Preconditioned Three-Operator Splitting Algorithm with Applications to Image Restoration

In this paper, we present primal-dual splitting algorithms for the convex minimization problem involving smooth functions with Lipschitzian gradient, finite sum of nonsmooth proximable functions, and linear composite functions. Many total variation-based image processing problems are special cases o...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Journal of scientific computing Ročník 92; číslo 3; s. 106
Hlavní autoři: Tang, Yuchao, Wen, Meng, Zeng, Tieyong
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.09.2022
Springer Nature B.V
Témata:
Algorithms
Composite functions
Computational Mathematics and Numerical Analysis
Convex analysis
Image processing
Image restoration
Mathematical and Computational Engineering
Mathematical and Computational Physics
Mathematics
Mathematics and Statistics
Optimization
Splitting
Theoretical
Convex minimization
Three-operator splitting algorithm
Primal-dual algorithm
90C46
90C25
Total variation
47A52
ISSN:0885-7474, 1573-7691
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:In this paper, we present primal-dual splitting algorithms for the convex minimization problem involving smooth functions with Lipschitzian gradient, finite sum of nonsmooth proximable functions, and linear composite functions. Many total variation-based image processing problems are special cases of such problems. The obtained primal-dual splitting algorithms are derived from a preconditioned three-operator splitting algorithm applied to primal-dual optimality conditions in a proper product space. The convergence of the proposed algorithms under appropriate assumptions on the parameters has been proved. Numerical experiments on a novel image restoration problem are presented to demonstrate the efficiency and effectiveness of the proposed algorithms.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0885-7474
1573-7691
DOI:10.1007/s10915-022-01958-w