Persistent Link:
http://hdl.handle.net/10150/186904
Title:
Non-scanning imaging spectrometry.
Author:
Descour, Michael Robert.
Issue Date:
1994
Publisher:
The University of Arizona.
Rights:
Copyright © 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.
Abstract:
The objective of imaging spectrometry is to collect three-dimensional data about object space. Two of the three dimensions are spatial. The third dimension is spectral. Current techniques rely on some form of scanning, causing instruments to include moving components and/or to be capable of imaging only static or slowly changing scenes. An interpretation of the problem in terms of computed tomography leads to a system design which can fulfill the objective of imaging spectrometry without scanning. The imaging spectrometer assumes the frame-rate and integration-time properties of its imaging array. The raw data collected by such an instrument must be processed to yield temporally coincident spectral images of the scene. The computed tomography imaging spectrometer is therefore an example of indirect imaging. The three-dimensional frequency-space viewpoint and the associated central slice theorem form the theoretical basis for an understanding of this technique and its limitations. As described here, computed tomography imaging spectrometry belongs to the class of limited-view-angle problems. The spectrometer is treated as a discrete-to-discrete mapping and described accordingly by the linear imaging equation g = Hf + n. The M-element vector g represents the data collected by the spectrometer. The purpose of the instrument and the subsequent processing is the acquisition of the object cube f. In the discrete-to-discrete model, f is approximated as a vector of N independent elements. The vector n represents measurement-computing noise. The M-by-N matrix H embodies the imaging properties of the instrument. We have developed and implemented an experimental method of characterizing H. Such an approach yields a description of the imaging spectrometer which is more accurate than techniques that model the instrument and compute H. Inversion of the imaging equation to find an estimate of f has been best performed by the Expectation-Maximization algorithm. This approach is based on a Poisson likelihood law and therefore the assumption of quantum noise dominating the measurements g.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Mathematics.; Optics.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Optical Sciences; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Dereniak, Eustace

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleNon-scanning imaging spectrometry.en_US
dc.creatorDescour, Michael Robert.en_US
dc.contributor.authorDescour, Michael Robert.en_US
dc.date.issued1994en_US
dc.publisherThe University of Arizona.en_US
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.en_US
dc.description.abstractThe objective of imaging spectrometry is to collect three-dimensional data about object space. Two of the three dimensions are spatial. The third dimension is spectral. Current techniques rely on some form of scanning, causing instruments to include moving components and/or to be capable of imaging only static or slowly changing scenes. An interpretation of the problem in terms of computed tomography leads to a system design which can fulfill the objective of imaging spectrometry without scanning. The imaging spectrometer assumes the frame-rate and integration-time properties of its imaging array. The raw data collected by such an instrument must be processed to yield temporally coincident spectral images of the scene. The computed tomography imaging spectrometer is therefore an example of indirect imaging. The three-dimensional frequency-space viewpoint and the associated central slice theorem form the theoretical basis for an understanding of this technique and its limitations. As described here, computed tomography imaging spectrometry belongs to the class of limited-view-angle problems. The spectrometer is treated as a discrete-to-discrete mapping and described accordingly by the linear imaging equation g = Hf + n. The M-element vector g represents the data collected by the spectrometer. The purpose of the instrument and the subsequent processing is the acquisition of the object cube f. In the discrete-to-discrete model, f is approximated as a vector of N independent elements. The vector n represents measurement-computing noise. The M-by-N matrix H embodies the imaging properties of the instrument. We have developed and implemented an experimental method of characterizing H. Such an approach yields a description of the imaging spectrometer which is more accurate than techniques that model the instrument and compute H. Inversion of the imaging equation to find an estimate of f has been best performed by the Expectation-Maximization algorithm. This approach is based on a Poisson likelihood law and therefore the assumption of quantum noise dominating the measurements g.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectMathematics.en_US
dc.subjectOptics.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineOptical Sciencesen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairDereniak, Eustaceen_US
dc.contributor.committeememberBarrett, Harrisonen_US
dc.contributor.committeememberMooney, Jonathanen_US
dc.identifier.proquest9517521en_US
dc.identifier.oclc704938162en_US
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