Advanced Photonics, 2019, 1 (3): 036002, Published Online: Jun. 19, 2019   

Learning-based lensless imaging through optically thick scattering media Download: 1087次

Author Affiliations
1 Chinese Academy of Sciences, Shanghai Institute of Optics and Fine Mechanics, Shanghai, China
2 University of Chinese Academy of Sciences, Center for Materials Science and Optoelectronics Engineering, Beijing, China
Copy Citation Text

Meng Lyu, Hao Wang, Guowei Li, Shanshan Zheng, Guohai Situ. Learning-based lensless imaging through optically thick scattering media[J]. Advanced Photonics, 2019, 1(3): 036002.

References

[1] J. W.Goodman, Introduction to Fourier Optics, Roberts & Co., Greenwood Village, Colorado (2005).

[2] V. Ntziachristos. Going deeper than microscopy: the optical imaging frontier in biology. Nat. Methods, 2010, 7: 603-614.

[3] A.Ishimaru, Wave Propagation and Scattering in Random Media, Academic Press, New York (1978).

[4] J. Beckers. Adaptive optics for astronomy: principles, performance, and applications. Annu. Rev. Astron. Astrophys., 1993, 31: 13-62.

[5] S. Rotter, S. Gigan. Light fields in complex media: mesoscopic scattering meets wave control. Rev. Mod. Phys., 2017, 89: 015005.

[6] J. W. Goodman, et al.. Wavefront reconstruction imaging through random media. Appl. Phys. Lett., 1966, 8: 311-313.

[7] Z. Yaqoob, et al.. Optical phase conjugation for turbidity suppression in biological samples. Nat. Photonics, 2008, 2: 110-115.

[8] Y. Zhang, et al.. Application of short-coherence lensless Fourier-transform digital holography in imaging through diffusive medium. Opt. Commun., 2013, 286: 56-59.

[9] A. K. Singh, et al.. Exploiting scattering media for exploring 3D objects. Light Sci. Appl., 2017, 6: e16219.

[10] I. M. Vellekoop, A. Mosk. Focusing coherent light through opaque strongly scattering media. Opt. Lett., 2007, 32: 2309-2311.

[11] A. P. Mosk, et al.. Controlling waves in space and time for imaging and focusing in complex media. Nat. Photonics, 2012, 6: 283-292.

[12] O. Katz, E. Small, Y. Silberberg. Looking around corners and through thin turbid layers in real time with scattered incoherent light. Nat. Photonics, 2012, 6: 549-553.

[13] S. M. Popoff, et al.. Measuring the transmission matrix in optics: an approach to the study and control of light propagation in disordered media. Phys. Rev. Lett., 2010, 104: 100601.

[14] S. Popoff, et al.. Image transmission through an opaque material. Nat. Commun., 2010, 1: 81.

[15] M. R. I. Freund, S. Feng. Memory effects in propagation of optical waves through disordered media. Phys. Rev. Lett., 1998, 61: 2328-2331.

[16] J. Bertolotti, et al.. Non-invasive imaging through opaque scattering layers. Nature, 2012, 491: 232-234.

[17] O. Katz, et al.. Non-invasive single-shot imaging through scattering layers and around corners via speckle correlations. Nat. Photonics, 2014, 8: 784-790.

[18] G. Li, et al.. Cyphertext-only attack on the double random-phase encryption: experimental demonstration. Opt. Express, 2017, 25: 8690-8697.

[19] W. Yang, G. Li, G. Situ. Imaging through scattering media with the auxiliary of a known reference object. Sci. Rep., 2018, 8: 9614.

[20] S. Schott, et al.. Characterization of the angular memory effect of scattered light in biological tissues. Opt. Express, 2015, 23: 13505-13516.

[21] G. Li, et al.. Image transmission through scattering media using ptychographic iterative engine. Appl. Sci., 2019, 9: 849.

[22] I.Goodfellow, Y.Bengio and A.Courville, Deep Learning, MIT Press, Cambridge (2016).

[23] Y. LeCun, Y. Bengio, G. Hinton. Deep learning. Nature, 2015, 521: 436-444.

[24] R. Horisaki, R. Takagi, J. Tanida. Learning-based imaging through scattering media. Opt. Express, 2016, 24: 13738-13743.

[25] M.Lyuet al., “Exploit imaging through opaque wall via deep learning,” arXiv:1708.07881 (2017).

[26] Y. Rivenson, et al.. Phase recovery and holographic image reconstruction using deep learning in neural networks. Light Sci. Appl., 2018, 7: 17141.

[27] A. Sinha, et al.. Lensless computational imaging through deep learning. Optica, 2017, 4: 1117-1125.

[28] K. H. Jin, M. T. McCann. Deep convolutional neural network for inverse problems in imaging. IEEE Trans. Image Process., 2017, 26: 4509-4522.

[29] P. Caramazza, et al.. Neural network identification of people hidden from view with a single-pixel, single-photon detector. Sci. Rep., 2018, 8: 11945.

[30] S. Li, et al.. Imaging through glass diffusers using densely connected convolutional networks. Optica, 2018, 5: 803-813.

[31] Y. Li, Y. Xue, L. Tian. Deep speckle correlation: a deep learning approach toward scalable imaging through scattering media. Optica, 2018, 5: 1181-1190.

[32] G. Barbastathis, A. Ozcan, G. Situ. On the use of deep learning for computational imaging. Optica, 2019.

[33] M. Lyu, et al.. Deep-learning-based ghost imaging. Sci. Rep., 2017, 7: 17865.

[34] L. Deng. The MNIST database of handwritten digit images for machine learning research [best of the web]. IEEE Signal Process. Mag., 2012, 29: 141-142.

[35] I. Freund. Looking through walls and around corners. Phys. A, 1990, 168: 49-65.

[36] I. Freund. Image reconstruction through multiple scattering media. Opt. Commun., 1991, 86: 216-227.

[37] K. Hornik, M. Stinchcombe, H. White. Multilayer feedforward networks are universal approximators. Neural Netw., 1989, 2: 359-366.

[38] G. Cybenko. Approximation by superpositions of a sigmoidal function. Math. Control Signals Syst., 1989, 2: 303-314.

[39] V.Nair and G. E.Hinton, “Rectified linear units improve restricted Boltzmann machines,” in Proc. of the 27th Int. Conf. on Machine Learning, pp. 807814 (2010).

[40] K.Diederik and J.Ba, “Adam: a method for stochastic optimization,” arXiv:1412:6980 (2014).

[41] N. Srivastava, et al.. Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res., 2014, 15: 1929-1958.

[42] C. M. Michail, et al.. Figure of image quality and information capacity in digital mammography. BioMed Res. Int., 2015, 2014: 297-308.

[43] J. W.Goodman, Statistical Optics, 2nd Ed., Wiley and Sons, Hoboken, New Jersey (2015).

[44] R. Michels, F. Foschum, A. Kienle. Optical properties of fat emulsions. Opt. Express, 2008, 16: 5907-5925.

Meng Lyu, Hao Wang, Guowei Li, Shanshan Zheng, Guohai Situ. Learning-based lensless imaging through optically thick scattering media[J]. Advanced Photonics, 2019, 1(3): 036002.

本文已被 18 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!