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《Chinese Journal of Optics》 2011-05
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Application of compressed sensing theory in image processing

ZHU Ming1,GAO Wen1,2,GUO Li-qiang1 (1.Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences,Changchun 130033,China;2.Graduate University of Chinese Academy of Sciences,Beijing 100039,China)  
Traditional Shannon sampling method leads to a large amount of image data,and massive data processing brings a great pressure to bear on the post-processing of image information.Compressed Sensing(CS) theory which can overcome the problem mentioned above is researched in this paper.It can reconstruct a large amount data by sampling small quantity data,and breakthroughs the restriction of Shannon sampling theory.This paper reviews the theory and key technique of CS,and introduces the application and development of CS in imaging system,image fusion,target recognition and tracking.It points out that the CS theory is an effective data processing,and more extensive applications will be come true with the development of the theory.
【Fund】: 中国科学院二期创新工程基金资助项目(No.C50Top2)
【CateGory Index】: TP391.41
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1 CAI Cheng,ZHANG Ming,ZHU JunPing Deparment of Computer Science,College of Information Engineering,Northwest A&F University,Yangling 712100,China;Weed seeds classification based on compressive sensing theory[J];Scientia Sinica(Informationis);2010-S1
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