High-order correlation of non-Rayleigh speckle fields and its application in super-resolution imaging

被引：12
|
作者：
Zhang, Suzhen [1 ,2 ,3 ]
Wang, Wei [4 ]
Yu, Rong [5 ]
Yang, Xiaoxue [1 ,2 ]
机构：
[1] Huazhong Univ Sci & Technol, Natl Lab Optoelect, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Sch Phys, Wuhan 430074, Peoples R China
[3] Dezhou Univ, Coll Phys & Elect Informat, Dezhou 253023, Peoples R China
[4] Chinese Acad Sci, Shanghai Inst Opt & Fine Mech, Shanghai 201800, Peoples R China
[5] Wuhan Inst Technol, Sch Sci, Hubei Prov Key Lab Intelligent Robot, Wuhan 430073, Peoples R China
来源：
LASER PHYSICS | 2016年 / 26卷 / 05期
基金：
美国国家科学基金会;
关键词：
quantum imaging; non-Rayleigh speckle; super-resolution imaging; ghost imaging; GHOST; LIGHT; ENTANGLEMENT; ILLUMINATION; DIFFRACTION; RESOLUTION; LIMIT;
D O I：
10.1088/1054-660X/26/5/055007
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
Classical correlation of Rayleigh speckle fields E(x) can only mimic second-order correlation in quantum imaging. Here, we propose a method to explore the high-order correlation of non-Rayleigh speckle fields E-N(x) which shows a totally different property from the Rayleigh speckle fields. As a specific example, we illustrate and analyze in detail the third-order speckle scanning imaging which overcomes the diffraction barrier by a factor of root 3. The influences of diffractions in the illumination path and the detection path are also discussed. This investigation may pave the way for applications in super-resolution imaging.
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收藏
页数：5
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  • [1] High-order ghost imaging using non-Rayleigh speckle sources
    Kuplicki, Kyrus
    Chan, Kam Wai Clifford
    [J]. OPTICS EXPRESS, 2016, 24 (23): : 26766 - 26776
  • [2] A Review of Super-Resolution Imaging through Optical High-Order Interference [Invited]
    Hong, Peilong
    Zhang, Guoquan
    [J]. APPLIED SCIENCES-BASEL, 2019, 9 (06):
  • [3] High-Order Residual Network for Light Field Super-Resolution
    Meng, Nan
    Wu, Xiaofei
    Liu, Jianzhuang
    Lam, Edmund
    [J]. THIRTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THE THIRTY-SECOND INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE AND THE TENTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2020, 34 : 11757 - 11764
  • [4] Generalized interpolation and its application in super-resolution imaging
    Rajan, D
    Chaudhuri, S
    [J]. IMAGE AND VISION COMPUTING, 2001, 19 (13) : 957 - 969
  • [5] Semiconducting Polymer Dots with Modulated Photoblinking for High-Order Super-Resolution Optical Fluctuation Imaging
    Sun, Zezhou
    Liu, Zhihe
    Chen, Haobin
    Li, Rongqin
    Sun, Yujie
    Chen, Danni
    Xu, Gaixia
    Liu, Liwei
    Wu, Changfeng
    [J]. ADVANCED OPTICAL MATERIALS, 2019, 7 (09)
  • [6] High-order super-resolution optical fluctuation imaging based on low-pass denoising
    Zou, Limin
    Zhang, Su
    Wang, Baokai
    Tan, Jiubin
    [J]. OPTICS LETTERS, 2018, 43 (04) : 707 - 710
  • [7] Mixed High-Order Non-Local Attention Network for Single Image Super-Resolution
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    Jiang, Saibiao
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    [J]. IEEE ACCESS, 2021, 9 : 49514 - 49521
  • [8] Multiframe super-resolution based on a high-order spatially weighted regularisation
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    Alahyane, Mohamed
    Ghazdali, Abdelghani
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  • [9] An edge preserving high-order PDE for multiframe image super-resolution
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    Hakim, Abdelilah
    [J]. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2019, 356 (11): : 5834 - 5857
  • [10] High-order relational generative adversarial network for video super-resolution
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    Mu, Yang
    Zhang, Yan
    [J]. PATTERN RECOGNITION, 2024, 146
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