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Proceedings Paper

Development of an image/threshold database for designing and testing human vision models
Author(s): Thom Carney; Stanley A. Klein; Christopher W. Tyler; Amnon D. Silverstein; Brent Beutter; Dennis Levi; Andrew B. Watson; Adam J. Reeves; Anthony M. Norcia; Chien-Chung Chen; Walter Makous; Miguel P. Eckstein
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Paper Abstract

Models that predict human performance on narrow classes of visual stimuli abound in the vision science literature. However, the vision and the applied imaging communities need robust general-purpose, rather than narrow, computational human visual system models to evaluate image fidelity and quality and ultimately improve imaging algorithms. Psychophysical measure of image imaging algorithms. Psychophysical measures of image quality are too costly and time consuming to gather to evaluate the impact each algorithm modification might have on image quality.

Paper Details

Date Published: 19 May 1999
PDF: 10 pages
Proc. SPIE 3644, Human Vision and Electronic Imaging IV, (19 May 1999); doi: 10.1117/12.348473
Show Author Affiliations
Thom Carney, Neurometrics Institute and Univ. of California/Berkeley (United States)
Stanley A. Klein, Univ. of California/Berkeley (United States)
Christopher W. Tyler, Smith-Kettlewell Eye Research Institute (United States)
Amnon D. Silverstein, Hewlett-Packard Labs. (United States)
Brent Beutter, NASA Ames Research Ctr. (United States)
Dennis Levi, Univ. of Houston (United States)
Andrew B. Watson, NASA Ames Research Ctr. (United States)
Adam J. Reeves, Northeastern Univ. (United States)
Anthony M. Norcia, Smith-Kettlewell Eye Research Institute (United States)
Chien-Chung Chen, Smith-Kettlewell Eye Research Institute (Canada)
Walter Makous, Univ. of Rochester (United States)
Miguel P. Eckstein, Cedars-Sinai Medical Ctr. (United States)


Published in SPIE Proceedings Vol. 3644:
Human Vision and Electronic Imaging IV
Bernice E. Rogowitz; Thrasyvoulos N. Pappas, Editor(s)

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