Modeling Polarimetric Imaging using DIRSIG by Jason P. Meyers MSEE, Observables Reduction ...

181 Pages·2003·2.29 MB·English

Modeling Polarimetric Imaging using DIRSIG
by
Jason P. Meyers
M.S.E.E., Observables Reduction, Air Force Institute of Technology,
Wright-Patterson AFB, OH, 1994
B.S., Electrical Engineering, Michigan Technological University, 1993
A dissertation submitted in partial fulfillment of the
requirements for the degree of Doctor of Philosophy
in the Chester F. Carlson Center for Imaging Science
Rochester Institute of Technology
2002
Signature of the Author
Accepted by
Coordinator, Ph.D. Degree Program Date
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CHESTER F. CARLSON CENTER FOR IMAGING SCIENCE
ROCHESTER INSTITUTE OF TECHNOLOGY
ROCHESTER, NEW YORK
CERTIFICATE OF APPROVAL
Ph.D. DEGREE DISSERTATION
The Ph.D. Degree Dissertation of Jason P. Meyers
has been examined and approved by the
dissertation committee as satisfactory for the
dissertation required for the
Ph.D. degree in Imaging Science
Dr. John Schott, Dissertation Advisor
Dr. William Grande, Committee Chair
Dr. Joel Kastner
Dr. Michael Kotlarchyk
Date
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DISSERTATION RELEASE PERMISSION
ROCHESTER INSTITUTE OF TECHNOLOGY
CHESTER F. CARLSON CENTER FOR IMAGING SCIENCE
Title of Dissertation:
Modeling Polarimetric Imaging using DIRSIG
I, Jason P. Meyers, hereby grant permission to Wallace Memorial Library of R.I.T. to
reproduce my thesis in whole or in part. Any reproduction will not be for commercial
use or profit.
Signature
Date
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Modeling Polarimetric Imaging using DIRSIG
by
Jason P. Meyers
Submitted to the
Chester F. Carlson Center for Imaging Science
in partial fulfillment of the requiremnets
for the Doctor of Philosophy Degree
at the Rochester Institute of Technology
Abstract
The remote sensing community is beginning to recognize the potential benefit
of exploiting polarimetric signatures. The ability to accurately model polarimetric
phenomenology in a remote sensing system will assist efforts in system design, algo-
rithm development, phenomenology studies, and analyst training. This dissertation
lays the ground work for enhancing the current Digital Imaging and Remote Sens-
ing Laboratory’s Synthetic Image Generation (DIRSIG) model to include polarimetric
phenomenology. The current modeling capabilities are discussed along with the theo-
retical background required to expand upon the current state of the art. Methods for
modeling and estimating polarimetric signatures and phenomenology from start to
end in a typical remote sensing system are presented. A series of simple simulations
wereconductedtoassesstheperformanceofthenewpolarimetriccapabilities. Analy-
siswasperformedtocharacterizetheindividualmodelsandthecollectedperformance
of the models.
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DISCLAIMER
The views expressed in this article are those of the authors and do not reflect the
official policy or position of the United States Air Force, Department of Defense, or
the U.S. Government.
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