J. M. Bioucas-dias, A. Plaza, N. Dobigeon, M. Parente, D. Qian et al., Hyperspectral unmixing overview: Geometrical, statistical, and sparse regression-based approaches, IEEE J. Sel. Topics Appl. Earth Observations Remote Sens, vol.5, issue.2, pp.354-379, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00760787

O. Eches, N. Dobigeon, and J. Y. Tourneret, Enhancing hyperspectral image unmixing with spatial correlations, IEEE Trans. Geosci. Remote Sens, vol.49, issue.11, pp.4239-4247, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00548759

C. Shi and L. Wang, Incorporating spatial information in spectral unmixing: A review, Remote Sens. Environment, vol.149, issue.0, pp.70-87, 2014.

M. D. Iordache, J. M. Bioucas-dias, and A. Plaza, Total variation spatial regularization for sparse hyperspectral unmixing, IEEE Trans. Geosci. Remote Sens, vol.50, issue.11, pp.4484-4502, 2012.

T. Uezato, R. J. Murphy, A. Melkumyan, and A. Chlingaryan, Incorporating spatial information and endmember variability into unmixing analyses to improve abundance estimates, IEEE Trans. Image Process, vol.25, 2016.

J. Liu, J. Zhang, Y. Gao, C. Zhang, and Z. Li, Enhancing spectral unmixing by local neighborhood weights, IEEE J. Sel. Topics Appl. Earth Observations Remote Sens, vol.5, issue.5, pp.1545-1552, 2012.

T. Uezato, R. J. Murphy, A. Melkumyan, and A. Chlingaryan, A novel spectral unmixing method incorporating spectral variability within endmember classes, IEEE Trans. Geosci. Remote Sens, vol.54, issue.5, pp.2812-2831, 2016.

L. Ni, L. Gao, S. Li, J. Li, and B. Zhang, Edge-constrained markov random field classification by integrating hyperspectral image with lidar data over urban areas, Journal of Applied Remote Sensing, vol.8, issue.1, pp.85-089, 2014.

A. Castrodad, T. Khuon, R. Rand, and G. Sapiro, Sparse modeling for hyperspectral imagery with lidar data fusion for subpixel mapping, Proc. IEEE Int. Conf. Geosci. Remote Sens. (IGARSS), pp.7275-7278, 2012.

M. Dalponte, L. Bruzzone, and D. Gianelle, Fusion of hyperspectral and lidar remote sensing data for classification of complex forest areas, IEEE Trans. Geosci. Remote Sens, vol.46, issue.5, pp.1416-1427, 2008.

T. Uezato, M. Fauvel, S. May, and N. Dobigeon, Hyperspectral image unmixing with LiDAR data-aided spatial regularization

T. Uezato, R. J. Murphy, A. Melkumyan, and A. Chlingaryan, A novel endmember bundle extraction and clustering approach for capturing spectral variability within endmember classes, IEEE Trans. Geosci. Remote Sens, vol.54, issue.11, 2016.