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Y. Censor, D. Gordan and R. Gordan, “Component Aveging: An Efficient Iterative Parallel Algorithm for Large and Sparse Unstructured Problems,” Parallel Computing, Vol. 27, No. 6, 2001, pp. 777-808. doi:10.1016/S0167-8191(00)00100-9

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.