Paper
22 April 1996 Psychophysical methods for assessing visual comfort for a colored pattern of natural environment
Ken Sagawa, Yutaka Shimizu
Author Affiliations +
Proceedings Volume 2657, Human Vision and Electronic Imaging; (1996) https://doi.org/10.1117/12.238748
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States
Abstract
Humans visual comfort to a colored image of a natural scene presented on a CRT display was investigated by two psychophysical methods. One was to measure a number of colors contained in an image by using the categorical color naming technique and to correlate it to the subjective estimation of visual comfort. The other one was to find an optimum percent chroma for a whole image by continuously adjusting the chroma value of all the pixels in the image relatively from zero (achromatic image) to 100% (original chroma) and to correlate it also to the comfort estimation value. Experimental results show that both variables strongly correlated to the subjective estimation of comfort; that is, a negative correlation between the comfort estimation and the number of categorical colors, which means the larger the number of colors contained in an image, the less comfort the image is felt to have, and a positive correlation between the comfort estimation and the optimum percent chroma means that the less comfort pattern is apt to be seen in a reduced chroma while the comfort pattern remains in original chroma. These findings suggest that the visual comfort could be evaluated by the number of categorical colors in an image and the relative amount of chroma of a whole image.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ken Sagawa and Yutaka Shimizu "Psychophysical methods for assessing visual comfort for a colored pattern of natural environment", Proc. SPIE 2657, Human Vision and Electronic Imaging, (22 April 1996); https://doi.org/10.1117/12.238748
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Cited by 3 scholarly publications.
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KEYWORDS
Visualization

Nomenclature

Image analysis

CRTs

Image quality

Data analysis

Pollution control

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