John Gallagher (Committee Member), Fred Garber (Committee Member), William Pierson (Committee Member), Brian Rigling (Advisor), Micheal Temple (Committee Member)
Doctor of Philosophy (PhD)
Sensors capable of collecting wide area motion imagery (WAMI), video synthetic aperture radar (SAR), and other high frame rate sensor modalities provide massive amounts of high-resolution data. Such data allows for the use of multiple images in exploitation tasks which may have traditionally used single images or single pairs of images. One such task is change detection. This dissertation presents new statistical methods for change detection that provide for the exploitation of multiple images per pass. Uncertainty in image registration can degrade change detection performance. Registration accuracy is analyzed, and the impact of registration uncertainty is propagated to the registered imagery. A statistical understanding of this uncertainty is incorporated into the sequential change detection algorithm to mitigate performance degradation due to registration errors. Theoretical results are verified through simulation experiments and with measured data sets.
Department or Program
Ph.D. in Engineering
Year Degree Awarded
Copyright 2012, all rights reserved. This open access ETD is published by Wright State University and OhioLINK.