Parameter selection methods for axisymmetric flame tomography through Tikhonov regularization
Applied Optics, Vol. 47, Issue 3, pp. 407-416 (2008)
http://dx.doi.org/10.1364/AO.47.000407
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Abstract
Deconvolution of optically collected axisymmetric flame data is equivalent to solving an ill-posed problem subject to severe error amplification. Tikhonov regularization has recently been shown to be well suited for stabilizing this deconvolution, although the success of this method hinges on choosing a suitable regularization parameter. Incorporating a parameter selection scheme transforms this technique into a reliable automatic algorithm that outperforms unregularized deconvolution of a smoothed data set, which is currently the most popular way to analyze axisymmetric data. We review the discrepancy principle, L-curve curvature, and generalized cross-validation parameter selection schemes and conclude that the L-curve curvature algorithm is best suited to this problem.
© 2008 Optical Society of America
OCIS Codes
(120.1740) Instrumentation, measurement, and metrology : Combustion diagnostics
(120.7000) Instrumentation, measurement, and metrology : Transmission
(280.1740) Remote sensing and sensors : Combustion diagnostics
(280.2470) Remote sensing and sensors : Flames
ToC Category:
Remote Sensing and Sensors
History
Original Manuscript: August 22, 2007
Manuscript Accepted: November 24, 2007
Published: January 17, 2008
Citation
Emil O. Åkesson and Kyle J. Daun, "Parameter selection methods for axisymmetric flame tomography through Tikhonov regularization," Appl. Opt. 47, 407-416 (2008)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-47-3-407
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