Solving total-variation image super-resolution problems via proximal symmetric alternating direction methods

Solving total-variation image super-resolution problems via proximal symmetric alternating direction methods

Abstract The single image super-resolution (SISR) problem represents a class of efficient models appealing in many computer vision applications. In this paper, we focus on designing a proximal symmetric alternating direction method of multipliers (SADMM) for the SISR problem. By taking full exploita...

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Bibliographic Details
Main Authors: Bin Gao, Fenggang Sun, Ying Tong, Shiming Xu
Format: Article
Language:English
Published: SpringerOpen 2016-08-01
Series:Journal of Inequalities and Applications
Subjects:
proximal symmetric alternating direction method of multipliers
linearized Peaceman-Rechford splitting method
convex minimization
strictly contractive
single image super-resolution
Online Access:http://link.springer.com/article/10.1186/s13660-016-1136-7

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http://link.springer.com/article/10.1186/s13660-016-1136-7

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