Fast high-resolution image reconstruction using tikhonov regularization based total least squares

Geunseop Lee, Haoying Fu, Jesse Louis Barlow

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The solution of an ill-conditioned total least squares (TLS) problem from highresolution imaging by the regularization approach of Golub, Hansen, and O'Leary [SIAM J. Matrix Anal. Appl., 21 (2000), pp. 185-194] is considered. This work solves the regularized TLS problem as a system of nonlinear equations in the two regularization parameters. Since the Jacobian of the system can be computed inexpensively, the approach is based upon Newton's method. From experimental results, the algorithm produces a fast computation of the solution of the high-resolution image reconstruction problem.

Original languageEnglish (US)
JournalSIAM Journal on Scientific Computing
Volume35
Issue number1
DOIs
StatePublished - Apr 22 2013

All Science Journal Classification (ASJC) codes

  • Computational Mathematics
  • Applied Mathematics

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