Journal
APPLIED OPTICS
Volume 55, Issue 21, Pages 5772-5782Publisher
OPTICAL SOC AMER
DOI: 10.1364/AO.55.005772
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Funding
- Imperial Oil (University Research Award)
- Natural Sciences and Engineering Research Council of Canada (NSERC) [CRD 452099-13]
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Reconstruction accuracy in chemical species tomography depends strongly on the arrangement of optical paths transecting the imaging domain. Optimizing the path arrangement requires a scheme that can predict the quality of a proposed arrangement prior to measurement. This paper presents a new Bayesian method for scoring path arrangements based on the estimated a posteriori covariance matrix. This technique focuses on defining an objective function that incorporates the same a priori information about the flow needed to carry out limited data tomography. Constrained and unconstrained path optimization studies verify the predictive capabilities of the objective function, and that superior reconstruction quality is obtained with optimized path arrangements. (C) 2016 Optical Society of America
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