Semisoft Generalized Total Variation Minimization for Image Reconstruction in Computed Tomography

Xiezhang Li, Fangjun Arroyo, Jiehua Zhu, Jianing Sun

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The generalized l1 greedy algorithm was recently proposed and shown to outperform the standard reweighted l1-minimization and l1-greedy algorithms for image reconstruction in computed tomography (CT). Herein, this algorithm is extended as a semisoft generalized l1 greedy algorithm by adapting the wavelet technique of semisoft thresholding. The extended algorithm can also be applied to image reconstruction by incorporating it into the BCPCS framework, resulting in a semisoft generalized total variation minimization (SSGTV) algorithm for CT. Numerical tests indicate that the proposed SSGTV algorithm improves the image reconstruction for CT.

Original languageEnglish
Article number7909042
Pages (from-to)8475-8481
Number of pages7
JournalIEEE Access
Volume5
DOIs
StatePublished - 2017

Keywords

  • Generalized l greedy algorithm
  • reweighted l-minimization
  • semisoft thresholding
  • total variation

Fingerprint

Dive into the research topics of 'Semisoft Generalized Total Variation Minimization for Image Reconstruction in Computed Tomography'. Together they form a unique fingerprint.

Cite this