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Optimizing Object, Atmosphere, and Sensor Parameters in Thermal Hyperspectral Imagery
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten. FOI, SE-58111 Linkoping, Sweden.ORCID-id: 0000-0002-6763-5487
2017 (engelsk)Inngår i: IEEE Transactions on Geoscience and Remote Sensing, ISSN 0196-2892, E-ISSN 1558-0644, Vol. 55, nr 2, s. 658-670Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

We address the problem of estimating atmosphere parameters (temperature and water vapor content) from data captured by an airborne thermal hyperspectral imager and propose a method based on linear and nonlinear optimization. The method is used for the estimation of the parameters (temperature and emissivity) of the observed object as well as sensor gain under certain restrictions. The method is analyzed with respect to sensitivity to noise and the number of spectral bands. Simulations with synthetic signatures are performed to validate the analysis, showing that the estimation can be performed with as few as 10-20 spectral bands at moderate noise levels. The proposed method is also extended to exploit additional knowledge, for example, measurements of atmospheric parameters and sensor noise. Additionally, we show how to extend the method in order to improve spectral calibration.

sted, utgiver, år, opplag, sider
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2017. Vol. 55, nr 2, s. 658-670
Emneord [en]
Infrared imaging; infrared spectroscopy; optimization methods; remote sensing
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-134597DOI: 10.1109/TGRS.2016.2613685ISI: 000392391800004OAI: oai:DiVA.org:liu-134597DiVA, id: diva2:1076021
Merknad

Funding Agencies|Swedish Research Council under Project EMC2

Tilgjengelig fra: 2017-02-21 Laget: 2017-02-21 Sist oppdatert: 2017-11-29

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