Spatial-Spectral Schroedinger Eigenmaps

Versione 1.1.0.0 (8,95 KB) da Nathan Cahill
Graph-based dimensionality reduction technique for image data
5.0
(2)
1,4K download
Aggiornato 19 ago 2014

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Performs dimensionality reduction and classification of hyperspectral imagery using the Spatial-Spectral Schroedinger Eigenmaps (SSSE) algorithm, as described in the papers:
1) N. D. Cahill, W. Czaja, and D. W. Messinger, "Schroedinger Eigenmaps with Nondiagonal Potentials for Spatial-Spectral Clustering of Hyperspectral Imagery," Proc. SPIE Defense & Security: Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XX, May 2014.

2) N. D. Cahill, W. Czaja, and D. W. Messinger, "Spatial-Spectral Schroedinger Eigenmaps for Dimensionality Reduction and Classification of Hyperspectral Imagery," submitted.

This example script also performs classification using Support Vector Machines, as described in paper 2.

Cita come

Nathan Cahill (2025). Spatial-Spectral Schroedinger Eigenmaps (https://it.mathworks.com/matlabcentral/fileexchange/45908-spatial-spectral-schroedinger-eigenmaps), MATLAB Central File Exchange. Recuperato .

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SSSE/

Versione Pubblicato Note della release
1.1.0.0

Updated the original version of SSSE as described in the SPIE conference paper to the newer version as described in the submitted journal article. Also included code for subsequent classification with SVMs.
1.0.0.0