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Proceedings Paper

On imaging multiple physical parameters in an inverse problems context
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Paper Abstract

The extraction of information regarding multiple, space-varying parameters from limited, tomographic-type data represents and ill-posed inverse problem which is increasingly of interest in a range of application areas. From a physical perspective one would expect some degree of co-variation among the desired quantities; however traditional regularization methods do not exploit such prior information. Thus, here we introduce a correlation-type of metric to enforce a degree of common “structure” among the desired parameters where we consider structure to be defined by the gradients of the individual profiles. The analytical and algorithmic details of our method are presented and its performance evaluated using photothermal nondestructive evaluation as a driving example.

Paper Details

Date Published: 21 May 2004
PDF: 12 pages
Proc. SPIE 5299, Computational Imaging II, (21 May 2004); doi: 10.1117/12.523381
Show Author Affiliations
Eric L. Miller, Northeastern Univ. (United States)
Andreas Mandelis, Univ. of Toronto (Canada)

Published in SPIE Proceedings Vol. 5299:
Computational Imaging II
Charles A. Bouman; Eric L. Miller, Editor(s)

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