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J. Imaging 2019, 5(1), 6; https://doi.org/10.3390/jimaging5010006

A Low-Rate Video Approach to Hyperspectral Imaging of Dynamic Scenes

1
Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623-5603, USA
2
School of Mathematical Sciences, Rochester Institute of Technology, Rochester, NY 14623-5603, USA
Current address: Harris Corporation, Rochester, NY 14623, USA.
*
Author to whom correspondence should be addressed.
Received: 10 November 2018 / Revised: 14 December 2018 / Accepted: 26 December 2018 / Published: 31 December 2018
(This article belongs to the Special Issue The Future of Hyperspectral Imaging)
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Abstract

The increased sensitivity of modern hyperspectral line-scanning systems has led to the development of imaging systems that can acquire each line of hyperspectral pixels at very high data rates (in the 200–400 Hz range). These data acquisition rates present an opportunity to acquire full hyperspectral scenes at rapid rates, enabling the use of traditional push-broom imaging systems as low-rate video hyperspectral imaging systems. This paper provides an overview of the design of an integrated system that produces low-rate video hyperspectral image sequences by merging a hyperspectral line scanner, operating in the visible and near infra-red, with a high-speed pan-tilt system and an integrated IMU-GPS that provides system pointing. The integrated unit is operated from atop a telescopic mast, which also allows imaging of the same surface area or objects from multiple view zenith directions, useful for bi-directional reflectance data acquisition and analysis. The telescopic mast platform also enables stereo hyperspectral image acquisition, and therefore, the ability to construct a digital elevation model of the surface. Imaging near the shoreline in a coastal setting, we provide an example of hyperspectral imagery time series acquired during a field experiment in July 2017 with our integrated system, which produced hyperspectral image sequences with 371 spectral bands, spatial dimensions of 1600 × 212, and 16 bits per pixel, every 0.67 s. A second example times series acquired during a rooftop experiment conducted on the Rochester Institute of Technology campus in August 2017 illustrates a second application, moving vehicle imaging, with 371 spectral bands, 16 bit dynamic range, and 1600 × 300 spatial dimensions every second. View Full-Text
Keywords: hyperspectral; video; imaging; coastal dynamics; moving vehicle imaging; bi-directional reflectance distribution function (BRDF); hemispherical conical reflectance factor (HCRF); stereo imaging; digital elevation model; Virginia Coast Reserve Long Term Ecological Research (VCR LTER) hyperspectral; video; imaging; coastal dynamics; moving vehicle imaging; bi-directional reflectance distribution function (BRDF); hemispherical conical reflectance factor (HCRF); stereo imaging; digital elevation model; Virginia Coast Reserve Long Term Ecological Research (VCR LTER)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Bachmann, C.M.; Eon, R.S.; Lapszynski, C.S.; Badura, G.P.; Vodacek, A.; Hoffman, M.J.; McKeown, D.; Kremens, R.L.; Richardson, M.; Bauch, T.; Foote, M. A Low-Rate Video Approach to Hyperspectral Imaging of Dynamic Scenes. J. Imaging 2019, 5, 6.

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