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Proceedings Paper

Perception of achromatic, monochromatic, pure chromatic, and chromatic noisy images by real human-observer under threshold conditions
Author(s): Nikolay N. Krasilnikov; Olga I. Krasilnikova; Yury E. Shelepin
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Paper Abstract

In the experimental verification of the ideal observer theory applicability to observation of: achromatic, monochromatic, pure chromatic and chromatic noisy images by real human- observer under threshold conditions we used the method of comparative measurements. We measured and compared the correct identification probabilities of the test objects in noisy above mentioned images by real human-observer and computer model of ideal observer. For the case when we have no full knowledge about test objects parameters we've developed the modified Zigert-Kotelnikov algorithm and appropriate model. In particular, when all image parameters are a priory known, this algorithm coincides with the ideal observer one. We formulated 3 new laws of matched filtering of exactly known color images and concluded that the probabilities of correct identification by the observer and by the computer model are in good agreement in a wide range of noise intensities. Absence of a priori information about test objects coordinates unlike test objects sizes information influences greatly on the correct identification probabilities. Our results are useful in modeling of human vision under threshold conditions. The developed model may be effectively used for estimation of picture quality impairment on the monitor screen, the diagnostic of the human visual system condition, etc.

Paper Details

Date Published: 14 April 2000
PDF: 8 pages
Proc. SPIE 3981, Medical Imaging 2000: Image Perception and Performance, (14 April 2000); doi: 10.1117/12.383093
Show Author Affiliations
Nikolay N. Krasilnikov, State Univ. of Aerospace Instrumentation (Russia)
Olga I. Krasilnikova, State Univ. of Aerospace Instrumentation (Russia)
Yury E. Shelepin, Pavlov Institute of Physiology (Russia)

Published in SPIE Proceedings Vol. 3981:
Medical Imaging 2000: Image Perception and Performance
Elizabeth A. Krupinski, Editor(s)

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