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Low Rank Prior and Total Variation Regularization for Image Deblurring
Ma, Liyan1; Xu, Li2; Zeng, Tieyong3,4
2017-03-01
Source PublicationJOURNAL OF SCIENTIFIC COMPUTING
ISSN0885-7474
Volume70Issue:3Pages:1336-1357
AbstractThe similar image patches should have similar underlying structures. Thus the matrix constructed from stacking the similar patches together has low rank. Based on this fact, the nuclear norm minimization, which is the convex relaxation of low rank minimization, leads to good denoising results. Recently, the weighted nuclear norm minimization has been applied to image denoising. This approach presents state-of-the-art result for image denoising. In this paper, we further study the weighted nuclear norm minimization problem for general image recovery task. For the weights being in arbitrary order, we prove that such minimization problem has a unique global optimal solution in the closed form. Incorporating this idea with the celebrated total variation regularization, we then investigate the image deblurring problem. Numerical experimental results illustratively clearly that the proposed algorithms achieve competitive performance.
KeywordImage deblurring Low rank Nuclear norm Variational method
DOI10.1007/s10915-016-0282-x
Language英语
Funding ProjectNational Natural Science Foundation of China[61402462] ; National Natural Science Foundation of China[11271049] ; National Natural Science Foundation of China[11201455] ; National Natural Science Foundation of China[11671383] ; National Natural Science Foundation of China[61503202] ; RGC[211911] ; RGC[12302714] ; RFGs of HKBU
WOS Research AreaMathematics
WOS SubjectMathematics, Applied
WOS IDWOS:000394326400015
PublisherSPRINGER/PLENUM PUBLISHERS
Citation statistics
Cited Times:10[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/24823
Collection计算数学与科学工程计算研究所
Affiliation1.Chinese Acad Sci, Inst Microelect, Beijing 100029, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Inst Computat Math, LSEC, Beijing, Peoples R China
3.Hong Kong Baptist Univ, Dept Math, Kowloon Tong, Hong Kong, Peoples R China
4.HKBU Inst Res & Continuing Educ, Shenzhen Virtual Univ Pk, Shenzhen 518057, Peoples R China
Recommended Citation
GB/T 7714
Ma, Liyan,Xu, Li,Zeng, Tieyong. Low Rank Prior and Total Variation Regularization for Image Deblurring[J]. JOURNAL OF SCIENTIFIC COMPUTING,2017,70(3):1336-1357.
APA Ma, Liyan,Xu, Li,&Zeng, Tieyong.(2017).Low Rank Prior and Total Variation Regularization for Image Deblurring.JOURNAL OF SCIENTIFIC COMPUTING,70(3),1336-1357.
MLA Ma, Liyan,et al."Low Rank Prior and Total Variation Regularization for Image Deblurring".JOURNAL OF SCIENTIFIC COMPUTING 70.3(2017):1336-1357.
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