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Proceedings Paper

Psychometric correlates of the effects of image-enhancing algorithms on visual performance
Author(s): George A. Reis; Kelly E. Neriani; Alan R. Pinkus; Eric L. Heft
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Paper Abstract

Future military imaging devices will have computational capabilities that will allow agile, real-time image enhancement. In preparing for such devices, numerous image enhancement algorithms should be studied. However, these algorithms need evaluating in terms of human visual performance using military-relevant imagery. Evaluating these algorithms through objective performance measures requires extensive time and resources. We investigated several subjective methodologies for down-selecting algorithms to be studied in future research. Degraded imagery was processed using six algorithms and then ranked along with the original non-degraded and degraded imagery through the method of paired comparisons and the method of magnitude estimation, in terms of subjective attitude. These rankings were then compared to objective performance measures: reaction times and errors in finding targets in the processed imagery. In general, we found associations between subjective and objective measures. This leads us to believe that subjective assessment may provide an easy and fast way for down-selecting algorithms but at the same time should not be used in place of objective performance-based measures.

Paper Details

Date Published: 19 May 2006
PDF: 10 pages
Proc. SPIE 6226, Enhanced and Synthetic Vision 2006, 62260P (19 May 2006); doi: 10.1117/12.665541
Show Author Affiliations
George A. Reis, Air Force Research Lab. (United States)
Kelly E. Neriani, Air Force Research Lab. (United States)
Consortium Research Fellows Program (United States)
Alan R. Pinkus, Air Force Research Lab. (United States)
Eric L. Heft, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 6226:
Enhanced and Synthetic Vision 2006
Jacques G. Verly; Jeff J. Guell, Editor(s)

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