UNMIXING HYPERSPECTRAL IMAGES USING THE GENERALIZED BILINEAR MODEL

被引：53

作者：

Halimi, Abderrahim ^{[1
]}

Altmann, Yoann ^{[1
]}

Dobigeon, Nicolas ^{[1
]}

Tourneret, Jean-Yves ^{[1
]}

机构：

[1] Univ Toulouse, IRIT INP ENSEEIHT TeSA, Toulouse, France

来源：

2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2011年

关键词：

hyperspectral imagery; spectral unmixing; bilinear model; Bayesian inference; MCMC methods; gradient descent algorithm; least square algorithm;

D O I：

10.1109/IGARSS.2011.6049492

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Nonlinear models have recently shown interesting properties for spectral unmixing. This paper considers a generalized bilinear model recently introduced for unmixing hyperspectral images. Different algorithms are studied to estimate the parameters of this bilinear model. The positivity and sum-to-one constraints for the abundances are ensured by the proposed algorithms. The performance of the resulting unmixing strategy is evaluated via simulations conducted on synthetic and real data.

引用

页码：1886 / 1889

页数：4

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