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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
发表期刊MULTIMEDIA TOOLS AND APPLICATIONS
ISSN1380-7501
2018-11-01
卷号77期号:21页码:28077-28100
摘要

The 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.

关键词Deblurring SalientPatch Kernel estimation Segmentation Large-size
DOI10.1007/s11042-018-6009-2
关键词[WOS]SALIENCY DETECTION ; DECONVOLUTION
收录类别SCI
语种英语
资助项目Independent Research Project of National Laboratory of Pattern Recognition[6140001010207] ; Independent Research Project of National Laboratory of Pattern Recognition[Z-2018005] ; Open Projects Program of National Laboratory of Pattern Recognition[201600038] ; National Natural Science Foundation of China[61771026] ; National Natural Science Foundation of China[61571439] ; National Natural Science Foundation of China[61502490] ; National Natural Science Foundation of China[61572405] ; National Natural Science Foundation of China[61671451] ; National Natural Science Foundation of China[61620106003] ; National 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]
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号WOS:000446601500015
出版者SPRINGER
引用统计
被引频次:4[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/173211/23041
专题模式识别国家重点实验室_三维可视计算
多模态人工智能系统全国重点实验室
通讯作者Xu, Shibiao; Zhang, Xiaopeng
作者单位1.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
第一作者单位模式识别国家重点实验室
通讯作者单位模式识别国家重点实验室
推荐引用方式
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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