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dc.contributor.advisor Kelly, Kevin F.
dc.creatorTakhar, Dharmpal
dc.date.accessioned 2014-08-08T22:00:29Z
dc.date.available 2014-08-08T22:00:29Z
dc.date.issued 2008
dc.identifier.citation Takhar, Dharmpal. "Compressed Sensing for Imaging Applications." (2008) Diss., Rice University. https://hdl.handle.net/1911/76508.
dc.identifier.urihttps://hdl.handle.net/1911/76508
dc.description.abstract Compressed sensing is a new sampling theory which allows reconstructing signals using sub-Nyquist measurements. This can significantly reduce the computation re­quired for both image and video whether during acquisition or encoding, especially at the sensor. Compressed sensing works on the assumption of sparsity of the sig­nal in some known domain, which is incoherent with the measurement domain. We exploit this technique to build a single pixel camera using an optical modulator and a single photosensor. Random projections of the signal (image) are applied to the optical modulator, which has a random matrix displayed on it corresponding to the measurement domain (random noise). This random projected signal is focused and summed at the photosensor and will be later used for reconstructing the signal. In this scheme, a tradeoff between the spatial extent of sampling array and a sequential sampling over time with a single detector is performed. In addition to the single sensor method, we will also demonstrate a new design which allows compressive im­
dc.format.extent 90 pp
dc.format.mimetype application/pdf
dc.language.iso eng
dc.subjectElectrical Engineering
Computer engineering
dc.title Compressed Sensing for Imaging Applications
dc.identifier.digital TakharD
dc.contributor.committeeMember Baraniuk, Richard G.
dc.contributor.committeeMember Yin, Wotao
dc.type.genre Thesis
dc.type.material Text
thesis.degree.department Electrical and Computer Engineering
thesis.degree.discipline Engineering
thesis.degree.grantor Rice University
thesis.degree.level Doctoral
thesis.degree.name Doctor of Philosophy


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