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Proceedings Paper

Estimating atmosphere parameters in hyperspectral data
Author(s): Jörgen Ahlberg
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Paper Abstract

We address the problem of estimating atmosphere parameters (temperature, water vapour content) from data captured by an airborne thermal hyperspectral imager, and propose a method based on direct optimization. The method also involves the estimation of object parameters (temperature and emissivity) under the restriction that the emissivity is constant for all wavelengths. Certain sensor parameters can be estimated as well in the same process. The method is analyzed with respect to sensitivity to noise and number of spectral bands. Simulations with synthetic signatures are performed to validate the analysis, showing that estimation can be performed with as few as 10-20 spectral bands at moderate noise levels. More than 20 bands does not improve the estimates. The proposed method is also extended to incorporate additional knowledge, for example measurements of atmospheric parameters and sensor noise.

Paper Details

Date Published: 12 May 2010
PDF: 8 pages
Proc. SPIE 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI, 76952A (12 May 2010); doi: 10.1117/12.851321
Show Author Affiliations
Jörgen Ahlberg, Swedish Defence Research Agency (Sweden)


Published in SPIE Proceedings Vol. 7695:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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