期刊文献+

确定性相位掩膜可压缩双透镜成像 被引量:3

Compressive Double Lens Imaging Using Deterministic Phase Mask
下载PDF
导出
摘要 压缩成像是压缩传感理论的一个重要应用领域.本文将确定性测量引入压缩成像,提出一种确定性相位掩膜可压缩双透镜成像方法.模拟实验结果表明,新的成像方法可以在显著地降低物理实现成本的同时,有效地捕获图像信息来重建原始图像.此方法改变了经典的模拟-数字转换的光学成像思路,减少模数转换开销,并有利于图像的传输和存储,可以为照相机的设计提供若干理论、计算和技术支撑. Compressive imaging is an important application of the theory of compressive sensing.The deterministic measurements were introduced into compressive imaging and a novel method-compressive double lens imaging was proposed using deterministic phase mask.Simulation results show that novel imaging method can effectively capture the information of image,and reduce the difficulty and costs of the hardware implementation significantly.The classical analog-to-digital conversion of optical imaging is changed,the digital conversion costs are reduced,and the image transmission and storage are able to be facilitated by the proposed method,which provides some theoretical,computing and technical support for new design of camera.
出处 《光子学报》 EI CAS CSCD 北大核心 2011年第6期949-954,共6页 Acta Photonica Sinica
基金 国家自然科学基金(No.60473102) "新一代宽带无线移动通信网"国家科技重大专项(No.2009ZX03006-001-02) 安徽高校省级自然科学研究项目(No.KJ2011B131)资助
关键词 压缩传感 压缩成像 成像系统 相位掩膜 确定性测量 Compressive sensing Compressive imaging Imaging system Phase mask Deterministic measurements
  • 相关文献

参考文献4

二级参考文献177

  • 1张春梅,尹忠科,肖明霞.基于冗余字典的信号超完备表示与稀疏分解[J].科学通报,2006,51(6):628-633. 被引量:71
  • 2R Baraniuk.A lecture on compressive sensing[J].IEEE Signal Processing Magazine,2007,24(4):118-121.
  • 3Guangming Shi,Jie Lin,Xuyang Chen,Fei Qi,Danhua Liu and Li Zhang.UWB echo signal detection with ultra low rate sampling based on compressed sensing[J].IEEE Trans.On Circuits and Systems-Ⅱ:Express Briefs,2008,55(4):379-383.
  • 4Cand,S E J.Ridgelets:theory and applications[I)].Stanford.Stanford University.1998.
  • 5E Candès,D L Donoho.Curvelets[R].USA:Department of Statistics,Stanford University.1999.
  • 6E L Pennec,S Mallat.Image compression with geometrical wavelets[A].Proc.of IEEE International Conference on Image Processing,ICIP'2000[C].Vancouver,BC:IEEE Computer Society,2000.1:661-664.
  • 7Do,Minh N,Vetterli,Martin.Contourlets:A new directional multiresolution image representation[A].Conference Record of the Asilomar Conference on Signals,Systems and Computers[C].Pacific Groove,CA,United States:IEEE Computer Society.2002.1:497-501.
  • 8G Peyré.Best Basis compressed sensing[J].Lecture Notes in Ccmputer Science,2007,4485:80-91.
  • 9V Temlyakov.Nonlinear Methods of Approximation[R].IMI Research Reports,Dept of Mathematics,University of South Carolina.2001.01-09.
  • 10S Mallat,Z Zhang.Matching pursuits with time-frequency dictionaries[J].IEEE Trans Signal Process,1993,41(12):3397-3415.

共引文献900

同被引文献41

  • 1刘吉英.压缩感知理论及在成像中的应用[D].国防科学技术大学.2010
  • 2A Mehmet,P Jinsoo,T Vahid.A Coding Theory Approach to Noisy Compressive Sensing Using Low Density Frames[].IEEE Trans on Signale Processing.2011
  • 3DONOHO D L,TSAIG Y,DRORI I,et al.Sparse solution of underdetermined system of linear equations by stagewise orthogonal matching pursuit[].IEEE Transactions on Information Theory.2012
  • 4D.L.Donoho.Compressed sensing[].IEEE Transactions on Information Theory.2006
  • 5D.Wei,O.Milenkovic.Subspace pursuit for compressivesensing signal reconstruction[].IEEE Transactions on Information Theory.2009
  • 6Yu Lifeng,Li Gang,Chang Liping.Optimizing projection matrixfor compressed sensing systems[].th InternationalConference on InformationCommunications and SignalProcessing(ICICS).2011
  • 7E.J.Candes,T.Tao.Near-optimal signal recovery fromrandom projections:universal encoding strategies[].IEEETransInformation Theory.2006
  • 8M.F.Duarte,M.A.Davenport,D.Takhar et al.Single-pixelimaging via compressive sampling[].IEEE Signal ProcessingMagazine.2008
  • 9M.Elad.Optimized projections for compressed sensing[].IEEE Transactions on Signal Processing.2007
  • 10J.M.Duarte-Carvajalino,G.Sapiro.Learning to sense sparsesignals:simultaneous sensing matrix and sparsifying dictionaryoptimization[].IEEE Transactions on Image Processing.2009

引证文献3

二级引证文献15

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部