Semisoft Generalized Total Variation Minimization for Image Reconstruction in Computed Tomography | Zendy

Xiezhang Li | Zendy; Fangjun Arroyo | Zendy; Jiehua Zhu | Zendy; Jianing Sun | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Semisoft Generalized Total Variation Minimization for Image Reconstruction in Computed Tomography

Author(s) -

Xiezhang Li,

Fangjun Arroyo,

Jiehua Zhu,

Jianing Sun

Publication year - 2017

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2017.2692245

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research