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- Title
A new hybrid \begin{document}$ l_p $\end{document}-\begin{document}$ l_2 $\end{document} model for sparse solutions with applications to image processing.
- Authors
Gao, Xuerui; Bai, Yanqin; Fang, Shu-Cherng; Luo, Jian; Li, Qian
- Abstract
Finding sparse solutions to a linear system has many real-world applications. In this paper, we study a new hybrid of the l p quasi-norm (0 < p < 1) and l 2 norm to approximate the l 0 norm and propose a new model for sparse optimization. The optimality conditions of the proposed model are carefully analyzed for constructing a partial linear approximation fixed-point algorithm. A convergence proof of the algorithm is provided. Computational experiments on image recovery and deblurring problems clearly confirm the superiority of the proposed model over several state-of-the-art models in terms of the signal-to-noise ratio and computational time.
- Subjects
APPROXIMATION algorithms; SIGNAL-to-noise ratio; LINEAR systems; IMAGE processing; DOCUMENT imaging systems; QUASI-Newton methods
- Publication
Journal of Industrial & Management Optimization, 2023, Vol 19, Issue 2, p890
- ISSN
1547-5816
- Publication type
Article
- DOI
10.3934/jimo.2021211