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dc.contributor.advisorRedford, Gary
dc.contributor.authorDuggan, Timothy Benjamin
dc.creatorDuggan, Timothy Benjamin
dc.date.accessioned2019-06-13T03:49:56Z
dc.date.available2019-06-13T03:49:56Z
dc.date.issued2019
dc.identifier.urihttp://hdl.handle.net/10150/632670
dc.descriptionGroup project with Shawn Nakajima, Dominic Sanchez, and Cristian Vergara
dc.description.abstractHigh-resolution images are greatly sought after in many commercial and military opti- cal systems because they are able to store large amounts of information { but detector costs increase significantly with the pixel count. The goal of this project was to create an imaging system where it is possible to get a four times improvement in both the X and Y directions for image resolution from the detector. This project implements the super resolution technique known as compressed sensing to improve the resolution of an imaging system that is limited not by its optics, but by the number of pixels in the detector. Compressed sensing encodes compressed information into the low-resolution measurements, allowing for the reconstruction of high-resolution images from many of these low-resolution samples. The super resolution imager designed uses com- pressed sensing to decrease the number of samples required to perfectly reconstruct an image. With a few low-resolution images modulated by a subpixel code, a linear system is gen- erated and solved for which predicts a high-resolution image using a small number of mea- surement data. This prototype imager uses a binary mask-actuator encoding design coupled with an exact L1 minimization reconstruction. Additionally, the project explored the idea of replacing this subpixel encoding with a digital micromirror device, and the reconstruction with a convolutional neural network approach.
dc.language.isoen
dc.publisherThe University of Arizona.
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
dc.titleSuper Resolution Imager
dc.typetext
dc.typeElectronic Thesis
thesis.degree.grantorUniversity of Arizona
thesis.degree.disciplineHonors College
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.nameB.S.
refterms.dateFOA2019-06-13T03:49:56Z


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