pthouvenin / robust-unmixing-plmm

A hierarchical Bayesian model accounting for endmember variability and abrupt spectral changes to unmix multitemporal hyperspectral images

A hierarchical Bayesian model accounting for endmember variability and abrupt spectral changes to unmix multitemporal hyperspectral images

Description: Matlab codes associated with the method described in

P.-A. Thouvenin, N. Dobigeon and J.-Y. Tourneret - A hierarchical Bayesian model accounting for endmember variability and abrupt spectral changes to unmix multitemporal hyperspectral images, IEEE Trans. Comput. Imag., vol. 4, no. 1, pp. 32-45, Mar. 2018.

Author: P.-A. Thouvenin, pierreantoine[dot]thouvenin[at]gmail[dot]com

Experiments: to run a representative example of the real data experiments reported in the article, configure and run the main_real_data.m script. The script main_extract_data.m can be used to extract the hyperspectral data from the raw data file included in the data/raw_data folder. A .mat file obtained after data extraction is already provided in the data folder.

Dependencies: the present codes includes MATLAB functions described in the following publications, and developed by their respective authors.

[1] J. M. Nascimento and J. M. Bioucas-Dias - Vertex component analysis: a fast algorithm to unmix hyperspectral data, IEEE Trans. Geosci. Remote Sens., vol. 43, no. 4, pp. 898--910, Apr. 2005.

[2] J. M. Bioucas-Dias and M. A. T. Figueiredo - Alternating direction algorithms for constrained sparse regression: Application to hyperspectral unmixing, Proc. IEEE GRSS Workshop Hyperspectral Image Signal Process.: Evolution in Remote Sens. (WHISPERS)., Reykjavik, Iceland, Jun. 2010.

[3] J. Bioucas-Dias and J. Nascimento - Hyperspectral subspace identification, IEEE Transactions on Geoscience and Remote Sensing., vol. 46, no. 8, pp. 2435-2445, 2008.

[4] J. M. Bioucas-Dias - A variable splitting augmented Lagrangian approach to linear spectral unmixing, Proc. IEEE GRSS Workshop Hyperspectral Image Signal Process.: Evolution in Remote Sens. (WHISPERS)., Grenoble, France, Aug. 2009.

[5] V. Mazet, - Simulation d'une distribution gaussienne tronquée sur un intervalle fini, Technical Report, Université de Strasbourg/CNRS, 2012. [Code]

[6] J. Tursa, MTIMESX - Fast Matrix Multiply with Multi-Dimensional Support, [Code on Matlab FileExchange], [Code on Github]