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The Convergence of Two Algorithms for Compressed Sensing Based Tomography
Advanced in Computed Tomography
  • Xiezhang Li, Georgia Southern University
  • Jiehua Zhu, Georgia Southern University
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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.


Comment: Article is published under the Creative Commons license (CC BY or CC BY-NC). Article obtained from the Advances in Computed Tomography. (Creative Commons Attribution License link does not work)

Citation Information
Xiezhang Li and Jiehua Zhu. "The Convergence of Two Algorithms for Compressed Sensing Based Tomography" Advanced in Computed Tomography Vol. 1 Iss. 3 (2012) p. 32 - 38
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