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Supervised nonlinear spectral unmixing using a post-nonlinear mixing model for hyperspectral imagery

Altmann, Yoann and Halimi, Abderrahim and Dobigeon, Nicolas and Tourneret, Jean-Yves Supervised nonlinear spectral unmixing using a post-nonlinear mixing model for hyperspectral imagery. (2012) IEEE Transactions on Image Processing, vol. 21 (n° 6). pp. 3017-3025. ISSN 1057-7149

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Official URL: http://dx.doi.org/10.1109/TIP.2012.2187668

Abstract

This paper presents a nonlinear mixing model for hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are nonlinear functions of pure spectral components contaminated by an additive white Gaussian noise. These nonlinear functions are approximated using polynomial functions leading to a polynomial postnonlinear mixing model. A Bayesian algorithm and optimization methods are proposed to estimate the parameters involved in the model. The performance of the unmixing strategies is evaluated by simulations conducted on synthetic and real data.

Item Type:Article
Additional Information:Thanks to IEEE. The original publication is available at http://ieeexplore.ieee.org/Xplore/home.jsp
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT
Université de Toulouse > Université Paul Sabatier-Toulouse III - UPS
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Deposited By: Nicolas DOBIGEON

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