[1] Pittman T B, Shih Y H, Strekalov D V, et al. Optical imaging by means of two-photon quantum entanglement[J]. Physical Review A, 1995, 52(5): R3429-R3432.
[2] Bennink R S, Bentley S J, Boyd R W. “Two-Photon" coincidence imaging with a classical source[J]. Physical Review Letters, 2002, 89(11): 113601.
[3] Garbe U, Ahuja Y, Ibrahim R, et al. Industrial application experiments on the neutron imaging instrument DINGO[J]. Physics Procedia, 2017, 88: 13-18.
[4] Gatti A, Brambilla E, Bache M, et al. Ghost imaging with thermal light: Comparing entanglement and classical correlation[J]. Physical Review Letters, 2004, 93(9): 093602.
[5] Zhang D, Zhai Y H, Wu L G, et al. Correlated two-photon imaging with true thermal light[J]. Optics Letters, 2005, 30(18): 2354-2356.
[6] Tian N, Guo Q C, Wang A L, et al. Fluorescence ghost imaging with pseudothermal light[J]. Optics Letters, 2011, 36(16): 3302-3304.
[7] Martienssen W, Spiller E. Coherence and fluctuations in light beams[J]. American Journal of Physics, 1964, 32(12): 919-926.
[8] Shih Y. The physics of ghost imaging: Nonlocal interference or local intensity fluctuation correlation?[J]. Quantum Information Processing, 2012, 11(4): 995-1001.
[9] Strekalov D V, Sergienko A V, Klyshko D N, et al. Observation of two-photon “ghost" interference and diffraction[J]. Physical Review Letters, 1995, 74(18): 3600-3603.
[10] Gong W L, Han S S. Phase-retrieval ghost imaging of complex-valued objects[J]. Physical Review A, 2010, 82(2): 023828.
[11] Khakimov R I, Henson B M, Shin D K, et al. Ghost imaging with atoms[J]. Nature, 2016, 540(7631): 100-103.
[12] Kingston A M, Myers G R, Pelliccia D, et al. Neutron ghost imaging[J]. Physical Review A, 2020, 101(5): 053844.
[13] Li S, Cropp F, Kabra K, et al. Electron ghost imaging[J]. Physical Review Letters, 2018, 121(11): 114801.
[14] Chen B K, Sidorenko P, Lahav O, et al. Multiplexed single-shot ptychography[J]. Optics Letters, 2018, 43(21): 5379-5382.
[15] Miao J W, Charalambous P, Kirz J, et al. Extending the methodology of X-ray crystallography to allow imaging of micrometre-sized non-crystalline specimens[J]. Nature, 1999, 400(6742): 342-344.
[16] Xu R, Jiang H D, Song C Y, et al. Single-shot three-dimensional structure determination of nanocrystals with femtosecond X-ray free-electron laser pulses[J]. Nature Communications, 2014, 5: 4061.
[17] Ekeberg T, Svenda M, Abergel C, et al. Three-dimensional reconstruction of the giant mimivirus particle with an X-ray free-electron laser[J]. Physical Review Letters, 2015, 114(9): 098102.
[18] He S B, Shen X, Wang H, et al. Ghost diffraction without a beamsplitter[J]. Applied Physics Letters, 2010, 96(18): 181108.
[19] Gatti A, Magatti D, Bache M, et al. High-resolution ghost image and ghost diffraction experiments with incoherent pseudo-thermal light[C]. Proceeding of SPIE, 2005, 5893: 58930D.
[20] Cheng J, Han S S. Incoherent coincidence imaging and its applicability in X-ray diffraction[J]. Physical Review Letters, 2004, 92(9): 093903.
[21] Zhang M H, Wei Q, Shen X, et al. Lensless Fourier-transform ghost imaging with classical incoherent light[J]. Physical Review A, 2007, 75(2): 021803.
[22] Yu H, Lu R H, Han S S, et al. Fourier-transform ghost imaging with hard X rays[J]. Physical Review Letters, 2016, 117(11): 113901.
[23] Shapiro J H. Computational ghost imaging[C]. Conference on Lasers and Electro-Optics/International Quantum Electronics Conference, 2009.
[24] Mait J N, Euliss G W, Athale R A. Computational imaging[J]. Advances in Optics and Photonics, 2018, 10(2): 409-483.
[25] Katz O, Bromberg Y, Silberberg Y. Compressive ghost imaging[J]. Applied Physics Letters, 2009, 95(13): 131110.
[26] Zhu R G, Yu H, Lu R H, et al. Spatial multiplexing reconstruction for Fourier-transform ghost imaging via sparsity constraints[J]. Optics Express, 2018, 26(3): 2181-2190.
[27] Liu P J, Zhang H Z, Zhang K, et al. Multi-level wavelet-CNN for image restoration[C]. IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2018.
[28] Lyu M, Wang W, Wang H, et al. Deep-learning-based ghost imaging[J]. Scientific Reports, 2017, 7: 17865.
[29] Sinha A, Lee J, Li S, et al. Lensless computational imaging through deep learning[J]. Optica, 2017, 4(9): 1117.
[30] Zhao X, Yu H, Lu R H, et al. Research on pseudo-thermal source of X-ray Fourier-transform ghost imaging[J]. Acta Optica Sinica, 2017, 37(5): 0511001.
[31] Wang H, Han S S. Coherent ghost imaging based on sparsity constraint without phase-sensitive detection[J]. EPL (Europhysics Letters), 2012, 98(2): 24003.
[32] Tan Z J, Yu H, Lu R H, et al. Non-locally coded Fourier-transform ghost imaging[J]. Optics Express, 2019, 27(3): 2937-2948.
[33] Candès E J, Strohmer T, Voroninski V. PhaseLift: Exact and stable signal recovery from magnitude measurements via convex programming[J]. Communications on Pure and Applied Mathematics, 2013, 66(8): 1241-1274.
[34] Candès E J, Eldar Y C, Strohmer T, et al. Phase retrieval via matrix completion[J]. SIAM Review, 2015, 57(2): 225-251.
[35] Goldstein T, Studer C. PhaseMax: Convex phase retrieval via basis pursuit[J]. IEEE Transactions on Information Theory, 2018, 64(4): 2675-2689.
[36] Wei Z, Chen W, Yin T T, et al. Robust phase retrieval of complex-valued object in phase modulation by hybrid Wirtinger flow method[J]. Optical Engineering, 2017, 56(9): 093106.
[37] Chen Y X, Candès E J. Solving random quadratic systems of equations is nearly as easy as solving linear systems[J]. Communications on Pure and Applied Mathematics, 2017, 70(5): 822-883.
[38] Candès E J, Li X D, Soltanolkotabi M. Phase retrieval via Wirtinger flow: Theory and algorithms[J]. IEEE Transactions on Information Theory, 2015, 61(4): 1985-2007.
[39] Candès E J, Li X D, Soltanolkotabi M. Phase retrieval from coded diffraction patterns[J]. Applied and Computational Harmonic Analysis, 2015, 39(2): 277-299.
[40] Zhang F C, Chen B, Morrison G R, et al. Phase retrieval by coherent modulation imaging[J]. Nature Communications, 2016, 7: 13367.
[41] Chen Q, Yu H, Tan Z J, et al. Simulation research on X-ray Fourier-transform ghost imaging using super-Rayleigh speckle field[J]. Acta Optica Sinica, 2021, 41(19): 1934001.
[43] Yu W K, Li M F, Yao X R, et al. Adaptive compressive ghost imaging based on wavelet trees and sparse representation[J]. Optics Express, 2014, 22(6): 7133-7144.
[44] Gong W L, Zhao C Q, Yu H, et al. Three-dimensional ghost imaging lidar via sparsity constraint[J]. Scientific Reports, 2016, 6: 26133.
[45] Xi M J, Chen H, Yuan Y, et al. Bi-frequency 3D ghost imaging with Haar wavelet transform[J]. Optics Express, 2019, 27(22): 32349.
[46] Huang H Y, Zhou C, Tian T, et al. High-quality compressive ghost imaging[J]. Optics Communications, 2018, 412: 60-65.
[47] Chen Y, Cheng Z D, Fan X, et al. Compressive sensing ghost imaging based on image gradient[J]. Optik, 2019, 182: 1021-1029.
[48] Liu D W, Li L F, Chen H, et al. Complementary normalized compressive ghost imaging with entangled photons[J]. IEEE Photonics Journal, 2018, 10(2): 1-7.
[49] Fienup J R. Phase retrieval algorithms: A comparison[J]. Applied Optics, 1982, 21(15): 2758-2769.
[50] Quan T M, Nguyen-Duc T, Jeong W K. Compressed sensing MRI reconstruction using a generative adversarial network with a cyclic loss[J]. IEEE Transactions on Medical Imaging, 2018, 37(6): 1488-1497.
[51] Horisaki R, Takagi R, Tanida J. Learning-based imaging through scattering media[J]. Optics Express, 2016, 24(13): 13738-13743.
[52] Li S, Deng M, Lee J, et al. Imaging through glass diffusers using densely connected convolutional networks[J]. Optica, 2018, 5(7): 803-813.
[53] Li Y Z, Xue Y J, Tian L. Deep speckle correlation: A deep learning approach toward scalable imaging through scattering media[J]. Optica, 2018, 5(10): 1181-1190.
[54] Ledig C, Theis L, Huszár F, et al. Photo-realistic single image super-resolution using a generative adversarial network[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2017: 105-114.
[55] Dong C, Loy C C, He K, et al. Learning a Deep Convolutional Network for Image Super-Resolution[M]. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Verlag, 2014: 184-199.
[56] Nehme E, Weiss L E, Michaeli T, et al. Deep-STORM: Super-resolution single-molecule microscopy by deep learning[J]. Optica, 2018, 5(4): 458.
[57] Nguyen T, Xue Y J, Li Y Z, et al. Deep learning approach for Fourier ptychography microscopy[J]. Optics Express, 2018, 26(20): 26470-26484.
[58] Zhu R G, Yu H, Tan Z J, et al. Ghost imaging based on Y-net: A dynamic coding and decoding approach[J]. Optics Express, 2020, 28(12): 17556-17569.
[59] Khoshaman A, Vinci W, Denis B, et al. Quantum variational autoencoder[J]. Quantum Science and Technology, 2018, 4(1): 014001.
[60] Cemgil A T, Ghaisas S, Dvijotham K, et al. Autoencoding variational autoencoder[OL]. 2020, arXiv: 2012. 03715.
[61] Pu Y C, Gan Z, Henao R, et al. Variational autoencoder for deep learning of images, labels and captions[OL]. 2016, arXiv: 1609.08976, https://arxiv.org/abs/1609.08976.
[62] Hou X X, Shen L L, Sun K, et al. Deep feature consistent variational autoencoder[C]. IEEE Winter Conference on Applications of Computer Vision, 2017: 1133-1141.
[63] Hu C Y, Zhu R G, Yu H, et al. Correspondence Fourier-transform ghost imaging[J]. Physical Review A, 2021, 103(4): 043717.
[64] Shechtman Y, Sahl S J, Backer A S, et al. Optimal point spread function design for 3D imaging[J]. Physical Review Letters, 2014, 113(13): 133902.
[65] Sengijpta S K. Fundamentals of statistical signal processing: Estimation theory[J]. Technometrics, 1995, 37(4): 465-466.
[66] Schneider R, Mehringer T, Mercurio G, et al. Quantum imaging with incoherently scattered light from a free-electron laser[J]. Nature Physics, 2018, 14(2): 126-129.
[67] Oppel S, Büttner T, Kok P, et al. Superresolving multiphoton interferences with independent light sources[J]. Physical Review Letters, 2012, 109(23): 233603.
[68] Classen A, Waldmann F, Giebel S, et al. Superresolving imaging of arbitrary one-dimensional arrays of thermal light sources using multiphoton interference[J]. Physical Review Letters, 2016, 117(25): 253601.
[69] Thiel C, Bastin T, Martin J, et al. Quantum imaging with incoherent photons[J]. Physical Review Letters, 2007, 99(13): 133603.
[70] Oberthür D. Biological single-particle imaging using XFELs- towards the next resolution revolution[J]. IUCrJ, 2018, 5: 663-666.
[71] Barty A. Single molecule imaging using X-ray free electron lasers[J]. Current Opinion in Structural Biology, 2016, 40: 186-194.
[72] Li Z, Medvedev N, Chapman H N, et al. Radiation-damage-free ghost diffraction with atomic resolution[OL]. 2017, arXiv: 1511.05068, https://arxiv.org/abs/1511.05068.
[73] Tamasaku K, Sawada K, Nishibori E, et al. Visualizing the local optical response to extreme-ultraviolet radiation with a resolution of λ/380[J]. Nature Physics, 2011, 7(9): 705-708.
[74] Glover T E, Fritz D M, Cammarata M, et al. X-ray and optical wave mixing[J]. Nature, 2012, 488(7413): 603-608.
[75] Shwartz S, Coffee R N, Feldkamp J M, et al. X-ray parametric down-conversion in the Langevin regime[J]. Physical Review Letters, 2012, 109(1): 013602.
[76] Vinu R V, Chen Z Y, Singh R K, et al. Ghost diffraction holographic microscopy[J]. Optica, 2020, 7(12): 1697.
[77] Lee K, Park Y. Exploiting the speckle-correlation scattering matrix for a compact reference-free holographic image sensor[J]. Nature Communications, 2016, 7: 13359.
[78] Naik D N, Singh R K, Ezawa T, et al. Photon correlation holography[J]. Optics Express, 2011, 19(2): 1408.
[79] Zhang Z B, Ma X, Zhong J G. Single-pixel imaging by means of Fourier spectrum acquisition[J]. Nature Communications, 2015, 6(1): 6225.
[80] Mahdi Khamoushi S M, Nosrati Y, Tavassoli S H. Sinusoidal ghost imaging[J]. Optics Letters, 2015, 40(15): 3452-3455.
[81] Lane T J, Ratner D. What are the advantages of ghost imaging? Multiplexing for X-ray and electron imaging[J]. Optics Express, 2020, 28(5): 5898-5918.
