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dc.contributor.authorMoran, Jodien
dc.date.accessioned2006-08-22 14:20:52 (GMT)
dc.date.available2006-08-22 14:20:52 (GMT)
dc.date.issued2001en
dc.date.submitted2001en
dc.identifier.urihttp://hdl.handle.net/10012/1107
dc.description.abstractThe reconstruction of a phase surface from the observed principal values is required for a number of applications, including synthetic aperture radar (SAR) and magnetic resonance imaging (MRI). However, the process of reconstruction, called “phase unwrapping”, is an ill-posed problem. One class of phase-unwrapping algorithms uses smoothness prior models to remedy this situation. We categorize this class of algorithms according to the type of prior model used. Motivated by this categorization, we propose that phase-unwrapping algorithms be tested by generating phase surfaces from the prior models, and then quantifying the deviation of each reconstructed surface from the corresponding original surface. Finally, we present results of the new testing method on a selection of phase-unwrapping algorithms, including a new algorithm.en
dc.formatapplication/pdfen
dc.format.extent7824141 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.rightsCopyright: 2001, Moran, Jodi. All rights reserved.en
dc.subjectComputer Scienceen
dc.subjectphase unwrappingen
dc.subjectbayesianen
dc.subjectprobabilityen
dc.subjecttestingen
dc.titleQuantitative Testing of Probabilistic Phase Unwrapping Methodsen
dc.typeMaster Thesisen
dc.pendingfalseen
uws-etd.degree.departmentSchool of Computer Scienceen
uws-etd.degreeMaster of Mathematicsen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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