[1] Khater I M, Nabi I R, Hamarneh G. A review of super-resolution single-molecule localization microscopy cluster analysis and quantification methods [J]. Patterns, 2020, 1(3): 1-20. doi:  10.1016/j.patter.2020.100038
[2] Sun Yujie, Chen Xuanze. Nobel Prize in Chemistry 2014: Uper-resolved fluorescence microscopy [J]. University Chemistry, 2015, 30(1): 1-9. (in Chinese) doi:  10.3866/PKU.DXHX20150101
[3] Hess S T, Girirajan T, Mason M D. Ultra-high resolution imaging by fluorescence photoactivation localization microscopy [J]. Biophysical Journal, 2006, 91(11): 4258-4272. doi:  10.1529/biophysj.106.091116
[4] Rust M J, Bates M, Zhuang X. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM) [J]. Nature Methods, 2006, 3(10): 793-796. doi:  10.1038/nmeth929
[5] Fölling J, Bossi M, Bock H, et al. Fluorescence nanoscopy by ground-state depletion and single-molecule return [J]. Nature Methods, 2008, 5(11): 943-945. doi:  10.1038/nmeth.1257
[6] You Sihai, Wang Hongli, Feng Lei, et al. Pulsar TOA estimation based on wavelet transform and compressed sensing [J]. Infrared and Laser Engineering, 2020, 49(2): 0226001. (in Chinese) doi:  10.3788/IRLA202049.0226001
[7] Wu Jianbo, Lu Zhengwu, Guan Yurong, et al. SAR target recognition using feature fusion by 2 D compressive sensing with multiple random projection matrices [J]. Infrared and Laser Engineering, 2021, 50(6): 20200531. (in Chinese) doi:  10.3788/IRLA20200531
[8] Zhu L, Zhang W, Elnatan D, et al. Faster STORM using compressed sensing [J]. Nature Methods, 2012, 9(7): 721-723. doi:  10.1038/nmeth.1978
[9] Min J, Vonesch C, Kirshner H, et al. FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data [J]. Scientific Reports, 2014, 4: 4577. doi:  10.1038/srep04577
[10] Nehme E, Weiss L E, Michaeli T, et al. Deep-STORM: Super-resolution single-molecule microscopy by deep learning [J]. Optica, 2018, 5(4): 458-464. doi:  10.1364/OPTICA.5.000458
[11] Wu J, Li S, Zhang S, et al. Fast analysis method for stochastic optical reconstruction microscopy using multiple measurement vector model sparse Bayesian learning [J]. Optics Letters, 2018, 43(16): 3977. doi:  10.1364/OL.43.003977
[12] Quan Tingwei, Zeng Shaoqun, Lv Xiaohua. Comparison of algorithms for localization of single fluorescent molecule in super resolution imaging [J]. Chinese Journal of Lasers, 2010, 37(11): 2714-2718. (in Chinese) doi:  10.3788/CJL20103711.2714
[13] Zhang Hua, Cao Liangcai, Jin Guofan, et al. Progress on lensless digital holography imaging based on compressive sensing holographic algorithm [J]. Laser & Optoelectronics Progress, 2020, 667(8): 9-19. (in Chinese)
[14] Ke Jun, Zhang Linxia, Zhou Qun. Applications of compressive sensing in optical imaging [J]. Acta Optica Sinica, 2020, 40(1): 0111006. (in Chinese) doi:  10.3788/AOS202040.011006
[15] Min J, Jang J, Keum D, et al. Fluorescent microscopy beyond diffraction limits using speckle illumination and joint support recovery [J]. Scientific Reports, 2013, 3(6): 2075. doi:  10.1038/srep02075
[16] Babcock H, Sigal Y M, Zhuang X. A high-density 3 D localization algorithm for stochastic optical reconstruction microscopy [J]. Optical Nanoscopy, 2012, 1(1): 1-10. doi:  10.1186/2192-2853-1-6
[17] Biomedical Imaging Group, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne. Super-resolution microscopy metrics [EB/OL]. [2021-09-25]https://srm.epfl.ch/Metrics.