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Dimensionality Reduction on Hyperspectral Data for Solids Analysis. Annalisse Booth Utah State University Electrical and Computer Engineering Department Research Experience for Undergraduates 2009. Hyperspectral Imaging: An Overview. Records information across electromagnetic spectrum
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Dimensionality Reductionon Hyperspectral Data for Solids Analysis Annalisse Booth Utah State University Electrical and Computer Engineering Department Research Experience for Undergraduates 2009
Hyperspectral Imaging: An Overview • Records information across electromagnetic spectrum • Spectral band correlates to certain range of wavelength • Bands combined to form cube • Hundreds to thousands of bands per cube • 258 bands in current data Source: http://www.yellowstoneresearch.org
Solids Hyperspectral Data • 3 months data • Camera on tripod, but shaken • Cleaned up by Mckay • Turned into video, RGB approximations • Wrote other applicable codes January 11, 2008 17:41:25, wavelength 46
Gathering Tools for Analysis • Multidimensional Scaling (MDS) • Principle Component Analysis (PCA) • Locally Linear Embedding (LLE) • Isomap (weighted geodesic distances) • Maximum Variance Unfolding (MVU) An example of a Locally Linear Embedding (LLE)
Comparing Techniques Source: Boundary Constrained Manifold Unfolding. Bo, Hongbin, Wenan. 2008.
Comparing Techniques Source: Boundary Constrained Manifold Unfolding. Bo, Hongbin, Wenan. 2008.
Comparing Techniques Source: Boundary Constrained Manifold Unfolding. Bo, Hongbin, Wenan. 2008.
Work Still Uncompleted • Write program to choose pixels from each substance through time • Compare pixels of each substance to self and other substances • Analysis in Isomap for preliminary results • Write code for Riemmanian Manifold Learning (RML) • Execute code on data • Write code for Boundary Constrained Manifold Unfolding • Execute new code, compare