[1] Guarnieri M. The television: from mechanics to electronics[J]. IEEE Industrial Electronics Magazine, 4, 43-45(2010).

[2] Ben-Yosef N, Sirat G. Real-time spatial filtering utilizing the piezoelectric-elasto-optic effect[J]. Optica Acta: International Journal of Optics, 29, 419-423(1982).

[3] Sen P, Chen B, Garg G et al. Dual photography[J]. ACM Transactions on Graphics, 24, 745-755(2005).

[4] Donoho D L. Compressed sensing[J]. IEEE Transactions on Information Theory, 52, 1289-1306(2006).

[5] Elad M. Optimized projections for compressed sensing[J]. IEEE Transactions on Signal Processing, 55, 5695-5702(2007).

[6] Candès E, Romberg J. Sparsity and incoherence in compressive sampling[J]. Inverse Problems, 23, 969-985(2007).

[7] Duarte M F, Davenport M A, Takhar D et al. Single-pixel imaging via compressive sampling[J]. IEEE Signal Processing Magazine, 25, 83-91(2008).

[8] Pittman T B, Shih Y H, Strekalov D V et al. Optical imaging by means of two-photon quantum entanglement[J]. Physical Review A, 52, R3429-R3432(1995).

[9] Bennink R S, Bentley S J, Boyd R W. Two-photon coincidence imaging with a classical source[J]. Physical Review Letters, 89, 113601(2002).

[10] Shapiro J H. Computational ghost imaging[J]. Physical Review A, 78, 061802(2008).

[11] Gibson G M, Johnson S D, Padgett M J. Single-pixel imaging 12 years on: a review[J]. Optics Express, 28, 28190-28208(2020).

[12] Li M F, Yuan Z H, Liu Y X et al. Photon counting computational ghost imaging[J]. Laser & Optoelectronics Progress, 58, 1011026(2021).

[13] Wu Y B, Yang Z H, Tang Z L. Experimental study on anti-disturbance ability of underwater ghost imaging[J]. Laser & Optoelectronics Progress, 58, 0611002(2021).

[14] Greenberg J, Krishnamurthy K, Brady D. Compressive single-pixel snapshot X-ray diffraction imaging[J]. Optics Letters, 39, 111-114(2014).

[15] Yu H, Lu R H, Han S S et al. Fourier-transform ghost imaging with hard X rays[J]. Physical Review Letters, 117, 113901(2016).

[16] Hoshi I, Shimobaba T, Kakue T et al. Single-pixel imaging using a recurrent neural network combined with convolutional layers[J]. Optics Express, 28, 34069-34078(2020).

[17] Edgar M P, Gibson G M, Bowman R W et al. Simultaneous real-time visible and infrared video with single-pixel detectors[J]. Scientific Reports, 5, 10669(2015).

[18] Chan W L, Charan K, Takhar D et al. A single-pixel terahertz imaging system based on compressed sensing[J]. Applied Physics Letters, 93, 121105(2008).

[19] Hornett S M, Stantchev R I, Vardaki M Z et al. Subwavelength terahertz imaging of graphene photoconductivity[J]. Nano Letters, 16, 7019-7024(2016).

[20] Radwell N, Johnson S D, Edgar M P et al. Deep learning optimized single-pixel LiDAR[J]. Applied Physics Letters, 115, 231101(2019).

[21] Sun B, Edgar M P, Bowman R et al. 3D computational imaging with single-pixel detectors[J]. Science, 340, 844-847(2013).

[22] Xi M J, Chen H, Yuan Y et al. Bi-frequency 3D ghost imaging with Haar wavelet transform[J]. Optics Express, 27, 32349-32359(2019).

[23] Xu Z H, Chen W, Penuelas J et al. 1000 fps computational ghost imaging using LED-based structured illumination[J]. Optics Express, 26, 2427-2434(2018).

[24] Yang Z H, Chen X, Zhao Z H et al. Image-free real-time target tracking by single-pixel detection[J]. Optics Express, 30, 864-873(2022).

[25] Song Z Y, Yang Z H, Yu Y J et al. Tracking compensation in computational ghost imaging of the moving targets[J]. Optical Technique, 45, 343-347(2019).

[26] Komatsu K, Ozeki Y, Nakano Y et al. Ghost imaging using integrated optical phased array[C], Th3H.4(2017).

[27] Braverman B, Liu X L, Boyd R W. How an acousto-optic modulator can be used as a spatial light modulator[C], PsM3F.5(2020).

[28] Hahamovich E, Monin S, Hazan Y et al. Single pixel imaging at megahertz switching rates via cyclic Hadamard masks[J]. Nature Communications, 12, 4516(2021).

[29] Jiang W J, Jiao J P, Guo Y et al. Single-pixel camera based on a spinning mask[J]. Optics Letters, 46, 4859-4862(2021).

[30] Khasanov I S, Zykova L A. Terahertz ghost imaging and surface plasmon resonance microscopy: analysis of factors affecting the image quality[J]. Proceedings of SPIE, 11582, 1158215(2020).

[31] Zhao Y Q, Zhang L L, Zhu D C et al. Single-pixel terahertz imaging based on compressed sensing[J]. Chinese Journal of Lasers, 38, s111003(2011).

[32] He Y H, Huang Y Y, Zeng Z R et al. Single-pixel imaging with neutrons[J]. Science Bulletin, 66, 133-138(2021).

[33] Bromberg Y, Katz O, Silberberg Y. Ghost imaging with a single detector[J]. Physical Review A, 79, 053840(2009).

[34] Xie Y T, Li Q Z. A review of deep learning methods for compressed sensing image reconstruction and its medical applications[J]. Electronics, 11, 586(2022).

[35] Liu B L, Wang F, Chen C H et al. Self-evolving ghost imaging[J]. Optica, 8, 1340-1349(2021).

[36] Geadah Y A, Corinthios M J G. Natural, dyadic, and sequency order algorithms and processors for the Walsh-Hadamard transform[J]. IEEE Transactions on Computers, 26, 435-442(1977).

[37] Yu W K. Super sub-Nyquist single-pixel imaging by means of cake-cutting Hadamard basis sort[J]. Sensors, 19, 4122(2019).

[38] Sun M J, Meng L T, Edgar M P et al. A Russian Dolls ordering of the Hadamard basis for compressive single-pixel imaging[J]. Scientific Reports, 7, 3464(2017).

[39] Yu W K, Liu Y M. Single-pixel imaging with origami pattern construction[J]. Sensors, 19, 5135(2019).

[40] Zhang Z B, Ma X, Zhong J G. Single-pixel imaging by means of Fourier spectrum acquisition[J]. Nature Communications, 6, 6225(2015).

[41] Zhang Z B, Wang X Y, Zheng G A et al. Fast Fourier single-pixel imaging via binary illumination[J]. Scientific Reports, 7, 12029(2017).

[42] Rousset F, Ducros N, Farina A et al. Adaptive basis scan by wavelet prediction for single-pixel imaging[J]. IEEE Transactions on Computational Imaging, 3, 36-46(2017).

[43] Czajkowski K M, Pastuszczak A, Kotyński R. Single-pixel imaging with Morlet wavelet correlated random patterns[J]. Scientific Reports, 8, 466(2018).

[44] Lu T A, Qiu Z H, Zhang Z B et al. Comprehensive comparison of single-pixel imaging methods[J]. Optics and Lasers in Engineering, 134, 106301(2020).

[45] Ferri F, Magatti D, Lugiato L A et al. Differential ghost imaging[J]. Physical Review Letters, 104, 253603(2010).

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

[47] Czajkowski K M, Pastuszczak A, Kotyński R. Real-time single-pixel video imaging with Fourier domain regularization[J]. Optics Express, 26, 20009-20022(2018).

[48] Bian L H, Suo J L, Dai Q H et al. Experimental comparison of single-pixel imaging algorithms[J]. Journal of the Optical Society of America A, Optics, Image Science, and Vision, 35, 78-87(2018).

[49] Mustapha A, Mohamed L, Ali K. An overview of gradient descent algorithm optimization in machine learning: application in the ophthalmology field[M]. Hamlich M, Bellatreche L, Mondal A, et al. Smart applications and data analysis. Communications in computer and information science, 1207, 349-359(2020).

[50] Hager W W, Zhang H C. A new conjugate gradient method with guaranteed descent and an efficient line search[J]. SIAM Journal on Optimization, 16, 170-192(2005).

[51] Ma J, Zhang G Y, Tan L Y. Analysis of quantum bit error rate based on single-photon source with Poisson distribution[J]. Optical Technique, 32, 101-104(2006).

[52] Bian L H, Suo J L, Chung J et al. Fourier ptychographic reconstruction using Poisson maximum likelihood and truncated Wirtinger gradient[J]. Scientific Reports, 6, 27384(2016).

[53] Wang W, Hu X M, Liu J D et al. Gerchberg-Saxton-like ghost imaging[J]. Optics Express, 23, 28416-28422(2015).

[54] Aβmann M, Bayer M. Compressive adaptive computational ghost imaging[J]. Scientific Reports, 3, 1545(2013).

[55] Yu W K, Liu X F, Yao X R et al. Complementary compressive imaging for the telescopic system[J]. Scientific Reports, 4, 5834(2014).

[56] Becker S, Bobin J, Candès E J. NESTA: a fast and accurate first-order method for sparse recovery[J]. SIAM Journal on Imaging Sciences, 4, 1-39(2011).

[57] Li C B, Yin W T, Jiang H et al. An efficient augmented Lagrangian method with applications to total variation minimization[J]. Computational Optimization and Applications, 56, 507-530(2013).

[58] Lü M, Wang W, Wang H et al. Deep-learning-based ghost imaging[J]. Scientific Reports, 7, 17865(2017).

[59] Shimobaba T, Endo Y, Nishitsuji T et al. Computational ghost imaging using deep learning[J]. Optics Communications, 413, 147-151(2018).

[60] Higham C F, Murray-Smith R, Padgett M J et al. Deep learning for real-time single-pixel video[J]. Scientific Reports, 8, 2369(2018).