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Proceedings Paper

An image-dependent model of veiling glare effects on detection performance in large-luminance-range displays
Author(s): Mina Choi; Luigi Albani; Aldo Badano
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Paper Abstract

One limitation of visual detection tasks in complex scenes with a large range of luminance values is the decrease in sensitivity due to veiling glare in the display device and in the human eye caused by unwanted light scattering. We used our previously measured results regarding the increase in detection thresholds due to veiling glare to formulate an empirical model for this phenomenon. Our results are based on a ring glare source and a Gaussian target on white noise using a dual-layer, high-dynamic-range liquid-crystal display prototype. The thresholds, measured using a double-random staircase technique with added signal-absent images, are modeled as a function of illuminance at the eyes and angular distance between the veiling glare source and the detection target. In this work, we model increases in detection contrast thresholds due to veiling glare for any image by calculating the contribution of each display pixel. We validate our model by determining threshold increases for the set of experimental results previously obtained with human subjects. Our imagedependent model predicts how the contrast threshold is affected by veiling glare for any target location. Finally, we discuss the range of validity of our model and show predictions for sample mammography, chest CT, and chest radiography images displayed on large-luminance-range devices.

Paper Details

Date Published: 28 February 2012
PDF: 10 pages
Proc. SPIE 8318, Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment, 831804 (28 February 2012); doi: 10.1117/12.913649
Show Author Affiliations
Mina Choi, U.S. Food and Drug Administration (United States)
Luigi Albani, BARCO FIMI (Italy)
Aldo Badano, U.S. Food and Drug Administration (United States)

Published in SPIE Proceedings Vol. 8318:
Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment
Craig K. Abbey; Claudia R. Mello-Thoms, Editor(s)

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