• Photonics Research
  • Vol. 4, Issue 6, 281 (2016)
Chao Yang1, Chenglong Wang2, Jian Guan1, Chi Zhang1..., Shuxu Guo1, Wenlin Gong2,3 and Fengli Gao1,*|Show fewer author(s)
Author Affiliations
  • 1State Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, China
  • 2Key Laboratory for Quantum Optics and Center for Cold Atom Physics of CAS, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China
  • 3e-mail: gongwl@siom.ac.cn
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    DOI: 10.1364/PRJ.4.000281 Cite this Article Set citation alerts
    Chao Yang, Chenglong Wang, Jian Guan, Chi Zhang, Shuxu Guo, Wenlin Gong, Fengli Gao, "Scalar-matrix-structured ghost imaging," Photonics Res. 4, 281 (2016) Copy Citation Text show less

    Abstract

    The features of the characteristic matrix used in linear intensity correlation reconstruction methods are directly related to the quality of ghost imaging. In order to suppress the noise caused by the off-diagonal elements in the characteristic matrix, we propose a reconstruction method for ghost imaging called scalar-matrix-structured ghost imaging (SMGI). The characteristic matrix is made to approximate a scalar matrix by modifying the measurement matrix. Experimental results show that SMGI improves the peak signal-to-noise ratio of the object reconstruction significantly compared with differential ghost imaging, even in the case of a nonzero two-arm longitudinal difference, which is a promising result for practical applications.of China (2013AA122901); National Natural Science Foundation of China (NSFC) (61571427); Youth Innovation Promotion Association of the Chinese Academy of Sciences (2013162).
    TGI(x,y)=1Nn=1N(Bn-Bn)In(x,y)=1Nn=1N(Bn-Bn)(In(x,y)-In(x,y)),(1)

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    Ψ=[I1(1,1)I1(1,2)I1(q,q)I2(1,1)I2(q,q)IN(1,1)IN(1,2)IN(q,q)].(2)

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    B=[B1,B2Bn]T.(3)

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    T=[T(1,1)T(1,2)T(q,q)].(4)

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    TGI=1N(ΨIΨ)T(BIB)=1N(ΨIΨ)T(ΨIΨ)T=1NΦTΦT,(5)

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    Anew=(ΦTΦX)Φ,(6)

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    TSMGI=1NAnewT=1N(ΦTΦX)ΦT=1N(ΦTΦX)(BIB).(7)

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    ΦX=(ΦTΦAnew)/Φ.(8)

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