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Statistical Methods for Image Change Detection with Uncertainty

Lingg, Andrew James
http://rave.ohiolink.edu/etdc/view?acc_num=wright1357249370

Abstract Details

2012, Doctor of Philosophy (PhD), Wright State University, Engineering 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.
Brian Rigling, PhD (Advisor)
Fred Garber, PhD (Committee Member)
John Gallagher, PhD (Committee Member)
Micheal Temple, PhD (Committee Member)
William Pierson, PhD (Committee Member)
167 p.
Computer Science; Electrical Engineering; Engineering; Statistics
Change Detection; Estimation; Registration; Sequential Analysis; Cramer-Rao Lower Bound; Compressive Sensing

Recommended Citations

Citations

  • Lingg, A. J. (2012). Statistical Methods for Image Change Detection with Uncertainty [Doctoral dissertation, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1357249370

    APA Style (7th edition)

  • Lingg, Andrew. Statistical Methods for Image Change Detection with Uncertainty. 2012. Wright State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1357249370.

    MLA Style (8th edition)

  • Lingg, Andrew. "Statistical Methods for Image Change Detection with Uncertainty." Doctoral dissertation, Wright State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=wright1357249370

    Chicago Manual of Style (17th edition)

wright1357249370
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© 2012, all rights reserved.
This open access ETD is published by Wright State University and OhioLINK.