Spatial-Spectral Dimensionality Reduction with Partial Knowledge of Class Labels
Performs spatial-spectral dimensionality reduction of hyperspectral imagery with partial knowledge of class labels, followed by SVM-based classification, as described in the paper:
N. D. Cahill, S. E. Chew, and P. S. Wenger, "Spatial-Spectral Dimensionality Reduction of Hyperspectral Imagery with Partial Knowledge of Class Labels," Proc. SPIE Defense & Security: Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, April 2015.
This code requires the Spectral-Spatial Schroedinger Eigenmaps library, available at the MATLAB File Exchange, File No. 45908.
Cite As
Nathan Cahill (2024). Spatial-Spectral Dimensionality Reduction with Partial Knowledge of Class Labels (https://www.mathworks.com/matlabcentral/fileexchange/50189-spatial-spectral-dimensionality-reduction-with-partial-knowledge-of-class-labels), MATLAB Central File Exchange. Retrieved .
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- Image Processing and Computer Vision > Computer Vision Toolbox > Point Cloud Processing > Display Point Clouds >
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Acknowledgements
Inspired by: Spatial-Spectral Schroedinger Eigenmaps
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