact factor: 6.167

8.  Individual differences in visual science: What can be learned and what is good experimental practice?

Authors:  John D Mollon; Jenny M Bosten; David H Peterzell; Michael A Webster
Journal:  Vision Res       Date:  2017-11-16       Impact factor: 1.886

9.  Individual and age-related variation in chromatic contrast adaptation.

Authors:  Sarah L Elliott; John S Werner; Michael A Webster
Journal:  J Vis       Date:  2012-08-17       Impact factor: 2.240

10.  The brightness of colour.

Authors:  David Corney; John-Dylan Haynes; Geraint Rees; R Beau Lotto
Journal:  PLoS One       Date:  2009-03-31       Impact factor: 3.240

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