Research on ghost image reconstruction algorithm based on photons simulation with doubly Poisson stochastic process

被引:0
|
作者
Yang, Yibing [1 ]
Yan, Qiurong [1 ]
Wang, Yifan [1 ]
Li, Dan [1 ]
Tao, Ling [1 ]
机构
[1] Nanchang Univ, Dept Elect Informat Engn, Nanchang 330031, Jiangxi, Peoples R China
基金
中国国家自然科学基金;
关键词
doubly Poisson stochastic process; ghost imaging; TCSPC; photon-counting; simulation; PSNR; LIGHT;
D O I
10.1117/12.2511627
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
In this paper, we propose a photon counting ghost imaging scheme based on time-correlated single photon counting, and based on this scheme, Monte Carlo simulation is conduct with doubly Poisson stochastic process model,the feasibility of traditional ghost imaging and corresponding ghost imaging is verified in this simulation, the influencing factors such as the number of frame M and the number of pulse within a single digital micro-minor device(DMD) period D is also analyzed in the simulation. The results shows that the corresponding ghost imaging algorithm can effectively reduce the calculation amount when the imaging quality is close between the two algorithms, and the number of frames M has a greater influence on image quality. The model can effectively verify the feasibility of system design and improve the efficiency of the experiment, saving experiment time and costs.
引用
收藏
页数:7
相关论文
共 50 条
  • [21] On the characteristic functional of a doubly stochastic Poisson process: Application to a narrow-band process
    Bouzas, P. R.
    Valderrama, M. J.
    Aguilera, A. M.
    APPLIED MATHEMATICAL MODELLING, 2006, 30 (09) : 1021 - 1032
  • [22] The application of compressed sensing algorithm based on total variation method into ghost image reconstruction
    Song, Yangyang
    Wu, Guohua
    Luo, Bin
    INTERNATIONAL CONFERENCE ON OPTOELECTRONICS AND MICROELECTRONICS TECHNOLOGY AND APPLICATION, 2017, 10244
  • [23] Functional principal component modelling of the-intensity of a doubly stochastic Poisson process
    Aguilera, AM
    Bouzas, PR
    Ruiz-Fuentes, N
    COMPSTAT 2002: PROCEEDINGS IN COMPUTATIONAL STATISTICS, 2002, : 373 - 376
  • [24] Doubly stochastic Poisson process models for precipitation at fine time-scales
    Ramesh, Nadarajah I.
    Onof, Christian
    Xie, Dichao
    ADVANCES IN WATER RESOURCES, 2012, 45 : 58 - 64
  • [25] AN IMPROVED PROCEDURE FOR EVALUATING THE STATISTICAL CHARACTERISTICS OF A DOUBLY STOCHASTIC POISSON-PROCESS
    GUTIERREZ, R
    VALDERRAMA, MJ
    THEORY OF PROBABILITY AND ITS APPLICATIONS, 1992, 37 (02) : 340 - 342
  • [26] NONPARAMETRIC INFERENCE OF DOUBLY STOCHASTIC POISSON PROCESS DATA VIA THE KERNEL METHOD
    Zhang, Tingting
    Kou, S. C.
    ANNALS OF APPLIED STATISTICS, 2010, 4 (04): : 1913 - 1941
  • [27] An image reconstruction algorithm based on regularization optimization for process tomography
    Ding, Yong-Wei
    Dong, Feng
    PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2007, : 1717 - 1722
  • [28] A PDE based Expectation Maximization algorithm adapted to Poisson noise for Medical Image Reconstruction
    Tiwari, Shailendra
    Srivastava, Rajeev
    2014 IEEE INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY (ISSPIT), 2014, : 137 - 142
  • [29] Research on a hybrid ERT image reconstruction algorithm based on GA
    Xiao, Liqing
    Shao, Xiaogen
    Li, Zilong
    Shi, Tianming
    Zhang, Liang
    Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument, 2010, 31 (02): : 305 - 311
  • [30] Stochastic origin ensemble image reconstruction algorithm for time-of-flight dual photons emission computed tomography system
    Chiang, C. C.
    Chuang, K. S.
    Lin, H. H.
    Ni, Y. C.
    EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2016, 43 : S505 - S506