Multiscale anomaly detection and image registration algorithms for airborne landmine detection

Author

Jeffrey D. Barnes

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.

Recommended 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