Single image super-resolution using combined total variation regularization by split Bregman Iteration
Li, Lin; Xie, Yuan; Hu, Wenrui; Zhang, Wensheng
2014-10-22
发表期刊NEUROCOMPUTING
卷号142页码:551-560
文章类型Article
摘要This 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.
关键词Super-resolution Total Variation Steering Kernel Regression Split Bregman Iteration Local Structural Regularity Non-local Self-similarity
WOS标题词Science & Technology ; Technology
关键词[WOS]KERNEL REGRESSION ; RECONSTRUCTION ; INTERPOLATION ; RESTORATION ; RECOGNITION
收录类别SCI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000340341400057
引用统计
被引频次:12[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/8042
专题精密感知与控制研究中心_精密感知与控制
作者单位Univ Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
推荐引用方式
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.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
Single image super-r(12862KB)期刊论文作者接受稿开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Li, Lin]的文章
[Xie, Yuan]的文章
[Hu, Wenrui]的文章
百度学术
百度学术中相似的文章
[Li, Lin]的文章
[Xie, Yuan]的文章
[Hu, Wenrui]的文章
必应学术
必应学术中相似的文章
[Li, Lin]的文章
[Xie, Yuan]的文章
[Hu, Wenrui]的文章
相关权益政策
暂无数据
收藏/分享
文件名: Single image super-resolution using combined total variation regularization by split Bregman Iteration.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。