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LARGE FORMAT CTIS IN REAL TIME: PARALLELIZED ALGORITHMS AND PRECONDITIONING INITIALIZERS

Real time processing of hyperspectral imaging data of the kind acquired by Computed Tomography Imaging Spectroscopy (CTIS) presents some unique challenges in computational power and data storage. The general approach pursued in this work is a direct application of numerical solution methods implemented in the computing cluster environment of Vanderbilt Universitys Advanced Computing Cluster Resource (ACCRE). The examination of four reconstruction algorithms, Simultaneous Algebraic Reconstruction, Cimmino Component Averaging, Expectation Maximization-Maximum Likelihood, and Multiplicative Algebraic Reconstruction Technique were explored. The Multiplicative Algebraic Reconstruction Technique proved robust in quality and speed as implemented with the matrix preconditioning method as employed.

Identiferoai:union.ndltd.org:VANDERBILT/oai:VANDERBILTETD:etd-03152008-170236
Date01 April 2008
CreatorsSethaphong, Latsavongsakda
ContributorsEric J. Hustedt, Albert H. Beth, David W. Piston
PublisherVANDERBILT
Source SetsVanderbilt University Theses
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.library.vanderbilt.edu/available/etd-03152008-170236/
Rightsunrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Vanderbilt University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.

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