[1] RODDIER F. Adaptive Optics in Astronomy ［M］. UK: Cambridge University Press, 1999.

[2] 耿则勋, 陈波, 王振国, 等. 自适应光学图像复原理论与方法［M］. 北京: 科学出版社, 2010.

    GENG Z X, CHEN B, WANG ZH G, et al.. The Theory and Method About Adaptive Optics Image Restoration ［M］. Beijing: Science press, 2010. (in Chinese)

[3] TIKHONOV A N, ARSENIN U Y. Solution of Ill-Posed Problems ［M］. New York: John Wiley & Sons, 1977: 9-21.

[4] ZHENG H, HELLWICH O. Adaptive data-driven regularization for variational image restoration in the BV space［C］. Proceedings of VISAPP’07, Barcelona, Spain, 2007, 53-60.

[5] CHEN X J, NG M K, ZHANG C. Non-Lipschitz lp-regularization and box constrained model for image restoration［J］. IEEE Transaction on Image Processing, 2012, 21(12): 4709-4721.

[6] STAMATIOS L, AURELIEN B, MICHAEL U. Hessian-based norm regularization for image restoration with biomedical applications ［J］. IEEE Transactions on Image Processing, 2012, 21(3): 983-996.

[7] 刘成云, 常发亮. 基于稀疏表示和Weber定律的运动图像盲复原［J］. 光学 精密工程, 2015, 23(2): 600-608.

    LIU CH Y, CHANG F L. Blind moving image restoration based on sparse representation and Weber’s law［J］. Opt. Precision Eng., 2015, 23(2): 600-608. (in Chinese)

[8] CHAN T F, WONG C K. Total variation blind deconvolution ［J］. IEEE Transactions on Image Processing, 1998, 7(3): 370-375.

[9] LI W, LI Q, GONG W, et al.. Total variation blind deconvolution employing split Bregman iteration［J］. Journal of Visual Communication & Image Representation, 2012, 23(3): 409-417.

[10] 马少贤, 江成顺. 基于四阶偏微分方程的盲图像恢复模型［J］. 中国图象图形学报, 2010, 15(1): 26-30.

    MA SH X, JIANG CH SH. A new method for image blind restoration based on fourth-order PDE［J］. Journal of Image and Graphics, 2010, 15(1): 26-30. (in Chinese)

[11] 刘琨, 王国宇, 姬婷婷. 一种四阶P-Laplace图像盲复原方法［J］. 中国海洋大学学报, 2014, 44(9): 110-115.

    LIU K, WANG G Y, JI T T. A method for fourth-order P-Laplace blind image restoration［J］. Periodical of Ocean University of China, 2014, 44(9): 110-115. (in Chinese)

[12] 初永玲, 李绍春, 王枚.非凸全变分正则化模糊图像复原模型研究［J］. 计算机工程与应用, 2011, 47(35): 171-173.

    CHU Y L, LI SH CH, WANG M. Study on non-convex total variation regularization model for restoration of motion blurred image［J］. Computer Engineering and Applications, 2011, 47(35): 171-173. (in Chinese)

[13] 陈明举. 基于统计特性的非局部均值去噪算法［J］. 液晶与显示, 2014, 29(3): 450-454.

    CHEN M J. Non-local means image denoising algorithm based on statistical property［J］. Chinese Journal of Liquid Crystals and Display, 2014, 29(3): 450-454. (in Chinese)

[14] ALMEIDA M, ALMEIDA L. Blind and semi-blind deblurring of natural images［J］. IEEE Trans. Image Processing, 2010, 19(1): 36-52.

[15] KRISHNAN D, TAY T, FERGUS R. Blind deconvolution using a normalized sparsity measure［C］. Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition IEEE Computer Society, 2011: 233-240.

[16] KOTERA J, ROUBEK F, MILANFAR P. Blind deconvolution using alternating maximum a posteriori estimation with heavy-tailed priors［J］. Computer Analysis of Images and Patterns, 2013: 59-66.

[17] SHAO W Z, LI H B, ELAD M. Bi-l0-l2-Norm Regularization for Blind Motion Deblurring［J］. Eprint Arxiv, 2014.

[18] KRISHNAN D, BRUNA J, FERGUS R. Blind Deconvolution with Re-weighted Sparsity Promotion［J］. Arxiv Preprint Arxiv, 2013.

[19] 王亚强, 陈波. 一种改进的各向异性扩散超声图像去噪算法［J］. 液晶与显示, 2015, 30(2): 310-316.

    WANG Y Q, CHEN B. Improved anisotropic diffusion ultrasound image denoising algorithm［J］. Chinese Journal of Liquid Crystals and Display, 2015, 30(2): 310-316. (in Chinese)

[20] 闫敬文, 彭鸿, 刘蕾, 等. 基于L0正则化模糊核估计的遥感图像复原［J］. 光学 精密工程, 2014, 22(9): 2572-2579.

    YAN J W. PENG H, LIU L, et al.. Remote sensing image restoration based on zero-norm regularized kernel estimation ［J］. Opt. Precision Eng., 2014, 22(9): 2572-2579. (in Chinese)

[21] ZHANG J J, WANG Q. An iterative conjugate gradient regularization method for image restoration［J］. Journal of Information and Computing Science, 2010, 5(1): 55-62.

[22] SHI Y, CHANG Q, XU J. Convergence of fixed point iteration for deblurring and denoising problem［J］. Applied Mathematics and Computation, 2007, 189(2): 1178-1185.

[23] FANG H, YAN L. Multiframe blind image deconvolution with split Bregman method ［J］. Optik International Journal for Light and Electron Optics, 2014, 125(1): 446-451.

[24] WU C L, TAI X C. Augmented lagrangian method, dual methods, and split bregman iteration for ROF, vectorial TV, and high order models ［J］. Siam Journal on Imaging Sciences, 2010, 3(3): 300-339.

[25] HE C, HU C, YANG X, et al.. An adaptive total generalized variation model with augmented lagrangian method for image denoising［J］. Mathematical Problems in Engineering, 2014, 842(2): 805-808.

[26] HONG M, LUO Z Q. On the linear convergence of the alternating direction method of multipliers［J］. Eprint Arxiv, 2012.

[27] YANG J, ZHANG Y. Alternating direction algorithms for L1 problems in compressive sensing［J］.SIAM Journal on Scientific Computing, 2011, 33(1): 250-278.

[28] GETREUER P, GETREUER P. Total variation deconvolution using split Bregman［J］. Image Processing on Line, 2012, 2: 158-174.

[29] KRISHNAN D, FERGUS R. Fast image deconvolution using hyper-laplacian priors［J］. Proceedings of Neural Information Processing Systems Blurred Lut Nr, 2009: 1033-1041.

[30] KRISHNAN D, TAY T, FERGUS R. Blind deconvolution using a normalized sparsity measure［C］.2011 IEEE Conference on Computer Vision and Pattern Recognition(CVPR), 2011: 233-240.