Image Super-Resolution With Sparse Neighbor Embedding

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 光学影像学习与分析中心

	Image Super-Resolution With Sparse Neighbor Embedding
	Gao, Xinbo 1; Zhang, Kaibing 1; Tao, Dacheng 2,3; Li, Xuelong 4
刊名	ieee transactions on image processing
	2012-07-01
卷号	21 期号:7 页码:3194-3205
关键词	Histograms of oriented gradients (HoG) neighbor embedding (NE) sparse representation super-resolution (SR)
ISSN号	1057-7149
产权排序	4
合作状况	国际
英文摘要	until now, neighbor-embedding-based (ne) algorithms for super-resolution (sr) have carried out two independent processes to synthesize high-resolution (hr) image patches. in the first process, neighbor search is performed using the euclidean distance metric, and in the second process, the optimal weights are determined by solving a constrained least squares problem. however, the separate processes are not optimal. in this paper, we propose a sparse neighbor selection scheme for sr reconstruction. we first predetermine a larger number of neighbors as potential candidates and develop an extended robust-sl0 algorithm to simultaneously find the neighbors and to solve the reconstruction weights. recognizing that the k-nearest neighbor (k-nn) for reconstruction should have similar local geometric structures based on clustering, we employ a local statistical feature, namely histograms of oriented such clustering. by conveying local structural information of hog in the synthesis stage, the k-nn of each lr input patch is adaptively chosen from their associated subset, which significantly improves the speed of synthesizing the hr image while preserving the quality of reconstruction. experimental results suggest that the proposed method can achieve competitive sr quality compared with other state-of-the-art baselines.
学科主题	computer science ; artificial intelligence ; engineering ; electrical & electronic
WOS标题词	science & technology ; technology
类目[WOS]	computer science, artificial intelligence ; engineering, electrical & electronic
研究领域[WOS]	computer science ; engineering
关键词[WOS]	quality assessment ; representation ; interpolation ; reconstruction ; algorithm ; norm
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000305577600007
公开日期	2012-09-03
内容类型	期刊论文
源URL	[http://ir.opt.ac.cn/handle/181661/20249]
专题	西安光学精密机械研究所_光学影像学习与分析中心
作者单位	1.Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China 2.Univ Technol Sydney, Fac Engn & Informat Technol, Sydney, NSW 2007, Australia 3.Univ Technol Sydney, Ctr Quantum Computat & Intelligent Syst, Sydney, NSW 2007, Australia 4.Chinese Acad Sci, Ctr Opt Imagery Anal & Learning, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China
推荐引用方式 GB/T 7714	Gao, Xinbo,Zhang, Kaibing,Tao, Dacheng,et al. Image Super-Resolution With Sparse Neighbor Embedding[J]. ieee transactions on image processing,2012,21(7):3194-3205.
APA	Gao, Xinbo,Zhang, Kaibing,Tao, Dacheng,&Li, Xuelong.(2012).Image Super-Resolution With Sparse Neighbor Embedding.ieee transactions on image processing,21(7),3194-3205.
MLA	Gao, Xinbo,et al."Image Super-Resolution With Sparse Neighbor Embedding".ieee transactions on image processing 21.7(2012):3194-3205.