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Presentation
A Generalized l1 Greedy Algorithm for Image Reconstruction in Computed Tomography
2013 Joint Mathematics Meetings (2013)
  • Jiehua Zhu
Abstract
The sparse vector solutions for an underdetermined system of linear equations Ax = b have many applications in signal recovery and image reconstruction in tomography. Under certain conditions, the sparsest solution can be found by solving a constrained l1 minimization problem: min ||x||1 subject to Ax = b. Recently, the reweighted l1 minimization and l1 greedy algorithm have been introduced to improve the convergence of the l1 minimization problem. As an extension, a generalized l1 greedy algorithm for computerized tomography (CT) is proposed in this paper. It is implemented as a generalized total variation minimization for images with sparse gradients in CT. A numerical experiment is also given to illustrate the advantage of the new algorithm.
Keywords
  • Computed tomography,
  • Greedy algorithm
Disciplines
Publication Date
January 9, 2013
Citation Information
Jiehua Zhu. "A Generalized l1 Greedy Algorithm for Image Reconstruction in Computed Tomography" 2013 Joint Mathematics Meetings. San Diego, CA. Jan. 2013.
source:http://jointmathematicsmeetings.org/amsmtgs/2141_abstracts/1086-92-2969.pdf