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D. Butnariu, R. Davidi, G. T. Herman and I. G. Kazantsev, “Stable Convergence Behavior under Summable Perturbation of a Class Projection Methods for Convex Feasibility and Optimization Problems,” IEEE Journal of Selected Topics in Signal Processing, Vo. 1, No. 4, 2007, pp. 540547.

has been cited by the following article:

• TITLE: The Convergence of Two Algorithms for Compressed Sensing Based Tomography

  AUTHORS: Xiezhang Li, Jiehua Zhu

  KEYWORDS: Compressed Sensing; Image Reconstruction; Total Variation Minimization; Block Iterative Methods

  JOURNAL NAME: Advances in Computed Tomography, Vol.1 No.3, December 28, 2012

  ABSTRACT: The constrained total variation minimization has been developed successfully for image reconstruction in computed tomography. In this paper, the block component averaging and diagonally-relaxed orthogonal projection methods are proposed to incorporate with the total variation minimization in the compressed sensing framework. The convergence of the algorithms under a certain condition is derived. Examples are given to illustrate their convergence behavior and noise performance.