Representation of Signals and Images by Complex Coefficient Weighted Singularity Functions

摘要：

Previously proposed singularity function models are suitable only for representing real data.However,in a number of application domains such as magnetic resonance imaging,the initial raw data are complex images,which requires new image models for representing them.In this paper,a novel singularity function analysis model is proposed that represents a complex discrete signal or image as a linear complex coefficient weighted combination of singularity functions.The interest of such model is investigated in the case of high-resolution image reconstruction problems.The results show that the thus obtained reconstruction approach provides significantly better performance than existing reconstruction techniques.

作者: J.H.Luo L.Zhang Y.G.Bai X.Y.Ding Y.M.Zhu

作者单位: College of Life Science and Technology,Shanghai Jiaotong University,200240,Shanghai,P.R.China. CREATIS-LRMN,CNRS UMR 5220,Inserm U630,INSA of Lyon,University of Lyon 1,University of Lyon,69621 Vi

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）