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dc.contributor.advisorHunt, Bobby R.en_US
dc.contributor.authorMcNown, Scott Raymond
dc.creatorMcNown, Scott Raymonden_US
dc.date.accessioned2013-04-18T09:32:43Z
dc.date.available2013-04-18T09:32:43Z
dc.date.issued1996en_US
dc.identifier.urihttp://hdl.handle.net/10150/282148
dc.description.abstractA method is presented for finding coordinate transformations (warpings) of "objects" and "images," related by a shift-variant linear system model, such that the warped objects and images are approximately related by a shift-invariant linear system model. Such warps have utility for inverse solutions to linear problems, in which solution times for shift-invariant systems are less than the solution times for shift-variant systems. To this end, a measure of shift-variance for sampled linear systems is proposed. This measure allows for a variability in the sampling locations, as well as separable multipliers in the object and image domains (collectively called warping parameters), so that the measure may be used as the objective function for an optimization problem. Properties of the desired solution, which includes adequate field coverage and limits on the allowable warps, are also proposed. These features are combined in a formally stated optimization problem, which will search for a set of sample locations and multipliers to minimize the shift-variance of the warped system. The performance of a number of optimization algorithms which were directed at this task are presented. Also reported are results for finding the optimal warpings for some example one-dimensional systems. Inverse solutions, using both linear and non-linear techniques, are obtained using this warping method, and these results are compared to related inverse solutions which directly perform shift-variant inversion.
dc.language.isoen_USen_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.subjectEngineering, Electronics and Electrical.en_US
dc.subjectPhysics, Optics.en_US
dc.titleCoordinate transformations for approximate LSI modeling of LSV systems, and applications to restorationen_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.identifier.proquest9713372en_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineOptical Sciencesen_US
thesis.degree.namePh.D.en_US
dc.identifier.bibrecord.b34360815en_US
refterms.dateFOA2018-08-20T11:03:15Z
html.description.abstractA method is presented for finding coordinate transformations (warpings) of "objects" and "images," related by a shift-variant linear system model, such that the warped objects and images are approximately related by a shift-invariant linear system model. Such warps have utility for inverse solutions to linear problems, in which solution times for shift-invariant systems are less than the solution times for shift-variant systems. To this end, a measure of shift-variance for sampled linear systems is proposed. This measure allows for a variability in the sampling locations, as well as separable multipliers in the object and image domains (collectively called warping parameters), so that the measure may be used as the objective function for an optimization problem. Properties of the desired solution, which includes adequate field coverage and limits on the allowable warps, are also proposed. These features are combined in a formally stated optimization problem, which will search for a set of sample locations and multipliers to minimize the shift-variance of the warped system. The performance of a number of optimization algorithms which were directed at this task are presented. Also reported are results for finding the optimal warpings for some example one-dimensional systems. Inverse solutions, using both linear and non-linear techniques, are obtained using this warping method, and these results are compared to related inverse solutions which directly perform shift-variant inversion.


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