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