Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
King, Roger L.
Committee Member
Follett, Randy
Committee Member
Younan, Nick
Date of Degree
12-14-2001
Document Type
Graduate Thesis - Open Access
Major
Electrical Engineering
Degree Name
Master of Science
College
College of Engineering
Department
Department of Electrical and Computer Engineering
Abstract
In this paper, the problem of analyzing hyperspectral data is presented. The complexity of multi-dimensional data leads to the need for computer assisted data compression and labeling of important features. A brief overview of Self-Organizing Maps and their variants is given and then two possible methods of data analysis are examined. These methods are incorporated into a program derived from som_toolbox2. In this program, ASD data (data collected by an Analytical Spectral Device sensor) is read into a variable, relevant bands for discrimination between classes are extracted, and several different methods of analyzing the results are employed. A GUI was developed for easy implementation of these three stages.
URI
https://hdl.handle.net/11668/19137
Recommended Citation
Null, Thomas C., "Use of Self Organized Maps for Feature Extraction of Hyperspectral Data" (2001). Theses and Dissertations. 4876.
https://scholarsjunction.msstate.edu/td/4876