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A Survey of Sparse Representation: Algorithms and Applications
Zhang, Zheng1,2; Xu, Yong1,2; Yang, Jian3; Li, Xuelong4; Zhang, David5
Department光学影像学习与分析中心
2015
Source PublicationIEEE ACCESS
ISSN2169-3536
Volume3Pages:490-530
Contribution Rank4
AbstractSparse representation has attracted much attention from researchers in fields of signal processing, image processing, computer vision, and pattern recognition. Sparse representation also has a good reputation in both theoretical research and practical applications. Many different algorithms have been proposed for sparse representation. The main purpose of this paper is to provide a comprehensive study and an updated review on sparse representation and to supply guidance for researchers. The taxonomy of sparse representation methods can be studied from various viewpoints. For example, in terms of different norm minimizations used in sparsity constraints, the methods can be roughly categorized into five groups: 1) sparse representation with L-0-norm minimization; 2) sparse representation with L-p-norm (0 < p < 1) minimization; 3) sparse representation with L-1-norm minimization; 4) sparse representation with 12,1-norm minimization; and 5) sparse representation with 12-norm minimization. In this paper, a comprehensive overview of sparse representation is provided. The available sparse representation algorithms can also be empirically categorized into four groups: 1) greedy strategy approximation; 2) constrained optimization; 3) proximity algorithm-based optimization; and 4) homotopy algorithm-based sparse representation. The rationales of different algorithms in each category are analyzed and a wide range of sparse representation applications are summarized, which could sufficiently reveal the potential nature of the sparse representation theory. In particular, an experimentally comparative study of these sparse representation algorithms was presented.
SubtypeArticle
KeywordSparse Representation Compressive Sensing Greedy Algorithm Constrained Optimization Proximal Algorithm Homotopy Algorithm Dictionary Learning
Subject AreaComputer Science, Information Systems
WOS HeadingsScience & Technology ; Technology
DOI10.1109/ACCESS.2015.2430359
Indexed BySCI ; EI
WOS KeywordINTERIOR-POINT METHOD ; ORTHOGONAL MATCHING PURSUIT ; ROBUST FACE RECOGNITION ; SINGLE-IMAGE SUPERRESOLUTION ; LINEAR INVERSE PROBLEMS ; CONSISTENT K-SVD ; VISUAL TRACKING ; SIGNAL RECOVERY ; LOW-RANK ; THRESHOLDING ALGORITHM
Language英语
WOS Research AreaComputer Science ; Engineering ; Telecommunications
Funding OrganizationNational Natural Science Foundation of China(61370163 ; Shenzhen Municipal Science and Technology Innovation Council(JCYJ20130329151843309 ; China Post-Doctoral Science Foundation Funded Project(2014M560264) ; Shaanxi Key Innovation Team of Science and Technology(2012KCT-04) ; 61233011 ; JCYJ20140417172417174 ; 61332011) ; CXZZ20140904154910774)
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000371388200037
Citation statistics
Document Type期刊论文
Identifierhttp://ir.opt.ac.cn/handle/181661/27315
Collection光学影像学习与分析中心
Corresponding AuthorXu, Yong
Affiliation1.Harbin Inst Technol, Shenzhen Grad Sch, Biocomp Res Ctr, Shenzhen 518055, Peoples R China
2.Key Lab Network Oriented Intelligent Computat, Shenzhen 518055, Peoples R China
3.Nanjing Univ Sci & Technol, Coll Comp Sci & Technol, Nanjing 210094, Jiangsu, Peoples R China
4.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr Opt Imagery Anal & Learning, State Key Lab Transient Opt & Photon, Xian 710119, Shaanxi, Peoples R China
5.Hong Kong Polytech Univ, Biometr Res Ctr, Hong Kong, Hong Kong, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Zheng,Xu, Yong,Yang, Jian,et al. A Survey of Sparse Representation: Algorithms and Applications[J]. IEEE ACCESS,2015,3:490-530.
APA Zhang, Zheng,Xu, Yong,Yang, Jian,Li, Xuelong,&Zhang, David.(2015).A Survey of Sparse Representation: Algorithms and Applications.IEEE ACCESS,3,490-530.
MLA Zhang, Zheng,et al."A Survey of Sparse Representation: Algorithms and Applications".IEEE ACCESS 3(2015):490-530.
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