Two New Efficient Iterative Regularization Methods for Image Restoration Problems
Iterative regularization methods are efficient regularization tools for image restoration problems. The IDR(s) and LSMR methods are state-of-the-arts iterative methods for solving large linear systems. Recently, they have attracted considerable attention. Little is known of them as iterative regular...
Saved in:
Main Authors: | Chao Zhao, Ting-Zhu Huang, Xi-Le Zhao, Liang-Jian Deng |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2013-01-01
|
Series: | Abstract and Applied Analysis |
Online Access: | http://dx.doi.org/10.1155/2013/129652 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Efficient Variational Method for Image Restoration
by: Jun Liu, et al.
Published: (2013-01-01) -
Split Bregman Iteration Algorithm for Image Deblurring Using Fourth-Order Total Bounded Variation Regularization Model
by: Yi Xu, et al.
Published: (2013-01-01) -
The regularity of solutions to the Lp Gauss image problem
by: Jia Xiumei, et al.
Published: (2025-01-01) -
Iterative Schemes for Nonconvex Quasi-Variational Problems with V-Prox-Regular Data in Banach Spaces
by: M. Bounkhel, et al.
Published: (2017-01-01) -
The Mann-Type Extragradient Iterative Algorithms with Regularization for Solving Variational Inequality Problems, Split Feasibility, and Fixed Point Problems
by: Lu-Chuan Ceng, et al.
Published: (2013-01-01)