A Generalized l1 Greedy Algorithm for Image Reconstruction in Computed Tomography2013 Joint Mathematics Meetings (2013)
AbstractThe 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.
- Computed tomography,
- Greedy algorithm
Publication DateJanuary 9, 2013
Citation InformationJiehua Zhu. "A Generalized l1 Greedy Algorithm for Image Reconstruction in Computed Tomography" 2013 Joint Mathematics Meetings. San Diego, CA. Jan. 2013.