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- Title
Fast algorithm for box‐constrained fractional‐order total variation image restoration with impulse noise.
- Authors
Zhu, Jianguang; Wei, Juan; Hao, Binbin
- Abstract
In this paper, a novel variational model with box constraints is proposed to restore images corrupted by impulse noise. The proposed model is composed of fractional‐order total variation regularization and Lp‐fidelity term (0<p<1)$(0<p<1)$. Moreover, the new model possesses the advantages of preserving sharp edges and removing blocking effect. To solve the proposed model, some auxiliary variables are first introduced to transform it into some easy‐to‐solve subproblems. Further, the alternating direction method of multipliers, iteratively re‐weighted ℓ1 algorithm and fast iteration technique are adopted to solve the related subproblems. Numerical results show that the proposed model performs better in comparison with the several existing methods, in terms of both quantitative evaluation and visual quality.
- Subjects
BURST noise; IMAGE reconstruction; IMAGE denoising; ALGORITHMS; MATHEMATICAL regularization
- Publication
IET Image Processing (Wiley-Blackwell), 2022, Vol 16, Issue 12, p3359
- ISSN
1751-9659
- Publication type
Article
- DOI
10.1049/ipr2.12570