RANDOM PROJECTION AND SVD METHODS IN HYPERSPECTRAL IMAGING

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.

Grantor dc:publisher

Wake Forest University

Year dc:date.issued

2012

Author dc:creator

• Zhang, Jiani

• Classification

Language dc:language.iso

en

Handle dc:identifier.uri

http://hdl.handle.net/10339/37432

OAI identifier oai:identifier

oai:wakespace.lib.wfu.edu:10339/37432