Journal of the Chungcheong Mathematical Society (충청수학회지)

The Chungcheong Mathematical Society (충청수학회)
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PRECONDITIONED GL-CGLS METHOD USING REGULARIZATION PARAMETERS CHOSEN FROM THE GLOBAL GENERALIZED CROSS VALIDATION

  • Oh, SeYoung (Department of Mathematics Chungnam National University) ;
  • Kwon, SunJoo (Innovation Center of Engineering Education Chungnam National University)
  • Received : 2014.09.17
  • Accepted : 2014.10.06
  • Published : 2014.11.15
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Abstract

In this paper, we present an efficient way to determine a suitable value of the regularization parameter using the global generalized cross validation and analyze the experimental results from preconditioned global conjugate gradient linear least squares(Gl-CGLS) method in solving image deblurring problems. Preconditioned Gl-CGLS solves general linear systems with multiple right-hand sides. It has been shown in [10] that this method can be effectively applied to image deblurring problems. The regularization parameter, chosen from the global generalized cross validation, with preconditioned Gl-CGLS method can give better reconstructions of the true image than other parameters considered in this study.

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References

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  1. A WEIGHTED GLOBAL GENERALIZED CROSS VALIDATION FOR GL-CGLS REGULARIZATION vol.29, pp.1, 2016, https://doi.org/10.14403/jcms.2016.29.1.59
  2. CHOOSING REGULARIZATION PARAMETER BY GLOBAL L-CURVE CRITERION vol.30, pp.1, 2014, https://doi.org/10.14403/jcms.2017.30.1.117
  3. MULTI-PARAMETER TIKHONOV REGULARIZATION PROBLEM WITH MULTIPLE RIGHT HAND SIDES vol.33, pp.4, 2014, https://doi.org/10.14403/jcms.2020.33.4.505