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dc.contributor.advisor Brady, David J en_US
dc.contributor.author Shankar, Mohan en_US
dc.date.accessioned 2008-01-02T16:33:37Z
dc.date.available 2008-01-02T16:33:37Z
dc.date.issued 2007-12-14 en_US
dc.identifier.uri http://hdl.handle.net/10161/445
dc.description Dissertation en_US
dc.description.abstract Computational sensing utilizes non-conventional sampling mechanisms along with processing algorithms for accomplishing various sensing tasks. It provides additional flexibility in designing imaging or spectroscopic systems. This dissertation analyzes sampling and signal estimation techniques through three computational sensing systems to accomplish specific tasks. The first is thin long-wave infrared imaging systems through multichannel sampling. Significant reduction in optical system thickness is obtained over a conventional system by modifying conventional sampling mechanisms and applying reconstruction algorithms. In addition, an information theoretic analysis of sampling in conventional as well as multichannel imaging systems is also performed. The feasibility of performing multichannel sampling for imaging is demonstrated using an information theoretic metric. The second system is an application of the multichannel system for the design of compressive low-power video sensors. Two sampling schemes have been demonstrated that utilize spatial as well as temporal aliasing. The third system is a novel computational spectroscopic system for detecting chemicals that utilizes the surface plasmon resonances to encode information about the chemicals that are tested. en_US
dc.format.extent 13460154 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.subject Engineering, System Science en_US
dc.subject Engineering, Electronics and Electrical en_US
dc.subject computational sensing en_US
dc.subject computational imaging en_US
dc.subject compression en_US
dc.title Sampling and Signal Estimation in Computational Optical Sensors en_US
dc.type Dissertation en_US
dc.department Electrical and Computer Engineering en_US

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