Alternating direction method of multipliers for nonconvex log total variation image restoration
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 338-359 |
| Journal / Publication | Applied Mathematical Modelling |
| Volume | 114 |
| Online published | 30 Sep 2022 |
| Publication status | Published - Feb 2023 |
Link(s)
Abstract
In this paper, we propose a nonconvex log total variation model for image restoration. A specific alternating direction method of multipliers is also presented to solve the nonconvex optimization model. Under mild conditions, we prove that the sequence generated by the proposed alternating direction method of multipliers converges to a stationary point. Experiment results on image denoising, image deblurring, computed tomography, magnetic resonance imaging and image super-resolution demonstrate that the proposed method is effective and improves the quality of image recovery.
Research Area(s)
- Alternating direction method of multipliers, Convergence, Image restoration, Log total variation, Nonconvex optimization
Citation Format(s)
Alternating direction method of multipliers for nonconvex log total variation image restoration. / Zhang, Benxin; Zhu, Guopu; Zhu, Zhibin et al.
In: Applied Mathematical Modelling, Vol. 114, 02.2023, p. 338-359.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
