Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/68285
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Type: Journal article
Title: Super-resolution of infrared images: does it improve operator object detection performance?
Author: Hanton, K.
Sunde, J.
Butavicius, M.
Burns, N.
Citation: Journal of Computing and Information Technology, 2010; 18(2):141-150
Publisher: Sveucilisni Racunski Centar
Issue Date: 2010
ISSN: 1330-1136
1846-3908
Statement of
Responsibility: 
Catherine Hanton, Jadranka Sunde, Marcus Butavicius and Nicholas R. Burns
Abstract: The ability to detect dangerous objects (such as improvised explosive devices) from a distance is important in security and military environments. Standoff imaging can produce images that have been degraded by atmospheric turbulence, movement, blurring and other factors. The number and size of pixels in the imaging sensor can also contribute to image degradation through under-sampling of the image. Establishing processes that enhance degraded or under-sampled infrared images so that objects of interest can be recognised with more certainty is important. In this paper, super-resolution image reconstruction and deconvolution methods are explored, with an emphasis on quantifying and understanding human operator detection performance.
Keywords: standoff detection; infrared imaging; superresolution; performance improvement measure
Rights: Copyright 2010 Sveuciliste U Zagrebu
RMID: 0020113741
DOI: 10.2498/cit.1001813
Appears in Collections:Psychology publications

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