Nonorthogonal object identification based on ghost imaging

被引:8
|
作者
Gu, Xiaofan [1 ]
Zhao, Shengmei [1 ,2 ]
机构
[1] NUPT, Inst Signal Proc & Transmiss, Nanjing 210003, Jiangsu, Peoples R China
[2] NUPT, Minist Educ, Key Lab Broadband Wireless Commun & Sensor Networ, Nanjing 210003, Jiangsu, Peoples R China
来源
PHOTONICS RESEARCH | 2015年 / 3卷 / 05期
基金
高等学校博士学科点专项科研基金; 中国国家自然科学基金;
关键词
Image detection systems; Quantum information and processing;
D O I
10.1364/PRJ.3.000238
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Ghost imaging could be used to make a quick identification of orthogonal objects by means of photocurrent correlation measurements. In this paper, we extend the method to identify nonorthogonal objects. In the method, an object is illuminated by one photon from an entangled pair, and the other one is diffracted into a particular direction by a pre-established multiple-exposure hologram in the idler arm. By the correlation measurements, the nonorthogonal object in the signal arm could be discriminated within a very short time. The constraints for the identification of nonorthogonal objects are presented, which show that the nonorthogonal objects can be discriminated when the overlapping portion between any two objects is less than half of all the objects in the set. The numerical simulations further verify the result. (C) 2015 Chinese Laser Press
引用
收藏
页码:238 / 242
页数:5
相关论文
共 50 条
  • [1] Nonorthogonal object identification based on ghost imaging
    Xiaofan Gu
    Shengmei Zhao
    [J]. Photonics Research., 2015, 3 (05) - 242
  • [2] Nonorthogonal object identification based on ghost imaging
    Xiaofan Gu
    Shengmei Zhao
    [J]. Photonics Research, 2015, (05) : 238 - 242
  • [3] Object identification in computational ghost imaging based on deep learning
    Jianbo Li
    Mingnan Le
    Jun Wang
    Wei Zhang
    Bin Li
    Jinye Peng
    [J]. Applied Physics B, 2020, 126
  • [4] Object identification in computational ghost imaging based on deep learning
    Li, Jianbo
    Le, Mingnan
    Wang, Jun
    Zhang, Wei
    Li, Bin
    Peng, Jinye
    [J]. APPLIED PHYSICS B-LASERS AND OPTICS, 2020, 126 (10):
  • [5] Object authentication based on compressive ghost imaging
    Chen, Zhipeng
    Shi, Jianhong
    Zeng, Guihua
    [J]. APPLIED OPTICS, 2016, 55 (30) : 8644 - 8650
  • [6] Ghost imaging for an occluded object
    Gao, Chao
    Wang, Xiaoqian
    Gou, Lidan
    Feng, Yuling
    Cai, Hongji
    Wang, Zhifeng
    Yao, Zhihai
    [J]. LASER PHYSICS LETTERS, 2019, 16 (06)
  • [7] High-Quality Object Reconstruction Based on Ghost Imaging
    Xiao, Yin
    Zhou, Lina
    Chen, Wen
    [J]. 2019 PHOTONICS & ELECTROMAGNETICS RESEARCH SYMPOSIUM - FALL (PIERS - FALL), 2019, : 2903 - 2907
  • [8] Ghost imaging of blurred object based on deep-learning
    Zhang, Zijin
    Wang, Chunfang
    Gong, Wenlin
    Zhang, Dawei
    [J]. APPLIED OPTICS, 2021, 60 (13) : 3732 - 3739
  • [9] Cloaking of a phase object in ghost imaging
    Gan, Shu
    Zhang, Su-Heng
    Zhao, Ting
    Xiong, Jun
    Zhang, Xiangdong
    Wang, Kaige
    [J]. APPLIED PHYSICS LETTERS, 2011, 98 (11)
  • [10] Grayscale object authentication based on ghost imaging using binary signals
    Chen, Wen
    Chen, Xudong
    [J]. EPL, 2015, 110 (04)