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Proceedings Paper

RGB-NIR image fusion: metric and psychophysical experiments
Author(s): Alex E. Hayes; Graham D. Finlayson; Roberto Montagna
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Paper Abstract

In this paper, we compare four methods of fusing visible RGB and near-infrared (NIR) images to produce a color output image, using a psychophysical experiment and image fusion quality metrics. The results of the psychophysical experiment show that two methods are significantly preferred to the original RGB image, and therefore RGB-NIR image fusion may be useful for photographic enhancement in those cases. The Spectral Edge method is the most preferred method, followed by the dehazing method of Schaul et al. We then investigate image fusion metrics which give results correlated with the psychophysical experiment results. We extend several existing metrics from 2 to 1 to M to N channel image fusion, as well as introducing new metrics based on output image colorfulness and contrast, and test them on our experimental data. While none of the individual metrics gives a ranking of the algorithms which exactly matches that of the psychophysical experiment, through a combination of two metrics we accurately rank the two leading fusion methods.

Paper Details

Date Published: 8 February 2015
PDF: 9 pages
Proc. SPIE 9396, Image Quality and System Performance XII, 93960U (8 February 2015); doi: 10.1117/12.2079224
Show Author Affiliations
Alex E. Hayes, Univ. of East Anglia (United Kingdom)
Graham D. Finlayson, Univ. of East Anglia (United Kingdom)
Roberto Montagna, Spectral Edge Ltd. (United Kingdom)

Published in SPIE Proceedings Vol. 9396:
Image Quality and System Performance XII
Mohamed-Chaker Larabi; Sophie Triantaphillidou, Editor(s)

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