SAR Phase Unwrapping Using Path-Based Least-Squares Phase Estimation and Region-Growing with Polynomial-Based Phase Prediction

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dc.contributor.advisorWang, Jian-Guo
dc.contributor.authorBrunson, Benjamin James Loker
dc.date.accessioned2019-11-22T18:50:46Z
dc.date.available2019-11-22T18:50:46Z
dc.date.copyright2019-05
dc.date.issued2019-11-22
dc.date.updated2019-11-22T18:50:46Z
dc.degree.disciplineEarth & Space Science
dc.degree.levelMaster's
dc.degree.nameMSc - Master of Science
dc.description.abstractDifferential SAR interferometry (DInSAR) has proven to be a processing approach that is well-suited to precisely identifying large-scale land deformation patterns. This is useful for many environmental monitoring applications, but the speckle noise and temporal decorrelation present in SAR images presents particular challenges in processing SAR images. This research focuses on the phase unwrapping problem, proposing two new approaches: Polynomial-Based Region-Growing Phase Unwrapping (PBRGPU), which expands upon the traditional region-growing approach to phase unwrapping; and Path-Based Least-Squares Phase Unwrapping (PBLSPU), which extends the least-squares phase unwrapping models in a path-based framework. Both algorithms were tested using simulated data and interferograms generated from RADARSAT-2 data. Both approaches significantly reduced the root mean square error compared to the algorithms they build from, and achieved a similar level of performance to the commonly-used SNAPHU algorithm without the need for masking low coherence areas.
dc.identifier.urihttp://hdl.handle.net/10315/36748
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectPhysical geography
dc.subject.keywordsSAR
dc.subject.keywordsSynthetic Aperture RADAR
dc.subject.keywordsPhase Unwrapping
dc.subject.keywordsRegion Growing
dc.subject.keywordsLeast Squares
dc.titleSAR Phase Unwrapping Using Path-Based Least-Squares Phase Estimation and Region-Growing with Polynomial-Based Phase Prediction
dc.typeElectronic Thesis or Dissertation

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