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RANDOM PROJECTION AND SVD METHODS IN HYPERSPECTRAL IMAGING

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title
RANDOM PROJECTION AND SVD METHODS IN HYPERSPECTRAL IMAGING
author
Zhang, Jiani
abstract
Hyperspectral imaging provides researchers with abundant information with which to study the characteristics of objects in a scene. Processing the massive hyperspectral imagery datasets in a way that efficiently provides useful information becomes an important issue. In this thesis, we consider methods which reduce the dimension of hyperspectral data while retaining as much useful information as possible.
subject
Classification
Dimension Reduction
Hyperspectral Imaging
Random Projection
Reconstruction
SVD
contributor
Erway, Jennifer (committee chair)
Jiang, Miaohua (committee member)
Hu, Xiaofei (committee member)
Pauca, Paul V (committee member)
date
2012-09-05T08:35:17Z (accessioned)
2012-09-05T08:35:17Z (available)
2012 (issued)
degree
Mathematics (discipline)
identifier
http://hdl.handle.net/10339/37432 (uri)
language
en (iso)
publisher
Wake Forest University
type
Thesis

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