[1] Belge M,Kilmer M E,Miller E L. Wavelet domain image restoration with adaptive edge-preserving regularization [J]. IEEE Trans. on Image Processing(S1057-7149),2000,9(4):597-608.
[2] Figueiredo M,Nowak R D. An EM algorithm for wavelet-based image restoration [J]. IEEE Trans. on Image Processing (S1057-7149),2003,12(8):906-916.
[3] Geman S,Geman D. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images [J]. IEEE Trans. on Pattern Analysis and Machine Intelligence(S0162-8828),1984,6(6):721-741.
[4] Chandas J,Galatsanos N P,Likas A. Bayesian Restoration Using a New Non-Stationary Edge-Preserving Image Prior [J]. IEEE Trans. on Image Processing(S1057-7149),2006,15(10):2987-2997.
[5] Chan T F,Esedoglu S,Park F,et al. Recent Development in Total Variation Image Restoration [M]// Mathematical Models of Computer Vision. Springer Verlag,2005.
[6] Babacan S D,Molina R,Katsaggelos A K. Parameter estimation in TV image restoration using variational distribution approximation [J]. IEEE Trans. on Image Processing(S1057-7149),2008,17(3):326-339.
[7] Pan Ruimin,Reeves Stanley J. Efficient Huber-Markov Edge-Preserving Image Restoration [J]. IEEE Trans. on Image Processing(S1057-7149),2006,15(12):3728-3735.
[8] Chantas G,Galatsanos N,Likas A,et al. Variational Bayesian image restoration based on product of t-distributions image prior [J]. IEEE Trans. on Image Processing(S1057-7149),2008,17(10):1795-1805.
[9] Park S,Prak M,Kang M. Super-resolution image reconstruction: A technical overview [J]. IEEE Signal Processing Magazine (S1053-5888),2003,20(3):21-36.
[10] Lee H,Battle A,Raina R,et al. Efficient sparse coding algorithms [C]// Neural Information Processing Systems,Vancouver, B.C., Canada,Dec 4-9, 2006:801-808.
[11] Donoho D L. Compressed sensing [J]. IEEE Trans. on Information Theory(S0018-9448),2006,52(4):1289-1306.
[12] Vogel C R,Oman M E. Fast, robust total variation-based reconstruction of noisy, blurred images [J]. IEEE Trans. on Image Processing (S1057-7149),1998,7(6):813-824.
[13] Bioucas-Dias J M,Figueiredo M A T,Oliveira J P. Total variation image deconvolution: A majorization- minimization approach [C]// IEEE International Conference on Acoustics, Speech and Signal Processing, Toulouse, France,May 14-19, 2006,2:11-14.
[14] HUANG Y,NG Michael K,WEN You-wei. A fast total variation minimization method for image restoration [J]. SIAM Journal on Multi scale Modeling & Simulation(S1540-3467),2008,7(2):774-795.
[15] Figueiredo M A T,Nowak R D. A bound optimization approach to wavelet-based image deconvolution [C]// IEEE International Conference on Image Processing,Genoa, Italy,Sept 11-14, 2005,2:782-785.
[16] Antonin Chambolle. An algorithm for total variation minimization and applications [J]. J. Math. Imaging Vision (S1573-7683),2004,20(1/2):89-97.
[17] Mingqiang Zhu,Wright Stephen J,Chan Tony F. Duality-Based algorithms for total-variation regularized image restoration,Computational and Applied Mathematics Report 08-33 [R]. UCLA,2008.
[18] Bioucas-Dias J. Bayesian wavelet-based image deconvolution: AGEM algorithm exploiting a class of heavy-tailed priors [J]. IEEE Transactions on Image Processing(S1057-7149),2006,15(4):937-951.
[19] Elad M,Matalon B,Zibulevsky M. Coordinate and subspace optimization methods for linear least squares with non-quadratic regularization [J]. Applied and Computational Harmonic Analysis(S1063-5203),2007,23:346-367.
[20] Combettes P,Wajs V. Signal recovery by proximal forward-backward splitting [J]. SIAM Journal on Multi scale Modeling & Simulation(S1540-3467),2005,4:1168-1200.
[21] AXELSSON Owe. Iterative Solution Methods [M]. New York,Cambridge University Press,1996.
[22] Barzilai J,Borwein J M. Two-point step size gradient methods [J]. IMA Journal of Numerical Analysis(S0272-4829),1988,8:141-149