% % SATF: Shape-Adaptive Tensor Factorization Model DEMO. % Version: 1.0 % Date : Apr 2021 % % This demo shows the SATF method for hyperspectral image dimensionality reduction and classification. % % IP_main.m ....... A man function implementing the SATF model for Indian Pines data sets. % PU_main.m ....... A man function implementing the SATF model for University of Pavia data sets. % normcols.m .......A function for normalization. % % /data ................ The folder contains the IP and PU data sets. % /LASIP_Image_Restoration_DemoBox_v113 .. The folder contains the Anisotropic Nonparametric Image Restoration DemoBox. % /LORSAL ...............The folder contains the LORSAL algorithm. % /NFEA .................The folder contains tensor_toolbox (for functions of tensor, fmt, rankingFisher). % /SA-DCT_Demobox_v143...The folder contains Pointwise Shape-Adaptive DCT Demobox (for shape-adaptive method). % /tensorlab_2016-03-28..The folder contains Tensorlab Demos Release 3.0 (for functions of mlsvd). % % -------------------------------------- % Note: Required toolbox/functions are covered % -------------------------------------- % 1. LASIP_Image_Restoration_DemoBox_v113: https://www.cs.tut.fi/~lasip/2D/ % 2. LORSAL: http://www.lx.it.pt/~jun/demos.html % 3. NFEA: https://faculty.skoltech.ru/people/anhhuyphan % 4. SA-DCT_Demobox_v143: https://www.cs.tut.fi/~foi/SA-DCT/ % 5. tensorlab_2016-03-28: https://www.tensorlab.net/ % -- Please cite the original implementation when appropriate. % -------------------------------------- % Cite: % -------------------------------------- % % [1]Z. Xue, S. Yang, M. Zhang. Shape-Adaptive Tensor Factorization Model for Dimensionality Reduction of Hyperspectral Images[J]. IEEE Access, 2019, 7: 115160-115170. % % -------------------------------------- % Copyright & Disclaimer % -------------------------------------- % % The programs contained in this package are granted free of charge for % research and education purposes only. % % Copyright (c) 2021 by Zhaohui Xue % zhaohui.xue@hhu.edu.cn % -------------------------------------- % For full package: % -------------------------------------- % https://sites.google.com/site/zhaohuixuers/