J. M. Bioucas-dias and A. Plaza, An overview on hyperspectral unmixing: geometrical, statistical, and sparse regression based approaches, Proceeding of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS'11, 2011.
DOI : 10.1109/igarss.2011.6049397
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.386.4860

S. Boyd and L. Vandenberghe, Convex optimization, 2004.

R. Bro, D. Jong, and S. , A fast non-negativity-constrained least squares algorithm, Journal of Chemometrics, vol.11, issue.5, pp.393-401, 1997.
DOI : 10.1002/(SICI)1099-128X(199709/10)11:5<393::AID-CEM483>3.0.CO;2-L

C. Chang, Hyperspectral data exploitation, 2007.
DOI : 10.1002/0470124628

E. Chouzenoux, S. Moussaoui, and J. Idier, Efficiency of linesearch strategies in interior point methods for linearly constrained signal restoration, Proceedings of the IEEE workshop on Statistical Signal Processing Workshop (SSP'11), pp.101-104, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00625901

R. N. Clark, G. A. Swayze, A. Gallagher, T. V. King, and W. M. Calvin, The U.S. geological survey digital spectral library: version 1 (0.2 to 3.0 µm). U.S. Geological Survey, Open File Rep, pp.93-592, 1993.
URL : https://hal.archives-ouvertes.fr/in2p3-00167014

A. Conn, N. Gould, and P. L. Toint, A primal-dual algorithm for minimizing a nonconvex function subject to bounds and nonlinear constraints, Nonlinear optimization and applications, 2 e éd, 1996.

L. C. Dixon, Conjugate Directions without Linear Searches, IMA Journal of Applied Mathematics, vol.11, issue.3, pp.317-328, 1973.
DOI : 10.1093/imamat/11.3.317

N. Dobigeon, S. Moussaoui, M. Coulon, J. Tourneret, and A. O. Hero, Algorithmes bayésiens pour le démélange supervisé, semi-supervisé et non supervisé d'images hyperspectrales, pp.79-108, 2010.
DOI : 10.3166/ts.27.79-108

N. Dobigeon, J. Tourneret, and C. Chang, Semi-Supervised Linear Spectral Unmixing Using a Hierarchical Bayesian Model for Hyperspectral Imagery, IEEE Transactions on Signal Processing, vol.56, issue.7, pp.2684-2695, 2008.
DOI : 10.1109/TSP.2008.917851
URL : https://hal.archives-ouvertes.fr/hal-00474880

A. S. El-bakry, R. A. Tapia, T. Tsuchiya, and Y. Zhang, On the formulation and theory of the Newton interior-point method for nonlinear programming, Journal of Optimization Theory and Applications, vol.26, issue.3, pp.507-541, 1996.
DOI : 10.1007/BF02275347

A. Forsgren and P. E. Gill, Primal-Dual Interior Methods for Nonconvex Nonlinear Programming, SIAM Journal on Optimization, vol.8, issue.4, pp.1132-1152, 1998.
DOI : 10.1137/S1052623496305560

A. Forsgren, P. E. Gill, and M. H. Wright, Interior Methods for Nonlinear Optimization, SIAM Review, vol.44, issue.4, pp.525-597, 2002.
DOI : 10.1137/S0036144502414942

D. Geman and G. Reynolds, Constrained restoration and the recovery of discontinuities, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.14, issue.3, pp.367-383, 1992.
DOI : 10.1109/34.120331

D. Geman and C. Yang, Nonlinear image recovery with half-quadratic regularization, IEEE Transactions on Image Processing, vol.4, issue.7, pp.932-946, 1995.
DOI : 10.1109/83.392335
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.53.7349

R. Green, Imaging Spectroscopy and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), Remote Sensing of Environment, vol.65, issue.3, pp.227-248, 1998.
DOI : 10.1016/S0034-4257(98)00064-9

G. Healey and D. Slater, Models and methods for automated material identification in hyperspectral imagery acquired under unknown illumination and atmospheric conditions, IEEE Transactions on Geoscience and Remote Sensing, vol.37, issue.6, pp.2706-2716, 1999.
DOI : 10.1109/36.803418

D. C. Heinz and C. Chang, Fully constrained least squares linear spectral mixture analysis method for material quantification in hyperspectral imagery, IEEE Transactions on Geoscience and Remote Sensing, vol.39, issue.3, pp.529-545, 2001.
DOI : 10.1109/36.911111

A. Huck, M. Guillaume, and J. Blanc-talon, Minimum Dispersion Constrained Nonnegative Matrix Factorization to Unmix Hyperspectral Data, IEEE Transactions on Geoscience and Remote Sensing, vol.48, issue.6, pp.2590-2602, 2010.
DOI : 10.1109/TGRS.2009.2038483
URL : https://hal.archives-ouvertes.fr/hal-01279698

J. Idier, Convex half-quadratic criteria and interacting auxiliary variables for image restoration, IEEE Transactions on Image Processing, vol.10, issue.7, pp.1001-1009, 2001.
DOI : 10.1109/83.931094
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.304.6240

C. A. Johnson, J. Seidel, and A. Sofer, Interior-point methodology for 3-D PET reconstruction, IEEE Transactions on Medical Imaging, vol.19, issue.4, pp.271-285, 2000.
DOI : 10.1109/42.848179
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.17.5645

N. Keshava and J. F. Mustard, Spectral unmixing, IEEE Signal Processing Magazine, vol.19, issue.1, pp.44-57, 2002.
DOI : 10.1109/79.974727

C. L. Lawson and R. J. Hanson, Solving least-squares problems, 1974.
DOI : 10.1137/1.9781611971217

S. Moussaoui, H. Hauksdóttir, F. Schmidt, and C. Jutten, On the decomposition of Mars hyperspectral data by ICA and Bayesian positive source separation, Neurocomputing, vol.71, issue.10-12, pp.10-12, 2008.
DOI : 10.1016/j.neucom.2007.07.034
URL : https://hal.archives-ouvertes.fr/hal-00272349

J. M. Nascimento and J. M. Bioucas-dias, Vertex component analysis: a fast algorithm to unmix hyperspectral data, IEEE Transactions on Geoscience and Remote Sensing, vol.43, issue.4, pp.898-910, 2005.
DOI : 10.1109/TGRS.2005.844293

M. Parente and A. Plaza, Survey of geometric and statistical unmixing algorithms for hyperspectral images, 2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2010.
DOI : 10.1109/WHISPERS.2010.5594929

A. Plaza, P. Martinez, R. Perez, and J. Plaza, A Quantitative and Comparative Analysis of Endmember Extraction Algorithms From Hyperspectral Data, IEEE Transactions on Geoscience and Remote Sensing, vol.42, issue.3, pp.650-663, 2004.
DOI : 10.1109/TGRS.2003.820314

J. R. Scott, Remote sensing: The image chain approach, 1997.

J. J. Settle and N. A. Drake, Linear mixing and the estimation of ground cover proportions, International Journal of Remote Sensing, vol.27, issue.6, pp.1159-1177, 1993.
DOI : 10.1109/36.103288

H. A. Van-der-vorst, Bi-CGSTAB: A Fast and Smoothly Converging Variant of Bi-CG for the Solution of Nonsymmetric Linear Systems, SIAM Journal on Scientific and Statistical Computing, vol.13, issue.2, pp.631-644, 1992.
DOI : 10.1137/0913035

G. Vane, R. O. Green, T. G. Chrien, H. T. Enmark, E. G. Hansen et al., The airborne visible/infrared imaging spectrometer (AVIRIS), Remote Sensing of Environment, vol.44, issue.2-3, pp.2-3, 1993.
DOI : 10.1016/0034-4257(93)90012-M

C. F. Van-loan, The ubiquitous Kronecker product, Journal of Computational and Applied Mathematics, vol.123, issue.1-2, pp.1-2, 2000.
DOI : 10.1016/S0377-0427(00)00393-9

M. H. Wright, Interior methods for constrained optimization, Acta Numerica, vol.26, pp.341-407, 1992.
DOI : 10.1007/BF02592025

M. H. Wright, Some properties of the Hessian of the logarithmic barrier function, Mathematical Programming, pp.265-295, 1994.
DOI : 10.1007/BF01582224

M. H. Wright, Ill-Conditioning and Computational Error in Interior Methods for Nonlinear Programming, SIAM Journal on Optimization, vol.9, issue.1, pp.84-111, 1998.
DOI : 10.1137/S1052623497322279