[1] Rust M J, Bates M, Zhuang X W. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM)[J]. Nature Methods, 3, 793(2006). http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=22456353&site=ehost-live

[2] Hess S T. Girirajan T P K, Mason M D. Ultra-high resolution imaging by fluorescence photoactivation localization microscopy[J]. Biophysical Journal, 91, 4258-4272(2006).

[3] Zhu L, Zhang W, Elnatan D et al. Faster STORM using compressed sensing[J]. Nature Methods, 9, 721-723(2012).

[4] Nehme E, Weiss L E, Michaeli T et al. Deep-STORM: super-resolution single-molecule microscopy by deep learning[J]. Optica, 5, 458(2018).

[5] Pan W H, Chen B L, Zhang J G et al. Compressed sensing STORM super-resolution image reconstruction based on noise correction-principal component analysis preprocessing algorithm[J]. Chinese Journal of Lasers, 47, 0207024(2020).

[6] Dempsey G T, Vaughan J C, Chen K H et al. Evaluation of fluorophores for optimal performance in localization-based super-resolution imaging[J]. Nature Methods, 8, 1027(2011).

[7] Zuo C, Feng S J, Zhang X Y et al. Deep learning based computational imaging: status, challenges, and future[J]. Acta Optica Sinica, 40, 0111003(2020).

[8] Wang H, Rivenson Y, Jin Y et al. Deep learning enables cross-modality super-resolution in fluorescence microscopy[J]. Nature Methods, 16, 103(2019).

[9] Li S M, Lei G Q, Fan R. Depth map super-resolution reconstruction based on convolutional neural networks[J]. Acta Optica Sinica, 37, 1210002(2017).

[10] Zhu Y, Shi J H, Wu X Y et al. Photon-limited non-imaging object detection and classification based on single-pixel imaging system[J]. Applied Physics B, 126, 21(2020).

[11] Zhang K, Zuo W M, Chen Y J et al. Beyond a Gaussian denoiser: residual learning of deep CNN for image denoising[J]. IEEE Transactions on Image Processing, 26, 3142-3155(2017).

[12] Zhou W J, Zou S, He D K et al. Speckle noise reduction of holograms based on spectral convolutional neural network[J]. Acta Optica Sinica, 40, 0509001(2020).

[13] Hirsch M, Wareham R J. Martin-Fernandez M L, et al. A Stochastic model for electron multiplication charge-coupled devices-from theory to practice[J]. Plos One, 8, e53671(2013).

[14] Plakhotnik T, Chennu A, Zvyagin A V. Statistics of single-electron signals in electron-multiplying charge-coupled devices[J]. IEEE Transactions on Electron Devices, 53, 618-622(2006).

[15] Huang G, Liu Z. Laurens V D M, et al. Densely connected convolutional networks[C]∥2017 IEEE conference on Computer Vision and Pattern Recognition. July 21-26, 2017. Honolulu, Hi, USA., 17355312(2017).

[16] Sun L, Shi J H, Wu X Y et al. Photon-limited imaging through scattering medium based on deep learning[J]. Optics Express, 27, 33120-33134(2019).

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

[18] Li S, Deng M, Lee J et al. Imaging through glass diffusers using densely connected convolutional networks[J]. Optica, 5, 803-813(2018).

[19] Salakhutdinov R, Mnih A, Hinton G. Restricted Boltzmann machines for collaborative filtering[C]∥Proceedings of the 24th international conference on Machine learning-ICML'07. June 20-24, 2007. Corvalis, Oregon., 791-798(2007).

[20] Hinton G E, Srivastava N, Krizhevsky A et al. arXiv:1207[2020-04-28]. 0580 https:∥arxiv., org/abs/1207, 0580(2012).

[21] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition[J]. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 770-778(2016).

[22] Huang F, Schwartz S L, Byars J M et al. Simultaneous multiple-emitter fitting for single molecule super-resolution imaging[J]. Biomedical Optics Express, 2, 1377-1393(2011).

[23] Kingma D P. arXiv:1412[2020-04-28]. 6980 https:∥arxiv., org/abs/1412, 6980(2014).

[24] Abadi M, Agarwal A, Barham P et al. arXiv:1603[2020-04-28]. 04467 https:∥arxiv., org/abs/1603, 04467(2016).

[25] Hou Y K, Zhao C X, Yang D Y et al. Comments on “image denoising by sparse 3-D transform-domain collaborative filtering”[J]. IEEE Transactions on Image Processing, 20, 268-270(2011).

[26] Holden S J, Uphoff S, Kapanidis A N. DAOSTORM: an algorithm for high-density super-resolution microscopy[J]. Nature Methods, 8, 279-280(2011).