Visual detection of spatial contrast patterns: evaluation of five simple models.

A B Watson

doi:10.1364/oe.6.000012

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Visual detection of spatial contrast patterns: evaluation of five simple models.

A B Watson

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Abstract

The ModelFest Phase One dataset is a collection of luminance contrast thresholds for 43 two-dimensional monochromatic spatial patterns confined to an area of approximately two by two degrees. These data were collected by a collaboration among twelve laboratories, and were designed to provide a common database for calibration and testing of spatial vision models. Here I report fits of the ModelFest data with five models: Peak Contrast, Contrast Energy, Generalized Energy, a Gabor Channels model, and a Discrete Cosine Transform model. The Gabor Channels model provides the best fit, though the other, simpler models, with the exception of Peak Contrast, provide remarkably good fits as well. Though there are clear individual differences, regularities in the data suggest the possibility of constructing a standard observer for spatial vision.

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Contrast Sensitivity Data Display Ergonomics Evaluation Studies as Topic Humans Models, Psychological Models, Statistical Pattern Recognition, Visual Psychophysics Sensory Thresholds Vision, Ocular NASA Center ARC NASA Discipline Space Human Factors Comparative Study Journal Article Research Support, U.S. Gov't, Non-P.H.S.

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A B Watson. 2000-01-03. Visual detection of spatial contrast patterns: evaluation of five simple models.. https://doi.org/10.1364/oe.6.000012

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