• Photonics Research
  • Vol. 12, Issue 4, 804 (2024)
Xiaoyu Nie1、2, Haotian Song2, Wenhan Ren1、2, Zhedong Zhang3、5, Tao Peng1、*, and Marlan O. Scully1、4、6
Author Affiliations
  • 1Institute for Quantum Science and Engineering, Texas A&M University, College Station, Texas 77843, USA
  • 2School of Physics, Xi’an Jiaotong University, Xi’an 710049, China
  • 3Department of Physics, City University of Hong Kong, Hong Kong, China
  • 4Baylor University, Waco, Texas 76706, USA
  • 5e-mail: zzhan26@cityu.edu.hk
  • 6e-mail: scully@tamu.edu
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    DOI: 10.1364/PRJ.504327 Cite this Article Set citation alerts
    Xiaoyu Nie, Haotian Song, Wenhan Ren, Zhedong Zhang, Tao Peng, Marlan O. Scully. Deep correlated speckles: suppressing correlation fluctuation and optical diffraction[J]. Photonics Research, 2024, 12(4): 804 Copy Citation Text show less
    References

    [1] D. J. Pine, D. A. Weitz, P. M. Chaikin. Diffusing wave spectroscopy. Phys. Rev. Lett., 60, 1134-1137(1988).

    [2] S.-W. Li, F. Li, T. Peng. Photon statistics of quantum light on scattering from rotating ground glass. Phys. Rev. A, 101, 063806(2020).

    [3] J. W. Goodman. Statistical properties of laser speckle patterns. Laser Speckle and Related Phenomena, 9-75(1975).

    [4] I. Zanette, T. Zhou, A. Burvall. Speckle-based X-ray phase-contrast and dark-field imaging with a laboratory source. Phys. Rev. Lett., 112, 253903(2014).

    [5] J. Wang, A. Z. Genack. Transport through modes in random media. Nature, 471, 345-348(2011).

    [6] L. Olivieri, J. S. T. Gongora, L. Peters. Hyperspectral terahertz microscopy via nonlinear ghost imaging. Optica, 7, 186-191(2020).

    [7] G. C. Valley, G. A. Sefler, T. J. Shaw. Multimode waveguide speckle patterns for compressive sensing. Opt. Lett., 41, 2529-2532(2016).

    [8] B. Redding, S. M. Popoff, H. Cao. All-fiber spectrometer based on speckle pattern reconstruction. Opt. Express, 21, 6584-6600(2013).

    [9] T. Strudley, T. Zehender, C. Blejean. Mesoscopic light transport by very strong collective multiple scattering in nanowire mats. Nat. Photonics, 7, 413-418(2013).

    [10] B. Redding, S. F. Liew, R. Sarma. Compact spectrometer based on a disordered photonic chip. Nat. Photonics, 7, 746-751(2013).

    [11] C. Ventalon, J. Mertz. Dynamic speckle illumination microscopy with translated versus randomized speckle patterns. Opt. Express, 14, 7198-7209(2006).

    [12] J. Mertz. Optical sectioning microscopy with planar or structured illumination. Nat. Methods, 8, 811-819(2011).

    [13] E. Mudry, K. Belkebir, J. Girard. Structured illumination microscopy using unknown speckle patterns. Nat. Photonics, 6, 312-315(2012).

    [14] S. Nakadate, H. Saito. Fringe scanning speckle-pattern interferometry. Appl. Opt., 24, 2172-2180(1985).

    [15] H. Yilmaz, E. G. van Putten, J. Bertolotti. Speckle correlation resolution enhancement of wide-field fluorescence imaging. Optica, 2, 424-429(2015).

    [16] M. Pascucci, G. Tessier, V. Emiliani. Superresolution imaging of optical vortices in a speckle pattern. Phys. Rev. Lett., 116, 093904(2016).

    [17] V. Doya, O. Legrand, F. Mortessagne. Speckle statistics in a chaotic multimode fiber. Phys. Rev. E, 65, 056223(2002).

    [18] J. Wang, S. K. Nadkarni. The influence of optical fiber bundle parameters on the transmission of laser speckle patterns. Opt. Express, 22, 8908-8918(2014).

    [19] W. McGehee, S. Kondov, W. Xu. Three-dimensional Anderson localization in variable scale disorder. Phys. Rev. Lett., 111, 145303(2013).

    [20] D. Delande, G. Orso. Mobility edge for cold atoms in laser speckle potentials. Phys. Rev. Lett., 113, 060601(2014).

    [21] E. Fratini, S. Pilati. Anderson localization of matter waves in quantum-chaos theory. Phys. Rev. A, 91, 061601(2015).

    [22] R. Liu, B. Qing, S. Zhao. Generation of non-Rayleigh nondiffracting speckles. Phys. Rev. Lett., 127, 180601(2021).

    [23] S. Han, N. Bender, H. Cao. Tailoring 3D speckle statistics. Phys. Rev. Lett., 130, 093802(2023).

    [24] M. Saxena, G. Eluru, S. S. Gorthi. Structured illumination microscopy. Adv. Opt. Photonics, 7, 241-275(2015).

    [25] N. Bender, M. Sun, H. Ylmaz. Circumventing the optical diffraction limit with customized speckles. Optica, 8, 122-129(2021).

    [26] Z. Li, X. Nie, F. Yang. Sub-Rayleigh second-order correlation imaging using spatially distributive colored noise speckle patterns. Opt. Express, 29, 19621-19630(2021).

    [27] R. S. Bennink, S. J. Bentley, R. W. Boyd. “two-photon” coincidence imaging with a classical source. Phys. Rev. Lett., 89, 113601(2002).

    [28] X.-H. Chen, Q. Liu, K.-H. Luo. Lensless ghost imaging with true thermal light. Opt. Lett., 34, 695-697(2009).

    [29] A. Valencia, G. Scarcelli, M. D’Angelo. Two-photon imaging with thermal light. Phys. Rev. Lett., 94, 063601(2005).

    [30] Y. Bromberg, H. Cao. Generating non-Rayleigh speckles with tailored intensity statistics. Phys. Rev. Lett., 112, 213904(2014).

    [31] H. E. Kondakci, A. Szameit, A. F. Abouraddy. Sub-thermal to super-thermal light statistics from a disordered lattice via deterministic control of excitation symmetry. Optica, 3, 477-482(2016).

    [32] B. Luo, P. Yin, L. Yin. Orthonormalization method in ghost imaging. Opt. Express, 26, 23093-23106(2018).

    [33] X. Nie, F. Yang, X. Liu. Noise-robust computational ghost imaging with pink noise speckle patterns. Phys. Rev. A, 104, 013513(2021).

    [34] X. Nie, X. Zhao, T. Peng. Sub-Nyquist computational ghost imaging with orthonormal spectrum-encoded speckle patterns. Phys. Rev. A, 105, 043525(2022).

    [35] K. Fukushima. Neocognitron: a self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biol. Cybern., 36, 193-202(1980).

    [36] A. Krizhevsky, I. Sutskever, G. E. Hinton. Imagenet classification with deep convolutional neural networks. Commun. ACM, 60, 84-90(2017).

    [37] J. H. Shapiro. Computational ghost imaging. Phys. Rev. A, 78, 061802(2008).

    [38] Y. Bromberg, O. Katz, Y. Silberberg. Ghost imaging with a single detector. Phys. Rev. A, 79, 053840(2009).

    [39] V. Nair, G. E. Hinton. Rectified linear units improve restricted Boltzmann machines. International Conference on Machine Learning, 807-814(2010).

    [40] S. Ioffe, C. Szegedy. Batch normalization: Accelerating deep network training by reducing internal covariate shift. International Conference on Machine Learning, 448-456(2015).

    [41] K. He, X. Zhang, S. Ren. Identity mappings in deep residual networks. European Conference on Computer Vision, 630-645(2016).

    [42] X. Zhu, M. Bain. B-CNN: branch convolutional neural network for hierarchical classification. arXiv(2017).

    [43] T. B. Pittman, Y. Shih, D. Strekalov. Optical imaging by means of two-photon quantum entanglement. Phys. Rev. A, 52, R3429-R3432(1995).

    [44] L. Wang, S. Zhao. Fast reconstructed and high-quality ghost imaging with fast Walsh–Hadamard transform. Photonics Res., 4, 240-244(2016).

    [45] Z. Zhang, X. Ma, J. Zhong. Single-pixel imaging by means of Fourier spectrum acquisition. Nat. Commun., 6, 6225(2015).

    [46] Z. Zhang, X. Wang, G. Zheng. Hadamard single-pixel imaging versus Fourier single-pixel imaging. Opt. Express, 25, 19619-19639(2017).

    [47] O. Katz, Y. Bromberg, Y. Silberberg. Compressive ghost imaging. Appl. Phys. Lett., 95, 131110(2009).

    [48] V. Katkovnik, J. Astola. Compressive sensing computational ghost imaging. J. Opt. Soc. Am. A, 29, 1556-1567(2012).

    [49] M. Lyu, W. Wang, H. Wang. Deep-learning-based ghost imaging. Sci. Rep., 7, 17865(2017).

    [50] T. Shimobaba, Y. Endo, T. Nishitsuji. Computational ghost imaging using deep learning. Opt. Commun., 413, 147-151(2018).

    [51] G. Barbastathis, A. Ozcan, G. Situ. On the use of deep learning for computational imaging. Optica, 6, 921-943(2019).

    [52] F. Wang, H. Wang, H. Wang. Learning from simulation: an end-to-end deep-learning approach for computational ghost imaging. Opt. Express, 27, 25560-25572(2019).

    [53] H. Wu, R. Wang, G. Zhao. Sub-Nyquist computational ghost imaging with deep learning. Opt. Express, 28, 3846-3853(2020).

    [54] D. Lim, K. K. Chu, J. Mertz. Wide-field fluorescence sectioning with hybrid speckle and uniform-illumination microscopy. Opt. Lett., 33, 1819-1821(2008).

    [55] A. Vigoren, J. M. Zavislan. Optical sectioning enhancement using higher-order moment signals in random speckle-structured illumination microscopy. J. Opt. Soc. Am. A, 35, 474-479(2018).

    [56] K. Kuplicki, K. W. C. Chan. High-order ghost imaging using non-Rayleigh speckle sources. Opt. Express, 24, 26766-26776(2016).

    [57] P. Liu. Label-free storm principle realized by super-Rayleigh speckle in photoacoustic imaging. Opt. Lett., 44, 4642-4645(2019).

    [58] M. Pascucci, S. Ganesan, A. Tripathi. Compressive three-dimensional super-resolution microscopy with speckle-saturated fluorescence excitation. Nat. Commun., 10, 1327(2019).

    [59] N. Bender, H. Ylmaz, Y. Bromberg. Customizing speckle intensity statistics. Optica, 5, 595-600(2018).

    [60] N. Bender, H. Ylmaz, Y. Bromberg. Creating and controlling complex light. APL Photonics, 4, 110806(2019).

    [61] J. Durnin. Exact solutions for nondiffracting beams. I. The scalar theory. J. Opt. Soc. Am. A, 4, 651-654(1987).

    [62] A. Vasara, J. Turunen, A. T. Friberg. Realization of general nondiffracting beams with computer-generated holograms. J. Opt. Soc. Am. A, 6, 1748-1754(1989).

    [63] L. Vicari. Truncation of non diffracting beams. Opt. Commun., 70, 263-266(1989).

    [64] J. G. Neto, E. J. Fonseca, A. J. Jesus-Silva. Exact solutions for non-Rayleigh nondiffracting speckles. Phys. Rev. A, 106, 053519(2022).

    [65] D. G. Voelz. Computational Fourier Optics: A MATLAB Tutorial, 534(2011).

    [66] O. Ronneberger, P. Fischer, T. Brox. U-net: convolutional networks for biomedical image segmentation. International Conference on Medical Image Computing and Computer-Assisted Intervention, 234-241(2015).

    [67] J. T. Connor, R. D. Martin, L. E. Atlas. Recurrent neural networks and robust time series prediction. IEEE Trans. Neural Netw., 5, 240-254(1994).

    Xiaoyu Nie, Haotian Song, Wenhan Ren, Zhedong Zhang, Tao Peng, Marlan O. Scully. Deep correlated speckles: suppressing correlation fluctuation and optical diffraction[J]. Photonics Research, 2024, 12(4): 804
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