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Li, C., Yin, W., Jiang, H. and Zhang, T. (2013) An E_cient Augmented Lagrangian Method with Applications to Total Variation inimization. Computational Optimization and Applications, 56, 07-530. ttps://doi.org/10.1007/s10589-013-9576-1

has been cited by the following article:

• TITLE: A Reweighted Total Variation Algorithm with the Alternating Direction Method for Computed Tomography

  AUTHORS: Xiezhang Li, Jiehua Zhu

  KEYWORDS: Computed Tomography, Nonmonotone Alternating Direction Algorithm, Reweighted Algorithm

  JOURNAL NAME: Advances in Computed Tomography, Vol.8 No.1, January 23, 2019

  ABSTRACT: A variety of alternating direction methods have been proposed for solving a class of optimization problems. The applications in computed tomography (CT) perform well in image reconstruction. The reweighted schemes were applied in l1-norm and total variation minimization for signal and image recovery to improve the convergence of algorithms. In this paper, we present a reweighted total variation algorithm using the alternating direction method (ADM) for image reconstruction in CT. The numerical experiments for ADM demonstrate that adding reweighted strategy reduces the computation time effectively and improves the quality of reconstructed images as well.