[1] J. S. Courtney-Pratt. A new method for the photographic study of fast transient phenomena. Res. Supply, 2, 287-295(1949).

[2] L. Gao, J. Liang, C. Li. Single-shot compressed ultrafast photography at one hundred billion frames per second. Nature, 516, 74-77(2014).

[3] P. Wang, J. Liang, L. V. Wang. Single-shot ultrafast imaging attaining 70 trillion frames per second. Nat. Commun., 11, 2091(2020).

[4] L. Zhu, Y. Chen, J. Liang. Space- and intensity-constrained reconstruction for compressed ultrafast photography. Optica, 3, 694-697(2016).

[5] I. Orović, V. Papić, C. Ioana. Compressive sensing in signal processing: algorithms and transform domain formulations. Math Probl. Eng., 2016, 616393(2016).

[6] E. J. Candes, J. Romberg, T. Tao. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans. Inform. Theory, 52, 489-509(2006).

[7] J. M. Bioucas-Dias, M. A. T. Figueiredo. A new twist: two-step iterative shrinkage/thresholding algorithms for image restoration. IEEE Trans. Image Process., 16, 2992-3004(2007).

[8] Z. M. Yao, L. Sheng, Y. Song. Dual-channel compressed ultrafast photography for Z-pinch dynamic imaging. Rev. Sci. Instrum., 94, 035106(2023).

[9] J. Yao, D. Qi, C. Yang. Multichannel-coupled compressed ultrafast photography. J. Opt., 22, 085701(2020).

[10] J. Liang, C. Ma, L. Zhu. Single-shot real-time video recording of a photonic mach cone induced by a scattered light pulse. Sci. Adv., 3, e1601814(2017).

[11] H. Zhou, Y. Song, Z. Yao. Unsupervised reconstruction with a registered time-unsheared image constraint for compressed ultrafast photography. Opt. Express, 32, 16333-16350(2024).

[12] Y. He, Y. Yao, Y. L. He. Multimodal fusion-based high-fidelity compressed ultrafast photography. Opt. Lasers Eng., 181, 108363(2024).

[13] C. Yang, D. Qi, X. Wang. Optimizing codes for compressed ultrafast photography by the genetic algorithm. Optica, 5, 147-151(2018).

[14] J. Yao, D. Qi, Y. Yao. Total variation and block-matching 3D filtering-based image reconstruction for single-shot compressed ultrafast photography. Opt. Lasers Eng., 139, 106475(2021).

[15] Y. Liu, X. Yuan, J. Suo. Rank minimization for snapshot compressive imaging. IEEE Trans. Pattern Anal. Mach. Intell., 41, 2990-3006(2019).

[16] X. Yuan, Y. Liu, J. Suo. Plug-and-play algorithms for large-scale snapshot compressive imaging. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 1444-1454(2020).

[17] X. Yuan, Y. Liu, J. Suo. Plug-and-play algorithms for video snapshot compressive imaging. IEEE Trans. Pattern Anal. Mach. Intell., 44, 7093-7111(2021).

[18] C. Z. Jin, D. Qi, J. Yao. Weighted multi-scale denoising via adaptive multi-channel fusion for compressed ultrafast photography. Opt. Express, 30, 31157-31170(2022).

[19] S. Boyd, N. Parikh, E. Chu. Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations Trends Mach. Learn., 3, 1-122(2011).

[20] X. Yuan. Generalized alternating projection based total variation minimization for compressive sensing. IEEE International Conference on Image Processing, 2539-2543(2016).

[21] A. Zhang, J. Wu, J. Suo. Single-shot compressed ultrafast photography based on U-net network. Opt. Express, 28, 39299-39310(2020).

[22] Y. Ma, X. Feng, L. Gao. Deep-learning-based image reconstruction for compressed ultrafast photography. Opt. Lett., 45, 4400-4403(2020).

[23] H. Zhou, Z. Yao, L. Sheng. X-ray compressed ultrafast photography under the constraint of time-integrated-image for X-pinch. Opt. Lasers Eng., 183, 108508(2024).

[24] Y. He, Y. Yao, Y. He. Untrained neural network enhances the resolution of structured illumination microscopy under strong background and noise levels. Adv. Photonics Nexus, 2, 046005(2023).

[25] D. Ulyanov, A. Vedaldi, V. S. Lempitsky. Deep image prior. Int. J. Comput. Vis., 128, 1867-1888(2017).

[26] R. Heckel, P. Hand. Deep decoder: concise image representations from untrained non-convolutional networks. arXiv(2018).

[27] J. Nie, L. Zhang, C. Wang. Robust deep hyperspectral imagery super-resolution. IEEE International Geoscience and Remote Sensing Symposium, 847-850(2019).

[28] D. Zhao, F. Zhao, Y. Gan. Reference-driven compressed sensing MR image reconstruction using deep convolutional neural networks without pre-training. Sensors, 20, 308(2020).

[29] Y. He, Y. Yao, Y. He. Untrained neural network enhances the resolution of structured illumination microscopy under strong background and noise levels. Adv. Photonics Nexus, 2, 046005(2023).

[30] F. Wang, Y. Bian, H. Wang. Phase imaging with an untrained neural network. Light Sci. Appl., 9, 77(2020).

[31] H. Zhou, Y. Song, Z. Yao. Image reconstruction for compressed ultrafast photography based on manifold learning and the alternating direction method of multipliers. J. Opt. Soc. Am. A, 41, 1585-1593(2024).

[32] M. Marquez, Y. Lai, X. Liu. Deep-learning supervised snapshot compressive imaging enabled by an end-to-end adaptive neural network. IEEE J. Sel. Top. Signal Process., 16, 688-699(2022).

[33] Y. Luo, X. Zhao, D. Meng. Hlrtf: hierarchical low-rank tensor factorization for inverse problems in multi-dimensional imaging. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 19281-19290(2022).

[34] T. Yokota, H. Hontani, Q. Zhao. Manifold modeling in embedded space: an interpretable alternative to deep image prior. IEEE Trans. Neural Networks Learn. Syst., 33, 1022-1036(2020).

[35] E. Kernfeld, M. Kilmer, S. Aeron. Tensor–tensor products with invertible linear transforms. Linear Algebr. Appl., 485, 545-570(2015).

[36] J. Liu, Y. Sun, X. Xu. Image restoration using total variation regularized deep image prior. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 7715-7719(2019).

[37] L. I. Rudin, S. Osher, E. Fatemi. Nonlinear total variation based noise removal algorithms. Physica D, 60, 259-268(1992).

[38] V. Saragadam, R. Balestriero, A. Veeraraghavan. Deeptensor: low-rank tensor decomposition with deep network priors. IEEE Trans. Pattern Anal. Mach. Intell., 46, 10337-10348(2024).

[39] Y. Chen, H. Zhang, Y. Wang. Flex-DLD: deep low-rank decomposition model with flexible priors for hyperspectral image denoising and restoration. IEEE Trans. Image Process., 33, 1211-1226(2024).

[40] M. Zhao, S. Jalali. Theoretical analysis of binary masks in snapshot compressive imaging systems. 2023 59th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 1-8(2023).

[41] D. P. Kingma, J. Ba. Adam: a method for stochastic optimization. arXiv(2014).

[42] Z. Wang, A. C. Bovik, H. R. Sheikh. Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process., 13, 600-612(2004).

[43] Y. Lai, M. Marquez, J. Liang. Tutorial on compressed ultrafast photography. J. Biomed. Opt., 29, S11524(2024).