Hyperspectral endmember spectra extraction based on constrained linear-quadratic matrix factorization using a projected gradient method
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Yannick Deville | Moussa Sofiane Karoui | Abdelaziz Ouamri | Fatima Zohra Benhalouche | M. S. Karoui | Y. Deville | A. Ouamri
[1] Pierre Comon,et al. Handbook of Blind Source Separation: Independent Component Analysis and Applications , 2010 .
[2] Gene H. Golub,et al. Matrix Computations, Third Edition , 1996 .
[3] Yannick Deville,et al. Matrix factorization for bilinear blind source separation: Methods, separability and conditioning , 2015, 2015 23rd European Signal Processing Conference (EUSIPCO).
[4] Alfred O. Hero,et al. Nonlinear Unmixing of Hyperspectral Images: Models and Algorithms , 2013, IEEE Signal Processing Magazine.
[5] Robert H. Halstead,et al. Matrix Computations , 2011, Encyclopedia of Parallel Computing.
[6] Antonio J. Plaza,et al. Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[7] Y. Deville. Blind Source Separation and Blind Mixture Identification Methods , 2016 .
[8] Yannick Deville,et al. Linear-Quadratic Blind Source Separation Using NMF to Unmix Urban Hyperspectral Images , 2014, IEEE Transactions on Signal Processing.
[9] Yannick Deville,et al. An Overview of Blind Source Separation Methods for Linear-Quadratic and Post-nonlinear Mixtures , 2015, LVA/ICA.
[10] J. Webster,et al. Wiley Encyclopedia of Electrical and Electronics Engineering , 2010 .
[11] Andrzej Cichocki,et al. Nonnegative Matrix and Tensor Factorization T , 2007 .
[12] Yannick Deville,et al. Linear–Quadratic Mixing Model for Reflectances in Urban Environments , 2014, IEEE Transactions on Geoscience and Remote Sensing.