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

Manuel Cubero-Castan, Jocelyn Chanussot, Xavier Briottet, Michal Shimoni, Véronique Achard

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdragepeer review

Samenvatting

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.

Originele taal-2Engels
Titel2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
UitgeverijInstitute of Electrical and Electronics Engineers Inc.
Pagina's7809-7813
Aantal pagina's5
ISBN van geprinte versie9781479928927
DOI's
StatusGepubliceerd - 2014
Evenement2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italië
Duur: 4 mei 20149 mei 2014

Publicatie series

NaamICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN van geprinte versie1520-6149

Congres

Congres2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
Land/RegioItalië
StadFlorence
Periode4/05/149/05/14

Vingerafdruk

Duik in de onderzoeksthema's van 'An unmixing-based method for the analysis of thermal hyperspectral images'. Samen vormen ze een unieke vingerafdruk.

Citeer dit