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Communication Dans Un Congrès Année : 2014

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

Résumé

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.
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Dates et versions

hal-01128418 , version 1 (09-03-2015)

Identifiants

Citer

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