Open Access Paper
16 February 2007 Adaptation and perceptual norms
Michael A. Webster, Maiko Yasuda, Sara Haber, Deanne Leonard, Nicole Ballardini
Author Affiliations +
Proceedings Volume 6492, Human Vision and Electronic Imaging XII; 64921S (2007) https://doi.org/10.1117/12.730399
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States
Abstract
We used adaptation to examine the relationship between perceptual norms--the stimuli observers describe as psychologically neutral, and response norms--the stimulus levels that leave visual sensitivity in a neutral or balanced state. Adapting to stimuli on opposite sides of a neutral point (e.g. redder or greener than white) biases appearance in opposite ways. Thus the adapting stimulus can be titrated to find the unique adapting level that does not bias appearance. We compared these response norms to subjectively defined neutral points both within the same observer (at different retinal eccentricities) and between observers. These comparisons were made for visual judgments of color, image focus, and human faces, stimuli that are very different and may depend on very different levels of processing, yet which share the property that for each there is a well defined and perceptually salient norm. In each case the adaptation aftereffects were consistent with an underlying sensitivity basis for the perceptual norm. Specifically, response norms were similar to and thus covaried with the perceptual norm, and under common adaptation differences between subjectively defined norms were reduced. These results are consistent with models of norm-based codes and suggest that these codes underlie an important link between visual coding and visual experience.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael A. Webster, Maiko Yasuda, Sara Haber, Deanne Leonard, and Nicole Ballardini "Adaptation and perceptual norms", Proc. SPIE 6492, Human Vision and Electronic Imaging XII, 64921S (16 February 2007); https://doi.org/10.1117/12.730399
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Cited by 4 scholarly publications.
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KEYWORDS
Visualization

Receptors

Colorimetry

Visual process modeling

Color vision

Spatial frequencies

Image filtering

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