CASIA OpenIR  > 多媒体计算与图形学团队
Accurate blind deblurring using salientpatch-based prior for large-size images
Ma, Chengcheng1,2,3; Zhang, Jiguang4; Xu, Shibiao3; Meng, Weiliang3; Xi, Runping1; Kumar, G. Hemantha4; Zhang, Xiaopeng3
Source PublicationMULTIMEDIA TOOLS AND APPLICATIONS
ISSN1380-7501
2018-11-01
Volume77Issue:21Pages:28077-28100
Corresponding AuthorXu, Shibiao(shibiao.xu@ia.ac.cn) ; Zhang, Xiaopeng(xiaopeng.zhang@ia.ac.cn)
AbstractThe full-image based kernel estimation strategy is usually susceptible by the smooth and fine-scale background regions impacting and it is time-consuming for large-size image deblurring. Since not all the pixels in the blurred image are informative and it is frequent to restore human-interested objects in the foreground rather than background, we propose a novel concept "SalientPatch" to denote informative regions for better blur kernel estimation without user guidance by computing three cues (objectness probability, structure richness and local contrast). Although these cues are not new, it is innovative to integrate and complement each other in motion blur restoration. Experiments demonstrate that our SalientPatch-based deblurring algorithm can significantly speed up the kernel estimation and guarantee high-quality recovery for large-size blurry images as well.
KeywordDeblurring SalientPatch Kernel estimation Segmentation Large-size
DOI10.1007/s11042-018-6009-2
WOS KeywordSALIENCY DETECTION ; DECONVOLUTION
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61620106003] ; National Natural Science Foundation of China[61671451] ; National Natural Science Foundation of China[61572405] ; National Natural Science Foundation of China[61502490] ; National Natural Science Foundation of China[61571439] ; National Natural Science Foundation of China[61771026] ; Open Projects Program of National Laboratory of Pattern Recognition[201600038] ; Independent Research Project of National Laboratory of Pattern Recognition[Z-2018005] ; Independent Research Project of National Laboratory of Pattern Recognition[6140001010207]
Funding OrganizationNational Natural Science Foundation of China ; Open Projects Program of National Laboratory of Pattern Recognition ; Independent Research Project of National Laboratory of Pattern Recognition
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000446601500015
PublisherSPRINGER
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23041
Collection多媒体计算与图形学团队
Corresponding AuthorXu, Shibiao; Zhang, Xiaopeng
Affiliation1.Northwestern Polytech Univ, Sch Comp Sci, Xian, Shaanxi, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
4.Univ Mysore, Dept Comp Sci, Mysore, Karnataka, India
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Ma, Chengcheng,Zhang, Jiguang,Xu, Shibiao,et al. Accurate blind deblurring using salientpatch-based prior for large-size images[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2018,77(21):28077-28100.
APA Ma, Chengcheng.,Zhang, Jiguang.,Xu, Shibiao.,Meng, Weiliang.,Xi, Runping.,...&Zhang, Xiaopeng.(2018).Accurate blind deblurring using salientpatch-based prior for large-size images.MULTIMEDIA TOOLS AND APPLICATIONS,77(21),28077-28100.
MLA Ma, Chengcheng,et al."Accurate blind deblurring using salientpatch-based prior for large-size images".MULTIMEDIA TOOLS AND APPLICATIONS 77.21(2018):28077-28100.
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