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Download the latest Endmember Induction Algorithms (EIAs) toolbox and the documentation here: | Download the latest Endmember Induction Algorithms (EIAs) toolbox and the documentation here: | ||
* MATLAB: [[Media:EIAs_matlab.zip | toolbox (xxx MB)]] [[Media:EIAs_matlab_doc.zip | manual (xxx MB)]] | * MATLAB: [[Media:EIAs_matlab.zip | toolbox (xxx MB)]] | [[Media:EIAs_matlab_doc.zip | manual (xxx MB)]] | ||
* SCILAB: [[Media:EIAs_scilab.zip | toolbox (xxx MB)]] [[Media:EIAs_scilab_doc.zip | manual (xxx MB)]] | * SCILAB: [[Media:EIAs_scilab.zip | toolbox (xxx MB)]] | [[Media:EIAs_scilab_doc.zip | manual (xxx MB)]] | ||
This software is distributed under the terms of the [http://www.gnu.org/licenses/gpl.html GNU General Public License] as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. | This software is distributed under the terms of the [http://www.gnu.org/licenses/gpl.html GNU General Public License] as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. | ||
Revisión del 13:19 26 abr 2011
Endmember Induction Algorithms toolbox
Download the latest Endmember Induction Algorithms (EIAs) toolbox and the documentation here:
- MATLAB: toolbox (xxx MB) | manual (xxx MB)
- SCILAB: toolbox (xxx MB) | manual (xxx MB)
This software is distributed under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
The here available Endmember Induction Algorithms (EIAs) toolbox have been developed with MATLAB 7.4 (licensed copy is needed to use it) and SCILAB 5.2 (open source and freely distributed).
If you are using the Endmember Induction Algorithms (EIAs) toolbox for your scientific research, please reference it as follows:
Endmember Induction Algorithms (EIAs) toolbox. Grupo de Inteligencia Computacional, Universidad del País Vasco / Euskal Herriko Unibertsitatea (UPV/EHU), Spain. http://www.ehu.es/computationalintelligence/index.php/Endmember_Induction_Algorithms
Copyright 2010 Grupo Inteligencia Computacional, Universidad del País Vasco / Euskal Herriko Unibertsitatea (UPV/EHU).
Acknowledgements to Prof. Antonio Plaza from the Department of Technology of Computers and Communications, University of Extremadura (Spain), and coordinator of the Hyper-I-Net project; and to Prof. Chein-I Chang from the Remote Sensing Signal and Image Processing Laboratory, University of Maryland (USA).
Endmember Induction Algorithms collection
Here you can find separately the EIAs included in the toolbox and their respective bibliographical references:
- Endmember Induction Heuristic Algorithm (EIHA)
- MATLAB: download (4.7 KB)
- SCILAB: download (4.5 KB)
M. Grana, I. Villaverde, J. O. Maldonado, and C. Hernandez Two lattice computing approaches for the unsupervised segmentation of hyperspectral images Neurocomput., vol. 72, nº. 10-12, págs. 2111-2120, 2009.
- Incremental Strong Lattice Independent Algorithm (ILSIA)
- MATLAB: download (7.4 KB)
- SCILAB: download (7.1 KB)
M. Grana, D. Chyzhyk, M. García-Sebastián, and C. Hernández Lattice independent component analysis for functional magnetic resonance imaging Information Sciences, vol. 181, pág. 1910–1928, May. 2011.
- Prof. Ritter's WM Algorithm (WM)
- MATLAB: download (2.4 KB)
- SCILAB: download (2.3 KB)
G. X. Ritter and G. Urcid A lattice matrix method for hyperspectral image unmixing Information Sciences, vol. In Press, Corrected Proof, Oct. 2010.
- N-FINDR
- MATLAB: download (3.9 KB)
- SCILAB: download (3.8 KB)
Chang, C.-I. and Plaza, A. A fast iterative algorithm for implementation of pixel purity index Geoscience and Remote Sensing Letters, IEEE, vol. 3, nº. 1, págs. 63-67, 2006.
- FIPPI
- MATLAB: download (3.7 KB)
- SCILAB: download (3.6 KB)
Winter, M. E. N-FINDR: an algorithm for fast autonomous spectral endmember determination in hyperspectral data presented at the Imaging Spectrometry V, Denver, CO, USA, 1999, vol. 3753, págs. 266-275.
- Automatic Target Generation Process (ATGP)
- MATLAB: download (3.8 KB)
- SCILAB: download (3.8 KB)
A. Plaza and C.-I. Chang Impact of Initialization on Design of Endmember Extraction Algorithms Geoscience and Remote Sensing, IEEE Transactions on, vol. 44, nº. 11, págs. 3397-3407, 2006.
- Convex Cone Analysis (CCA)
- MATLAB: download (3.5 KB)
- SCILAB: download (xxx KB)
Ifarraguerri, A. and C.-I. Chang Multispectral and hyperspectral image analysis with convex cones Geoscience and Remote Sensing, IEEE Transactions on, vol. 37, nº. 2, págs. 756-770, 1999.
- Vertex Component Analysis (VCA)
- MATLAB: download (xxx MB)
- SCILAB: download (xxx MB)
Nascimento, J. M. P. and Dias, J. M. B. Vertex component analysis: a fast algorithm to unmix hyperspectral data Geoscience and Remote Sensing, IEEE Transactions on, vol. 43, nº. 4, págs. 898-910, 2005.
Additional functions
Some of the algorithms require additional methods:
- Lattice Associative Memories (LAMs)
- MATLAB: download (3.1 KB)
- SCILAB: download (3.0 KB)
- Chebyshev distance
- MATLAB: download (2.0 KB)
- SCILAB: download (2.0 KB)
Some of the algorithms require as input the number of endmembers to search. If unknown, HFC virtual dimensionality algorithm can be used:
- HFC method
- MATLAB: download (3.2 KB)
- SCILAB: download (xxx KB)
Chang, C.-I. and Du, Q. Estimation of number of spectrally distinct signal sources in hyperspectral imagery Geoscience and Remote Sensing, IEEE Transactions on, vol. 42, nº. 3, págs. 608-619, 2004.
