Experimental and Numerical Investigations of Novel Architectures Applied to Compressive Imaging Systems

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dc.contributor.advisorKelly, Kevin F.en_US
dc.contributor.committeeMemberBaraniuk, Richard G.en_US
dc.contributor.committeeMemberYin, Wotaoen_US
dc.creatorTurner, Matthewen_US
dc.date.accessioned2012-09-06T03:57:55Zen_US
dc.date.accessioned2012-09-06T03:58:06Zen_US
dc.date.available2012-09-06T03:57:55Zen_US
dc.date.available2012-09-06T03:58:06Zen_US
dc.date.created2012-05en_US
dc.date.issued2012-09-05en_US
dc.date.submittedMay 2012en_US
dc.date.updated2012-09-06T03:58:07Zen_US
dc.description.abstractA recent breakthrough in information theory known as compressive sensing is one component of an ongoing revolution in data acquisition and processing that guides one to acquire less data yet still recover the same amount of information as traditional techniques, meaning less resources such as time, detector cost, or power are required. Starting from these basic principles, this thesis explores the application of these techniques to imaging. The first laboratory example we introduce is a simple infrared camera. Then we discuss the application of compressive sensing techniques to hyperspectral microscopy, specifically Raman microscopy, which should prove to be a powerful technique to bring the acquisition time for such microscopies down from hours to minutes. Next we explore a novel sensing architecture that uses partial circulant matrices as sensing matrices, which results in a simplified, more robust imaging system. The results of these imaging experiments lead to questions about the performance and fundamental nature of sparse signal recovery with partial circulant compressive sensing matrices. Thus, we present the results of a suite of numerical experiments that show some surprising and suggestive results that could stimulate further theoretical and applied research of partial circulant compressive sensing matrices. We conclude with a look ahead to adaptive sensing procedures that allow real-time, interactive optical signal processing to further reduce the resource demands of an imaging system.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationTurner, Matthew. "Experimental and Numerical Investigations of Novel Architectures Applied to Compressive Imaging Systems." (2012) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/64644">https://hdl.handle.net/1911/64644</a>.en_US
dc.identifier.slug123456789/ETD-2012-05-98en_US
dc.identifier.urihttps://hdl.handle.net/1911/64644en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectCompressive sensingen_US
dc.subjectSparse recoveryen_US
dc.subjectPhase transitionsen_US
dc.subjectMicroscopyen_US
dc.subjectRamanen_US
dc.subjectHyperspectral imagingen_US
dc.titleExperimental and Numerical Investigations of Novel Architectures Applied to Compressive Imaging Systemsen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentApplied Physicsen_US
thesis.degree.disciplineNatural Sciencesen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
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