This dissertation describes three computational sensors. The first sensor is a scanning multi-spectral aperture-coded microscope containing a coded aperture spectrometer that is vertically scanned through a microscope intermediate image plane. The spectrometer aperture-code spatially encodes the object spectral data and nonnegative
least squares inversion combined with a series of reconfigured two-dimensional (2D spatial-spectral) scanned measurements enables three-dimensional (3D) (x, y, λ) object estimation. The second sensor is a coded aperture snapshot spectral imager that employs a compressive optical architecture to record a spectrally filtered projection
of a 3D object data cube onto a 2D detector array. Two nonlinear and adapted TV-minimization schemes are presented for 3D (x,y,λ) object estimation from a 2D compressed snapshot. Both sensors are interfaced to laboratory-grade microscopes and
applied to fluorescence microscopy. The third sensor is a millimeter-wave holographic imaging system that is used to study the impact of 2D compressive measurement on 3D (x,y,z) data estimation. Holography is a natural compressive encoder since a 3D
parabolic slice of the object band volume is recorded onto a 2D planar surface. An adapted nonlinear TV-minimization algorithm is used for 3D tomographic estimation from a 2D and a sparse 2D hologram composite. This strategy aims to reduce scan time costs associated with millimeter-wave image acquisition using a single pixel receiver.
","abstract_html":"<p>This dissertation describes three computational sensors. The first sensor is a scanning multi-spectral aperture-coded microscope containing a coded aperture spectrometer that is vertically scanned through a microscope intermediate image plane. The spectrometer aperture-code spatially encodes the object spectral data and nonnegative</p> <p>least squares inversion combined with a series of reconfigured two-dimensional (2D spatial-spectral) scanned measurements enables three-dimensional (3D) (x, y, λ) object estimation. The second sensor is a coded aperture snapshot spectral imager that employs a compressive optical architecture to record a spectrally filtered projection</p> <p>of a 3D object data cube onto a 2D detector array. Two nonlinear and adapted TV-minimization schemes are presented for 3D (x,y,λ) object estimation from a 2D compressed snapshot. Both sensors are interfaced to laboratory-grade microscopes and</p> <p>applied to fluorescence microscopy. The third sensor is a millimeter-wave holographic imaging system that is used to study the impact of 2D compressive measurement on 3D (x,y,z) data estimation. Holography is a natural compressive encoder since a 3D</p> <p>parabolic slice of the object band volume is recorded onto a 2D planar surface. An adapted nonlinear TV-minimization algorithm is used for 3D tomographic estimation from a 2D and a sparse 2D hologram composite. This strategy aims to reduce scan time costs associated with millimeter-wave image acquisition using a single pixel receiver.</p>","abstract_has_math":false,"creators":["Fernandez, Christy Ann"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Brady, David J"],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010","date_published":"2010","updated_at":"2026-07-24T02:07:19Z","subjects":["Engineering, Electronics and Electrical","Engineering, System Science","Physics, Optics","compressive sensing","holography","Microscopy","millimeter-wave","optical system design","sensor design"],"languages":["en_US"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10161/2406","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Brady, David J"]},{"key":"dc:creator","label":"Author","values":["Fernandez, Christy Ann"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2010-05-10T19:57:42Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2010-05-10T19:57:42Z"]},{"key":"dc:date.issued","label":"Date","values":["2010"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engineering, Electronics and Electrical","Engineering, System Science","Physics, Optics","compressive sensing","holography","Microscopy","millimeter-wave","optical system design","sensor design"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_US"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10161/2406"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This dissertation describes three computational sensors. The first sensor is a scanning multi-spectral aperture-coded microscope containing a coded aperture spectrometer that is vertically scanned through a microscope intermediate image plane. The spectrometer aperture-code spatially encodes the object spectral data and nonnegative
least squares inversion combined with a series of reconfigured two-dimensional (2D spatial-spectral) scanned measurements enables three-dimensional (3D) (x, y, λ) object estimation. The second sensor is a coded aperture snapshot spectral imager that employs a compressive optical architecture to record a spectrally filtered projection
of a 3D object data cube onto a 2D detector array. Two nonlinear and adapted TV-minimization schemes are presented for 3D (x,y,λ) object estimation from a 2D compressed snapshot. Both sensors are interfaced to laboratory-grade microscopes and
applied to fluorescence microscopy. The third sensor is a millimeter-wave holographic imaging system that is used to study the impact of 2D compressive measurement on 3D (x,y,z) data estimation. Holography is a natural compressive encoder since a 3D
parabolic slice of the object band volume is recorded onto a 2D planar surface. An adapted nonlinear TV-minimization algorithm is used for 3D tomographic estimation from a 2D and a sparse 2D hologram composite. This strategy aims to reduce scan time costs associated with millimeter-wave image acquisition using a single pixel receiver.
"]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Computational spectral microscopy and compressive millimeter-wave holography"]}]}],"canonical_facts":{"dc:contributor.advisor":["Brady, David J"],"dc:creator":["Fernandez, Christy Ann"],"dc:date.accessioned":["2010-05-10T19:57:42Z"],"dc:date.available":["2010-05-10T19:57:42Z"],"dc:date.issued":["2010"],"dc:description.abstract":["This dissertation describes three computational sensors. The first sensor is a scanning multi-spectral aperture-coded microscope containing a coded aperture spectrometer that is vertically scanned through a microscope intermediate image plane. The spectrometer aperture-code spatially encodes the object spectral data and nonnegative
least squares inversion combined with a series of reconfigured two-dimensional (2D spatial-spectral) scanned measurements enables three-dimensional (3D) (x, y, λ) object estimation. The second sensor is a coded aperture snapshot spectral imager that employs a compressive optical architecture to record a spectrally filtered projection
of a 3D object data cube onto a 2D detector array. Two nonlinear and adapted TV-minimization schemes are presented for 3D (x,y,λ) object estimation from a 2D compressed snapshot. Both sensors are interfaced to laboratory-grade microscopes and
applied to fluorescence microscopy. The third sensor is a millimeter-wave holographic imaging system that is used to study the impact of 2D compressive measurement on 3D (x,y,z) data estimation. Holography is a natural compressive encoder since a 3D
parabolic slice of the object band volume is recorded onto a 2D planar surface. An adapted nonlinear TV-minimization algorithm is used for 3D tomographic estimation from a 2D and a sparse 2D hologram composite. This strategy aims to reduce scan time costs associated with millimeter-wave image acquisition using a single pixel receiver.
"],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["https://hdl.handle.net/10161/2406"],"dc:language.iso":["en_US"],"dc:subject":["Engineering, Electronics and Electrical","Engineering, System Science","Physics, Optics","compressive sensing","holography","Microscopy","millimeter-wave","optical system design","sensor design"],"dc:title":["Computational spectral microscopy and compressive millimeter-wave holography"],"dc:type":["Dissertation"]},"updated_at":"2026-07-24T02:07:19Z"}