%% This set of files contains the Matlab code
%% for the generalized compposite kernel paper intoduced in the following paper
%
%  [1] J. Li, P. R. Marpu, A. Plaza, J. M. Bioucas-Dias and J. A.Benediktsson. 
%  Generalized Composite Kernel Framework for Hyperspectral Image Classification.
%  IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 9, pp. 4816-4829,2013.
%
%%  and for the composite kernel paper
%
% [2] G. Camps-Valls, L. Gomez-Chova, J. Muoz-Mar, J. Vila-Francs, and J. Calpe-Maravilla, 
% “Composite kernels for hyperspectral image classi?cation,” 
% IEEE Geosci. Remote Sens. Lett., vol. 3, no. 1, pp. 93–97, Jan. 2006
%
%% the spatial information is built based on the Attribute profiles:
%
% [3] M. D. Mura, J. A. Benediktsson, B. Waske, and L. Bruzzone, 
% “Morphological attribute pro?les for the analysis of very high resolution images,” 
% IEEE Trans. Geosci. Remote Sens., vol. 48, no. 10, pp. 3747–3762,Oct. 2010.
%
%% The Multinomial logistic regression (MLR) implimentation is by:
%
% [4] J. Li, J. Bioucas-Dias and A. Plaza. 
% Hyperspectral Image Segmentation Using a New Bayesian Approach with Active Learning. 
% IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 10, pp. 3947-3960, October 2011
%
%% the SVM implitation is by libSVM
% [5] @article{CC01a,
% author = {Chang, Chih-Chung and Lin, Chih-Jen},
% title = {{LIBSVM}: A library for support vector machines},
% journal = {ACM Transactions on Intelligent Systems and Technology},
% volume = {2},
% issue = {3},
% year = {2011},
% pages = {27:1--27:27},
% note =	 {Software available at \url{http://www.csie.ntu.edu.tw/~cjlin/libsvm}}
%}
%
%%  ----------------If you use this demo, please cite these references------
%%  ----------------[1][2][3][4][5]----------------------------------------
%%
%  Any suggestions and comments are appreciated, and please send them to the
%  authors: jun@lx.it.pt. bioucas@lx.it.pt aplaza@unex.es