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Single image super-resolution using combined total variation regularization by split Bregman Iteration
Li, Lin; Xie, Yuan; Hu, Wenrui; Zhang, Wensheng
Source PublicationNEUROCOMPUTING
2014-10-22
Volume142Pages:551-560
SubtypeArticle
AbstractThis paper addresses the problem of generating a high-resolution (HR) image from a single degraded low-resolution (LR) input image without any external training set. Due to the ill-posed nature of this problem, it is necessary to find an effective prior knowledge to make it well-posed. For this purpose, we propose a novel super-resolution (SR) method based on combined total variation regularization. In the first place, we propose a new regularization term called steering kernel regression total variation (SKRTV), which exploits the local structural regularity properties in natural images. In the second place, another regularization term called non-local total variation (NLTV) is employed as a complementary term in our method, which makes the most of the redundancy of similar patches in natural images. By combining the two complementary regularization terms, we propose a maximum a posteriori probability framework of SR reconstruction. Furthermore, split Bregman iteration is applied to implement the proposed model. Extensive experiments demonstrate the effectiveness of the proposed method. (C) 2014 Elsevier B.V. All rights reserved.
KeywordSuper-resolution Total Variation Steering Kernel Regression Split Bregman Iteration Local Structural Regularity Non-local Self-similarity
WOS HeadingsScience & Technology ; Technology
WOS KeywordKERNEL REGRESSION ; RECONSTRUCTION ; INTERPOLATION ; RESTORATION ; RECOGNITION
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000340341400057
Citation statistics
Cited Times:15[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/8042
Collection精密感知与控制研究中心_精密感知与控制
AffiliationUniv Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Li, Lin,Xie, Yuan,Hu, Wenrui,et al. Single image super-resolution using combined total variation regularization by split Bregman Iteration[J]. NEUROCOMPUTING,2014,142:551-560.
APA Li, Lin,Xie, Yuan,Hu, Wenrui,&Zhang, Wensheng.(2014).Single image super-resolution using combined total variation regularization by split Bregman Iteration.NEUROCOMPUTING,142,551-560.
MLA Li, Lin,et al."Single image super-resolution using combined total variation regularization by split Bregman Iteration".NEUROCOMPUTING 142(2014):551-560.
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