An unmixing-based method for the analysis of thermal hyperspectral images

Abstract : The estimation of surface emissivity and temperature from thermal hyperspectral data is a challenge. Methods that estimate the temperature and emissivity on a pixel composed by one single material exist. However, the estimation of the temperature on a mixed pixel, i.e. a pixel composed by more than one material, is more complex and has scarcely been investigated in the literature. This paper addresses this issue by proposing an estimator which linearizes the Black Body law around the mean temperature of each material. The performance of this estimator is studied using simulated data with different hyperspectral sensor configurations and under various noise conditions. The obtained results are encouraging and show an accuracy on the estimated temperature of 0.5 K while using high spectral resolution sensor.
Type de document :
Communication dans un congrès
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2014), May 2014, Florence, Italy. Proceedings of ICASSP 2014, pp.7809-7813, 〈10.1109/ICASSP.2014.6855120〉
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http://hal.univ-grenoble-alpes.fr/hal-01128418
Contributeur : Vincent Couturier-Doux <>
Soumis le : lundi 9 mars 2015 - 16:42:29
Dernière modification le : lundi 9 avril 2018 - 12:22:34

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Manuel Cubero-Castan, Jocelyn Chanussot, X.. Briottet, M. Shimoni, Vincent Achard. An unmixing-based method for the analysis of thermal hyperspectral images. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2014), May 2014, Florence, Italy. Proceedings of ICASSP 2014, pp.7809-7813, 〈10.1109/ICASSP.2014.6855120〉. 〈hal-01128418〉

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