Post on 23-Feb-2016
description
Dimensionality Reduction on Hyperspectral Data for
Solids Analysis
Annalisse BoothUtah State University
Electrical and Computer Engineering DepartmentResearch Experience for Undergraduates 2009
Hyperspectral Imaging: An Overview
Source: http://www.yellowstoneresearch.org
• 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
January 11, 2008 17:41:25, wavelength 46
Solids Hyperspectral Data
• 3 months data
• Camera on tripod, but shaken
• Cleaned up by Mckay
• Turned into video, RGB approximations
• Wrote other applicable codes
Gathering Tools for Analysis
An example of a Locally Linear Embedding (LLE)
• Multidimensional Scaling (MDS)• Principle Component Analysis (PCA)• Locally Linear Embedding (LLE)• Isomap (weighted geodesic distances)• Maximum Variance Unfolding (MVU)
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