Masters Theses
Multiscale anomaly detection and image registration algorithms for airborne landmine detection
Abstract
"Multiscale techniques such as the wavelet transform have become a powerful tool for image compression, denoising, and analysis. This thesis outlines the use of such techniques for developing a multiscale processing stream for the purpose of airborne landmine detection. In this work, the Reed-Xiaoli (RX) multi-spectral anomaly detection algorithm is extended to perform detection within the shift-invariant wavelet representation of a given single-band image"--Abstract, page iii.
Advisor(s)
Agarwal, Sanjeev, 1971-
Committee Member(s)
Grow, David E.
Moss, Randy Hays, 1953-
Department(s)
Electrical and Computer Engineering
Degree Name
M.S. in Electrical Engineering
Publisher
University of Missouri--Rolla
Publication Date
Spring 2006
Pagination
ix, 94 pages
Rights
© 2006 Jeffrey D. Barnes, All rights reserved.
Document Type
Thesis - Citation
File Type
text
Language
English
Subject Headings
Image processing -- Mathematical models
Land mines -- Detection
Mines (Military explosives) -- Detection
Remote sensing
Thesis Number
T 9105
Print OCLC #
124070427
Link to Catalog Record
Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.
http://merlin.lib.umsystem.edu/record=b5850469~S5Recommended Citation
Barnes, Jeffrey D., "Multiscale anomaly detection and image registration algorithms for airborne landmine detection" (2006). Masters Theses. 5895.
https://scholarsmine.mst.edu/masters_theses/5895
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