E. Candes and M. Wakin, “An Introduction to Compressive Sampling,” IEEE Signal Processing Magazine, Vol. 25, No. 2, 2008, pp. 21-30. doi:10.1109/MSP.2007.914731
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.