Journal of applied mathematics & informatics

The Korean Society for Computational and Applied Mathematics (한국전산응용수학회)
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PARALLEL PERFORMANCE OF THE Gℓ-PCG METHOD FOR IMAGE DEBLURRING PROBLEMS

  • YUN, JAE HEON (Department of Mathematics, College of Natural Sciences, Chungbuk National University)
  • Received : 2015.01.25
  • Accepted : 2018.04.05
  • Published : 2018.05.30
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Abstract

We first provide how to apply the global preconditioned conjugate gradient ($G{\ell}-PCG$) method with Kronecker product preconditioners to image deblurring problems with nearly separable point spread functions. We next provide a coarse-grained parallel image deblurring algorithm using the $G{\ell}-PCG$. Lastly, we provide numerical experiments for image deblurring problems to evaluate the effectiveness of the $G{\ell}-PCG$ with Kronecker product preconditioner by comparing its performance with those of the $G{\ell}-CG$, CGLS and preconditioned CGLS (PCGLS) methods.

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