The Convergence of Two Algorithms for Compressed Sensing Based Tomography

DOI: 10.4236/act.2012.13007   PDF   HTML     2,743 Downloads   5,634 Views   Citations


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.

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Li, X. and Zhu, J. (2012) The Convergence of Two Algorithms for Compressed Sensing Based Tomography. Advances in Computed Tomography, 1, 30-36. doi: 10.4236/act.2012.13007.

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The authors declare no conflicts of interest.


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