微信服务号
微信订阅号
- TANG Shu
TANG Shu
Chongqing Key Laboratory of Computer Network and Communications Technology(Chongqing University of Posts and Telecommunications), Chongqing 400065, China
Find this author on CNKI
Find this author on BaiDu
Search for this author on this site - WAN Sheng-Dao
WAN Sheng-Dao
Chongqing Key Laboratory of Computer Network and Communications Technology(Chongqing University of Posts and Telecommunications), Chongqing 400065, China
Find this author on CNKI
Find this author on BaiDu
Search for this author on this site - YANG Shu-Li
YANG Shu-Li
Chongqing Key Laboratory of Computer Network and Communications Technology(Chongqing University of Posts and Telecommunications), Chongqing 400065, China
Find this author on CNKI
Find this author on BaiDu
Search for this author on this site - XIE Xian-Zhong
XIE Xian-Zhong
Chongqing Key Laboratory of Computer Network and Communications Technology(Chongqing University of Posts and Telecommunications), Chongqing 400065, China
Find this author on CNKI
Find this author on BaiDu
Search for this author on this site - XIA Ming
XIA Ming
Chongqing Key Laboratory of Computer Network and Communications Technology(Chongqing University of Posts and Telecommunications), Chongqing 400065, China
Find this author on CNKI
Find this author on BaiDu
Search for this author on this site - ZHANG Xu
ZHANG Xu
Chongqing Key Laboratory of Computer Network and Communications Technology(Chongqing University of Posts and Telecommunications), Chongqing 400065, China
Find this author on CNKI
Find this author on BaiDu
Search for this author on this site
TP391
National Natural Science Foundation of China (61601070, 61271259); Project of Science and Technology Research of Chongqing Education Commission (KJZD-K201800603, KJZD-M201900602); Fundamental and Advanced Technology Research Project of Chongqing (CSTC2016jcyjA0455, CSTC2014kjrc-qnrc40002); Science and Technology Research Project of Chongqing Municipal Education Commission (KJ1600411, KJ1400429)
- Article | |
- Metrics |
- Reference |
- Related |
- Cited by | |
- Comments
The accurate motion blur kernel (MBK) estimation is the key for the success of the single-image blind motion deblurring. Nevertheless, because of the imperfect useful edges selection and the simple regularizers design, the MBKs estimated by existing methods are inaccurate and contain various flaws. Therefore, in order to estimate an accurate MBK, in this study, a spatial-scale-information method for MBK estimation is proposed. First, in order to accurately extract the useful image edges and remove the pernicious image structures, an image smoothing model based on the spatial scale information is proposed, such that the useful image edges can be extracted accurately and quickly. Then, according to the characteristics of the MBK, a regularization constraint model, which combines spatial L0 norm with gradient L2 norm, is proposed for preserving the continuity and the sparsity of the MBK well. By combining the extracted useful image edges and the proposed regularization constraint model, the accurate MBK estimation can be achieved. Finally, a half-quadratic splitting alternating optimization strategy is employed to solve the proposed model. Extensive experiments results demonstrate that the proposed method can estimate more accurate MBKs and obtain higher quality deblurring images in terms of both quantitative metrics and subjective vision.
Get Citation
唐述,万盛道,杨书丽,谢显中,夏明,张旭.空间尺度信息的运动模糊核估计方法.软件学报,2019,30(12):3876-3891
Copy
Article Metrics
- Abstract:1450
- PDF: 3357
- HTML: 2090
- Cited by: 0
History
- Received:April 19,2017
- Revised:January 26,2018
- Online: December 05,2019
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-4
Address：4# South Fourth Street, Zhong Guan Cun, Beijing 100190,Postal Code：100190
Phone：010-62562563 Fax：010-62562533 Email：jos@iscas.ac.cn
Technical Support：Beijing Qinyun Technology Development Co., Ltd.
