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19 May 2006 Psychometric correlates of the effects of image-enhancing algorithms on visual performance
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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.
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George A. Reis, Kelly E. Neriani, Alan R. Pinkus, and Eric L. Heft "Psychometric correlates of the effects of image-enhancing algorithms on visual performance", Proc. SPIE 6226, Enhanced and Synthetic Vision 2006, 62260P (19 May 2006);

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