[1] Chen L, Yap K H. Efficient discrete spatial techniques for blur support identification in blind image deconvolution[J]. IEEE Transactions on Signal Processing, 2006, 54(4): 1557-1562.

[2] Dobe M, MacHala L, Fürst T. Blurred image restoration: a fast method of finding the motion length and angle[J]. Digital Signal Processing, 2010, 20(6): 1677-1686.

[3] Dash R, Majhi B. Motion blur parameters estimation for image restoration[J]. Optik, 2014, 125(5): 1634-1640.

[4] 赵妍妍, 袁艳, 苏丽娟. 任意方向匀速直线运动模糊的点扩展函数估计[J]. 中国激光, 2012, 39(8): 0809003.

    Zhao Y Y, Yuan Y, Su L J. Point spread function estimation of blurring due to uniform linear motion in arbitrary direction[J]. Chinese Journal of Lasers, 2012, 39(8): 0809003.

[5] Tiwari S, Shukla V P, Biradar S R, et al. Blur parameters identification for simultaneous defocus and motion blur[J]. CSI Transactions on ICT, 2014, 2(1): 11-22.

[6] 闫敬文, 谢婷婷, 彭鸿, 等. 基于L0范数正则项的运动图像去模糊[J]. 激光与光电子学进展, 2017, 54(2): 021005.

    Yan J W, Xie T T, Peng H, et al. Motion image deblurring based on L0 norms regularization term[J]. Laser & Optoelectronics Progress, 2017, 54(2): 021005.

[7] 朱婉霞, 王国栋, 潘振宽, 等. 基于多通道非线性扩散项的运动模糊图像盲复原[J]. 激光与光电子学进展, 2018, 55(7): 071008.

    Zhu W X, Wang G D, Pan Z K, et al. Motion blurred image blind deconvolution based on multichannel nonlinear diffusion term[J]. Laser & Optoelectronics Progress, 2018, 55(7): 071008.

[8] Cho S, Lee S. Fast motion deblurring[J]. ACM Transactions on Graphics, 2009, 28(5): 145.

[9] KrishnanD, TayT, FergusR. Blind deconvolution using a normalized sparsity measure[C]∥ 2011 Conference on Computer Vision and Pattern Recognition, June 20-25, 2011. Colorado Springs, CO, USA. New York: IEEE, 2011: 12258022.

[10] 李晖晖, 钱林弘, 杨宁, 等. 基于边缘预测和稀疏约束的湍流图像盲复原[J]. 仪器仪表学报, 2015, 36(4): 721-728.

    Li H H, Qian L H, Yang N, et al. Turbulence degraded image blind restoration based on sparsity regularization and edge prediction[J]. Chinese Journal of Scientific Instrument, 2015, 36(4): 721-728.

[11] KrishnanD, FergusR. Fast image deconvolution using hyper-Laplacian priors[C] ∥Proceedings of the 22 nd International Conference on Neural Information Processing Systems, December 7-10, 2009, Vancouver, British, Columbia. New York: Curran Associates Inc. 2009: 1033- 1041.

[12] Shao W Z, Li H B, Elad M. Bi-l0-l2-norm regularization for blind motion deblurring[J]. Journal of Visual Communication and Image Representation, 2015, 33: 42-59.

[13] 王灿, 杨帆, 李靖. 基于l1/l2的高低阶全变差运动模糊图像盲复原方法[J]. 激光与光电子学进展, 2018, 55(4): 041015.

    Wang C, Yang F, Li J. Blind recovery method of motion blurred image based on combining l1/l2 norm with high order and low order total variation[J]. Laser & Optoelectronics Progress, 2018, 55(4): 041015.

[14] Pan JS, HuZ, Su ZX, et al. Deblurring text images via L0-regularized intensity and gradient prior[C]∥2014 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2014. Columbus, OH, USA. New York: IEEE, 2014: 14632123.

[15] Bai YC, CheungG, Liu XM, et al. Blind image deblurring via reweighted graph total variation[C]∥2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), April 15-20, 2018. Calgary, AB. New York:IEEE, 2018: 18096836.

[16] 仇翔, 戴明. 基于L0稀疏先验的相机抖动模糊图像盲复原[J]. 光学精密工程, 2017, 25(9): 2490-2498.

    Qiu X, Dai M. Blind restoration of camera shake blurred image based on L 0 sparse priors[J]. Optics and Precision Engineering, 2017, 25(9): 2490-2498.

[17] Kong J, Lu K S, Jiang M. A new blind deblurring method via hyper-laplacian prior[J]. Procedia Computer Science, 2017, 107: 789-795.

[18] Tang S, Zheng W P, Xie X Z, et al. Multi-regularization-constrained blur kernel estimation method for blind motion deblurring[J]. IEEE Access, 2019, 7: 5296-5311.

[19] 唐述, 谢显中. 多正则化混合约束的模糊图像盲复原方法[J]. 电子与信息学报, 2015, 37(4): 770-776.

    Tang S, Xie X Z. Multi-regularization hybrid constraints method for blind image restoration[J]. Journal of Electronics & Information Technology, 2015, 37(4): 770-776.

[20] 孔军, 卢克赛, 蒋敏, 等. 一种基于超拉普拉斯先验的图像盲去模糊方法: CN201610814545.5[P].2017-01-18.

    KongJ, Lu KS, JiangM, et al. 2017-01-18.

[21] RothS, Black MJ. Fields ofexperts: a framework for learning image priors[C]∥2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), San Diego, CA, USA. New York: IEEE, 2005: 8624117.