Face image super-resolution through locality-induced support regression
文献类型：期刊论文
| 作者 | Junjun Jiang ; Ruimin Hu; Chao Liang; Zhen Han; Chunjie Zhang
|
| 刊名 | Signal Processing
 |
| 出版日期 | 2014 |
| 期号 | 103页码:168-183 |
| 关键词 | Super-resolution Face Image Support Regression Manifold Learning |
| 英文摘要 | In thispaperweproposeanovelfaceimagesuper-resolution(SR)methodnamed Locality-inducedSupportRegression(LiSR).Givenalow-resolution(LR)inputpatch,we learnamappingfunctionbetweenthelocalsupportLRandhigh-resolution(HR)patch pairs topredictitsHRversion.ThesupportcanbeobtainedfromtheLRorHRpatch manifolds,whichleadstotwovarietiesofLiSR,namelyLRpatchguidedLiSR(LR-LiSR)and HR patchguidedLiSR(HR-LiSR).LR-LiSRdirectlylearnsthemappingfunctionbetween local supportLR/HRpatchpairsgivenaninputLRpatch.AsforHR-LiSR,thesupportanda mappingfunctionwillbeiterativelylearnedtoupdatethetargetHRpatch.Thekey advantagesofourproposedframeworkaretwo-fold:(1)thestrongregularizationof “same representation” of priorwork [1,2] is relaxedtothesamesupport,andhencemuch flexibilitycanbegiventothelearnedmappingfunction;(2)wedefinethesupportinthe LR orHRpatchmanifoldspacebyincorporatingthelocalityconstraint,whichcanwell preserve themanifoldstructureofthetrainingset.Experimentalresultsreportedonboth simulatedLRfaceimagesandreal-worlddatasetsdemonstratetheeffectivenessofthe proposed method. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/15393]  |
| 专题 | 自动化研究所_类脑智能研究中心 |
| 推荐引用方式 GB/T 7714 | Junjun Jiang,Ruimin Hu,Chao Liang,et al. Face image super-resolution through locality-induced support regression[J]. Signal Processing,2014(103):168-183. |
| APA | Junjun Jiang,Ruimin Hu,Chao Liang,Zhen Han,&Chunjie Zhang.(2014).Face image super-resolution through locality-induced support regression.Signal Processing(103),168-183. |
| MLA | Junjun Jiang,et al."Face image super-resolution through locality-induced support regression".Signal Processing .103(2014):168-183. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。