Literature DB >> 17926193

Seasonal variations in the color statistics of natural images.

Michael A Webster1, Yoko Mizokami, Shernaaz M Webster.   

Abstract

We examined how the distribution of colors in natural images varies as the seasons change. Images of natural outdoor scenes were acquired at locations in the Western Ghats, India, during monsoon and winter seasons and in the Sierra Nevada, USA, from spring to fall. The images were recorded with an RGB digital camera calibrated to yield estimates of the L, M, and S cone excitations and chromatic and luminance contrasts at each pixel. These were compared across time and location and were analyzed separately for regions of earth and sky. Seasonal climate changes alter both the average color in scenes and how the colors are distributed around the average. Arid periods are marked by a mean shift toward the +L pole of the L vs. M chromatic axis and a rotation in the color distributions away from the S vs. LM chromatic axis and toward an axis of bluish-yellowish variation, both primarily due to changes in vegetation. The form of the change was similar at the two locations suggesting that the color statistics of natural images undergo a characteristic pattern of temporal variation. We consider the implications of these changes for models of both visual sensitivity and color appearance.

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Year:  2007        PMID: 17926193     DOI: 10.1080/09548980701654405

Source DB:  PubMed          Journal:  Network        ISSN: 0954-898X            Impact factor:   1.273


  27 in total

1.  Visualizing Visual Adaptation.

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

2.  Surface color and predictability determine contextual modulation of V1 firing and gamma oscillations.

Authors:  Alina Peter; Cem Uran; Pascal Fries; Martin Vinck; Johanna Klon-Lipok; Rasmus Roese; Sylvia van Stijn; William Barnes; Jarrod R Dowdall; Wolf Singer
Journal:  Elife       Date:  2019-02-04       Impact factor: 8.140

3.  Adjusting to a sudden “aging” of the lens.

Authors:  Katherine E M Tregillus; John S Werner; Michael A Webster
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2016-03       Impact factor: 2.129

4.  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

5.  Color naming across languages reflects color use.

Authors:  Edward Gibson; Richard Futrell; Julian Jara-Ettinger; Kyle Mahowald; Leon Bergen; Sivalogeswaran Ratnasingam; Mitchell Gibson; Steven T Piantadosi; Bevil R Conway
Journal:  Proc Natl Acad Sci U S A       Date:  2017-09-18       Impact factor: 11.205

6.  Color variance and achromatic settings.

Authors:  Siddhart S Rajendran; Michael A Webster
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2020-04-01       Impact factor: 2.129

7.  The Verriest Lecture: Adventures in blue and yellow.

Authors:  Michael A Webster
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2020-04-01       Impact factor: 2.129

8.  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

9.  Colour appearance and compensation in the near periphery.

Authors:  Michael A Webster; Kimberley Halen; Andrew J Meyers; Patricia Winkler; John S Werner
Journal:  Proc Biol Sci       Date:  2010-02-10       Impact factor: 5.349

10.  A simple principled approach for modeling and understanding uniform color metrics.

Authors:  Kevin A G Smet; Michael A Webster; Lorne A Whitehead
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2016-03       Impact factor: 2.129

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