Yin, Mingming and Adam, Tarmizi and Paramesran, Raveendran and Hassan, Mohd Fikree (2022) An l(0)-overlapping group sparse total variation for impulse noise image restoration. Signal Processing-Image Communication, 102. ISSN 0923-5965, DOI https://doi.org/10.1016/j.image.2021.116620.
Full text not available from this repository.Abstract
Total variation (TV) based methods are effective models in image restoration. For eliminating impulse noise, an effective way is to use the l(1)-norm total variation model. However, the TV image restoration always yields staircase artifacts, especially in high-density noise levels. Additionally, the l(1)-norm tends to over penalize solutions and is not robust to outlier characteristics of impulse noise. In this paper, we propose a new total variation model to effectively remove the staircase effects and eliminate impulse noise. The proposed model uses the l(0)-norm data fidelity to effectively remove the impulse noise while the overlapping group sparse total variation (OGSTV) acts as a regularizer to eliminate the staircase artifacts. Since the proposed method requires solving an l(0)-norm and an OGSTV optimization problem, a formulation using the mathematical program with equilibrium constraints (MPEC) and the majorization-minimization (MM) method are respectively used together with the alternating direction method of multipliers (ADMM). Experiments demonstrate that our proposed model performs better than several state-of-the-art algorithms such as the e1 total generalized variation, e0 total variation, and the l(1) overlapping group sparse total variation in terms of the peak signal-to-noise ratio (PSNR) and the structural similarity index measure (SSIM).
| Item Type: | Article |
|---|---|
| Funders: | None |
| Uncontrolled Keywords: | Non-convex; Image restoration; Total variation; Alternating direction method |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering > Department of Electrical Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 05 Sep 2023 07:25 |
| Last Modified: | 05 Sep 2023 07:25 |
| URI: | http://eprints.um.edu.my/id/eprint/43076 |
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