Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Parameter selection methods for axisymmetric flame tomography through Tikhonov regularization

Åkesson, Emil O LU and Daun, Kyle J (2008) In Applied Optics 47(3). p.407-416
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... (More)
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. (C) 2008 Optical Society of America. (Less)
Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Applied Optics
volume
47
issue
3
pages
407 - 416
publisher
Optical Society of America
external identifiers
  • wos:000253266800012
  • scopus:41549119442
ISSN
2155-3165
DOI
10.1364/AO.47.000407
language
English
LU publication?
yes
id
001349a6-9b75-4a1e-8139-bbfefe6853b3 (old id 1196996)
date added to LUP
2016-04-01 12:04:21
date last changed
2022-03-13 04:55:37
@article{001349a6-9b75-4a1e-8139-bbfefe6853b3,
  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. (C) 2008 Optical Society of America.}},
  author       = {{Åkesson, Emil O and Daun, Kyle J}},
  issn         = {{2155-3165}},
  language     = {{eng}},
  number       = {{3}},
  pages        = {{407--416}},
  publisher    = {{Optical Society of America}},
  series       = {{Applied Optics}},
  title        = {{Parameter selection methods for axisymmetric flame tomography through Tikhonov regularization}},
  url          = {{http://dx.doi.org/10.1364/AO.47.000407}},
  doi          = {{10.1364/AO.47.000407}},
  volume       = {{47}},
  year         = {{2008}},
}