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Communication Dans Un Congrès Année : 2011

A polynomial post nonlinear model for hyperspectral image unmixing

Résumé

This paper studies estimation algorithms for nonlinear hyperspectral image unmixing. The proposed unmixing model assumes that the pixel reflectances are polynomial functions of linear mixtures of pure spectral components contaminated by an additive white Gaussian noise. A hierarchical Bayesian algorithm and an optimization method are proposed for solving the resulting unmixing problem. The parameters involved in the proposed model satisfy constraints that are naturally included in the estimation procedure. The performance of the unmixing strategies is evaluated thanks to simulations conducted on synthetic and real data.
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Dates et versions

hal-04241321 , version 1 (13-10-2023)

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Yoann Altmann, Abderrahim Halimi, Nicolas Dobigeon, Jean-Yves Tourneret. A polynomial post nonlinear model for hyperspectral image unmixing. IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2011), IEEE, Jul 2011, Vancouver, Canada. pp.1882--1885, ⟨10.1109/IGARSS.2011.6049491⟩. ⟨hal-04241321⟩
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