B. Aiazzi, L. Alparone, S. Baronti, A. Garzelli, and M. Selva, 25 years of pansharpening: a critical review and new developments, Signal and Image Processing for Remote Sensing, pp.533-548, 2011.

L. Loncan, L. B. Almeida, J. M. Bioucas-dias, X. Briottet, J. Chanussot et al., Hyperspectral Pansharpening: A Review, IEEE Geoscience and Remote Sensing Magazine, vol.3, issue.3, pp.27-46, 2015.
DOI : 10.1109/MGRS.2015.2440094
URL : https://hal.archives-ouvertes.fr/hal-01403205

Q. Wei, N. Dobigeon, and J. Tourneret, Bayesian Fusion of Multi-Band Images, IEEE Journal of Selected Topics in Signal Processing, vol.9, issue.6, pp.1117-1127, 2015.
DOI : 10.1109/JSTSP.2015.2407855
URL : https://hal.archives-ouvertes.fr/hal-01187286

Q. Wei, J. Bioucas-dias, N. Dobigeon, and J. Tourneret, Hyperspectral and Multispectral Image Fusion Based on a Sparse Representation, IEEE Transactions on Geoscience and Remote Sensing, vol.53, issue.7, pp.3658-3668, 2015.
DOI : 10.1109/TGRS.2014.2381272
URL : https://hal.archives-ouvertes.fr/hal-01168121

M. Simoes, J. Bioucas-dias, L. Almeida, and J. Chanussot, A Convex Formulation for Hyperspectral Image Superresolution via Subspace-Based Regularization, IEEE Transactions on Geoscience and Remote Sensing, vol.53, issue.6, pp.3373-3388, 2015.
DOI : 10.1109/TGRS.2014.2375320
URL : https://hal.archives-ouvertes.fr/hal-01246551

B. Zhukov, D. Oertel, F. Lanzl, and G. , Unmixing-based multisensor multiresolution image fusion, IEEE Transactions on Geoscience and Remote Sensing, vol.37, issue.3, pp.1212-1226, 1999.
DOI : 10.1109/36.763276

M. T. Eismann and R. C. Hardie, Application of the stochastic mixing model to hyperspectral resolution enhancement, IEEE Transactions on Geoscience and Remote Sensing, vol.42, issue.9, pp.1924-1933, 2004.
DOI : 10.1109/TGRS.2004.830644

N. Yokoya, T. Yairi, and A. Lwasaki, Coupled Nonnegative Matrix Factorization Unmixing for Hyperspectral and Multispectral Data Fusion, IEEE Transactions on Geoscience and Remote Sensing, vol.50, issue.2, pp.528-537, 2012.
DOI : 10.1109/TGRS.2011.2161320

Z. An and Z. Shi, Hyperspectral image fusion by multiplication of spectral constraint and NMF, Optik - International Journal for Light and Electron Optics, vol.125, issue.13, pp.3150-3158, 2014.
DOI : 10.1016/j.ijleo.2014.01.005

B. Huang, H. Song, H. Cui, J. Peng, and Z. Xu, Spatial and Spectral Image Fusion Using Sparse Matrix Factorization, IEEE Transactions on Geoscience and Remote Sensing, vol.52, issue.3, pp.1693-1704, 2014.
DOI : 10.1109/TGRS.2013.2253612

]. E. Il, T. Wycoff, K. Chan, W. Jia, Y. Ma et al., A non-negative sparse promoting algorithm for high resolution hyperspectral imaging, Proc. IEEE lm. Conf Acoust. , Speech, and Signal Processing, pp.1409-1413, 2013.

Y. Zhang, S. De-backer, and P. Scheunders, Noise-Resistant Wavelet-Based Bayesian Fusion of Multispectral and Hyperspectral Images, IEEE Transactions on Geoscience and Remote Sensing, vol.47, issue.11, pp.3834-3843, 2009.
DOI : 10.1109/TGRS.2009.2017737

R. Kawakami, J. Wright, Y. Tai, Y. Matsushita, M. Ben-ezra et al., High-resolution hyperspectral imaging via rnatrix factorization, Proc. IEEE !nt. Conf Camp. Vision and Pattern Recognition (CVPR), pp.2329-2336, 2011.
DOI : 10.1109/cvpr.2011.5995457
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.221.3532

O. Berne, A. Helens, P. Pilleri, and C. Joblin, Non-negative matrix factorization pansharpening of hyperspectral data: An application to mid-infrared astronomy, 2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, pp.1-4, 2010.
DOI : 10.1109/WHISPERS.2010.5594900

X. He, L. Condat, J. Bioucas-dias, J. Chanussot, and J. Xia, A New Pansharpening Method Based on Spatial and Spectral Sparsity Priors, IEEE Transactions on Image Processing, vol.23, issue.9, pp.4160-4174, 2014.
DOI : 10.1109/TIP.2014.2333661
URL : https://hal.archives-ouvertes.fr/hal-01119229

M. A. Veganzones, M. Simôes, G. Licciardi, N. Yokoya, J. M. Bioucas-dias et al., Hyperspectral super-resolution of locally low rank images from complementary multisource data, IEEE Trans. Image Process, vol.2523, issue.1, pp.274-288, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01010408

J. Bieniarz, D. Cerra, J. Avbelj, P. Reinartz, and R. Müller, HYPERSPECTRAL IMAGE RESOLUTION ENHANCEMENT BASED ON SPECTRAL UNMIXING AND INFORMATION FUSION, Proc. JSPRS Hannover Workshop 2011: High-Resolution Earth Imaging for Geospatial Information
DOI : 10.5194/isprsarchives-XXXVIII-4-W19-33-2011
URL : http://elib.dlr.de/72671/1/contribution181.pdf

C. Lanaras, E. Baltsaias, and K. Schindler, ADVANCES IN HYPERSPECTRAL AND MULTISPECTRAL IMAGE FUSION AND SPECTRAL UNMIXING, ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol.3, issue.3, pp.451-458, 2015.
DOI : 10.5194/isprsarchives-XL-3-W3-451-2015

J. Bioucas-dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du et al., Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.5, issue.2, pp.354-379, 2012.
DOI : 10.1109/JSTARS.2012.2194696
URL : https://hal.archives-ouvertes.fr/hal-00760787

J. Amro, M. Mateos, R. Vega, A. K. Molina, and . Katsaggelos, A sm·vey of classical methods and new trends in pansharpening of multispectral images, EURASIP J. Adv. Signal Process, vol.2011, issue.79, pp.1-22, 2011.

M. Gonzalez-audîcana, J. L. Saleta, R. G. Catalân, and R. Garcîa, Fusion of multispectral and panchromatic images using improved IHS and PCA mergers based on wavelet decomposition, IEEE Transactions on Geoscience and Remote Sensing, vol.42, issue.6
DOI : 10.1109/TGRS.2004.825593

R. Geosci, . N. Sens, N. Yokoya, A. Mayumi, and . Lwasaki, Cross-calibration for data fusion of E0-1/Hyperion and Terra/ASTERBayesian fusion of multispectral and hyperspectral images using a block coordinate descent method, Proc. IEEE GRSS Workshop Hyperspectral Image Signal Process.: Evolution in Remote Sens. (WHISPERS), pp.1291-1299, 2004.

Q. Wei, N. Dobigeon, J. Tourneret, J. M. Bioucas-dias, and S. Godsill, R-FUSE: Robust Fast Fusion of Multiband Images Based on Solving a Sylvester Equation, IEEE Signal Processing Letters, vol.23, issue.11, 1818.
DOI : 10.1109/LSP.2016.2608858
URL : https://hal.archives-ouvertes.fr/hal-01407440

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

J. M. Bioucas-dias and J. M. Nascimento, Hyperspectral Subspace Identification, IEEE Transactions on Geoscience and Remote Sensing, vol.46, issue.8, pp.2435-2445, 2008.
DOI : 10.1109/TGRS.2008.918089
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.304.2548

N. Dobigeon, S. Moussaoui, M. Coulon, J. Tourneret, and A. O. Hero, Joint Bayesian Endmember Extraction and Linear Unmixing for Hyperspectral Imagery, IEEE Transactions on Signal Processing, vol.57, issue.11, pp.4355-4368, 2009.
DOI : 10.1109/TSP.2009.2025797
URL : https://hal.archives-ouvertes.fr/hal-00548758

S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein, Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers, Machine Learning, pp.1-122, 2011.
DOI : 10.1561/2200000016

Q. Wei, J. M. Bioucas-dias, N. Dobigeon, J. Tourneret, M. Chen et al., Multi-band image fusion based on spectral unrnixing," submitted

J. Eckstein and D. P. Bertsekas, On the Douglas???Rachford splitting method and the proximal point algorithm for maximal monotone operators, Mathematical Programming, pp.293-318, 1992.
DOI : 10.1007/BF01581204

. Tourneret, Fast single image super-resolution using a new analytical solution for /!2 -1!2 problems, IEEE Trans. Image Process, 2016.

M. Held, P. Wolfe, and H. P. Crowder, Validation of subgradient optimization, Mathematical programming, pp.62-88, 1974.
DOI : 10.1007/BF01580223

D. P. Bertsekas, Nonlinear programming, Athena Scientific, 1999.

Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli, Image Quality Assessment: From Error Visibility to Structural Similarity, IEEE Transactions on Image Processing, vol.13, issue.4, pp.600-612, 2004.
DOI : 10.1109/TIP.2003.819861
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.2477

J. M. Bioucas-dias, A variable splitting augmented Lagrangian approach to linear spectral unmixing, 2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, pp.1-4, 2009.
DOI : 10.1109/WHISPERS.2009.5289072