• Acta Photonica Sinica
  • Vol. 49, Issue 7, 709001 (2020)
Hang LIU, Yong-liang XIAO*, Jun-long TIAN, Hong-xing LI, and Jian-xin ZHONG
Author Affiliations
  • School of Physics and Optoelectronic Engineering, Xiangtan University, Xiangtan, Hunan 411105, China
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    DOI: 10.3788/gzxb20204907.0709001 Cite this Article
    Hang LIU, Yong-liang XIAO, Jun-long TIAN, Hong-xing LI, Jian-xin ZHONG. Nonlinear Reconstruction for Off-axis Fresnel Digital Holography with Deep Learning[J]. Acta Photonica Sinica, 2020, 49(7): 709001 Copy Citation Text show less
    References

    [3] B KEMPER, G BALLY. Digital holographic microscopy for live cell applications and technical inspection. Applied Optics, 47, 52-61(2008).

    [4] X TAN, O MATOBA, T SHIMURA. Secure optical storage that uses fully phase encryption. Applied Optics, 39, 6689-6694(2000).

    [5] X F MENG, L Z CAI, X F XU. Two-step phase-shifting interferometry and its application in image encryption. Optics Letters, 31, 1414-1416(2006).

    [7] E CUCHE, P MARQUET, C DEPEURSINGE. Spatial filtering for zero-order and twin-image elimination in digital off-axis holography. Applied Optics, 39, 4070-4075(2000).

    [8] Y TAKAKI, H KAWAI, H OHZU. Hybrid holographic microscopy free of conjugate and zero-order images. Applied Optics, 38, 4990-4996(1999).

    [9] Y LECUN, Y BENGIO, G HINTON. Deep learning. Nature, 521, 436-444(2015).

    [10] Y RIVENSON, Y WU, A OZCAN. Deep learning in holography and coherent imaging. Light:Science & Applications, 8, 196(2019).

    [11] Y LI, Y XUE, L TIAN. Deep speckle correlation:a deep learning approach toward scalable imaging through scattering media. Optica, 5, 1181-1190(2018).

    [12] F WANG, H WANG, H WANG. Learning from simulation:An end-to-end deep-learning approach for computational ghost imaging. Optics Express, 27, 25560-25572(2019).

    [13] A SINHA, G BARBARBSTATHIS, J LEE. Lensless computational imaging through deep learning. Optica, 4, 1117-1125(2017).

    [14] Y RIVENSON, Y ZHANG, H GUNAYDM. Phase recovery and holographic image reconstruction using deep learning in neural networks. Light Science & Applications, 7, 17141-17149(2018).

    [15] Y WU, Y RIVENSON, Y ZHANG. Extended depth-of-field in holographic imaging using deep-learning-based autofocusing and phase recovery. Optica, 5, 704-710(2018).

    [16] H WANG, M LYU, G SITU. eHoloNet:a learning-based end-to-end approach for in-line digital holographic reconstruction. Optics Express, 26, 22603-22614(2018).

    [17] G ZHANG, D WANG, T GUAN. Fast phase retrieval in off-axis digital holographic microscopy through deep learning. Optics Express, 26, 19388-19405(2018).

    [18] K WANG, J DOU, Q KEMAO. Y-Net:a one-to-two deep learning framework for digital holographic reconstruction. Optics Letters, 44, 4765-4768(2019).

    [19] Z REN, Z XU, YLAM E. End-to-end deep learning framework for digital holographic reconstruction. Advanced Photonics, 1, 016004(2019).

    [20] HE K, ZHANG X, REN S, et al. Deep Residual Learning f Image Recognition[C] Proceedings of IEEE Conference on Computer Vision Pattern Recognition (CVPR), 2016: 770778.

    [21] RONNEBERGER O, FISHER P, BROX T, U: convolutional wks f biomedical image segmentation[C]. International Conference on Medical Image Computing ComputerAssisted Intervention, 2015: 234241.

    [22] J W GOODMAN. Introduction to Fourier Optics(1995).

    [23] M T MCCANN, K H JIN, M UNSER. Convolutional neural networks for inverse problems in imaging:a review. IEEE Signal Processing Magazine, 34, 85-95(2017).

    [24] IOFFE S, SZEGEDY C. Batch nmalization: accelerating deep wk training by reducing internal covariate shift[C] Proceedings of the 32nd International Conference on Machine Learning (ICML), 2015: 448456.

    [25] NAIR V, HINTON G E. Rectified Linear Units Improve Restricted Boltzmann Machines[C]. Proceedings of the 27th International Conference on Machine Learning (ICML), 2010: 807814.

    [26] X GLOROT, Y BENGIO. Understanding the difficulty of training deep feedforward neural networks. Journal of Machine Learning Research (JMLR), 9, 249-256(2010).

    [27] KINGMA D P, BAI J. Adam: a method f stochastic optimization[C]. Proceedings of International Conference on Learning Representations (ICLR), 2015.

    [28] D E RUMELHART, G E HINTON, R J WILLIAMS. Learning representations by back-propagating errors. Nature, 323, 533-536(1986).

    [30] Z WANG, A C BOVIK, H R SHEIKH. Image quality assessment:from error visibility to structural similarity. IEEE Transactions on Image Processing, 13, 600-612(2004).

    Hang LIU, Yong-liang XIAO, Jun-long TIAN, Hong-xing LI, Jian-xin ZHONG. Nonlinear Reconstruction for Off-axis Fresnel Digital Holography with Deep Learning[J]. Acta Photonica Sinica, 2020, 49(7): 709001
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