M. Figueiredo and R. Nowak, An EM algorithm for wavelet-based image restoration, IEEE Transactions on Image Processing, vol.12, issue.8, pp.906-916, 2003.
DOI : 10.1109/TIP.2003.814255

J. Bioucas-dias and M. Figueiredo, A New TwIST: Two-Step Iterative Shrinkage/Thresholding Algorithms for Image Restoration, IEEE Transactions on Image Processing, vol.16, issue.12, pp.2292-3004, 2007.
DOI : 10.1109/TIP.2007.909319

E. Candès, J. Romberg, and T. Tao, Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information, IEEE Transactions on Information Theory, vol.52, issue.2, pp.489-509, 2006.
DOI : 10.1109/TIT.2005.862083

D. Donoho, Compressed sensing, IEEE Transactions on Information Theory, vol.52, issue.4, pp.1289-1306, 2006.
DOI : 10.1109/TIT.2006.871582
URL : https://hal.archives-ouvertes.fr/inria-00369486

J. Haupt and R. Nowak, Signal Reconstruction From Noisy Random Projections, IEEE Transactions on Information Theory, vol.52, issue.9, pp.4036-4048, 2006.
DOI : 10.1109/TIT.2006.880031
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.101.4085

P. Combettes and V. Wajs, Signal Recovery by Proximal Forward-Backward Splitting, Multiscale Modeling & Simulation, vol.4, issue.4, pp.1168-1200, 2005.
DOI : 10.1137/050626090
URL : https://hal.archives-ouvertes.fr/hal-00017649

D. Donoho, De-noising by soft-thresholding, IEEE Transactions on Information Theory, vol.41, issue.3, pp.613-627, 1995.
DOI : 10.1109/18.382009
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.161.9704

M. Figueiredo, J. Bioucas-dias, and M. Figueiredo, Majorization–Minimization Algorithms for Wavelet-Based Image Restoration, IEEE Transactions on Image Processing, vol.16, issue.12, pp.2980-2991, 2007.
DOI : 10.1109/TIP.2007.909318

J. Bioucas-dias and M. Figueiredo, A New TwIST: Two-Step Iterative Shrinkage/Thresholding Algorithms for Image Restoration, IEEE Transactions on Image Processing, vol.16, issue.12, pp.2992-3004, 2007.
DOI : 10.1109/TIP.2007.909319
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.9052

L. I. Rudin, S. Osher, and E. Fatemi, Nonlinear total variation based noise removal algorithms, Physica D: Nonlinear Phenomena, vol.60, issue.1-4, pp.259-268, 1992.
DOI : 10.1016/0167-2789(92)90242-F

J. Bioucas-dias and M. Figueiredo, An iterative algorithm for linear inverse problems with compound regularizers, 2008 15th IEEE International Conference on Image Processing, 2008.
DOI : 10.1109/ICIP.2008.4711847

T. Goldstein and S. Osher, The Split Bregman Method for L1-Regularized Problems, SIAM Journal on Imaging Sciences, vol.2, issue.2, pp.8-29, 2008.
DOI : 10.1137/080725891

F. Malgouyres, Minimizing the total variation under a general convex constraint for image restoration, IEEE Transactions on Image Processing, vol.11, issue.12, pp.1450-1456, 2002.
DOI : 10.1109/TIP.2002.806241

S. Durand and J. Froment, Reconstruction of Wavelet Coefficients Using Total Variation Minimization, SIAM Journal on Scientific Computing, vol.24, issue.5, pp.1754-1767, 2003.
DOI : 10.1137/S1064827501397792
URL : https://hal.archives-ouvertes.fr/hal-00712152

F. X. Dupé, J. M. Fadili, and J. L. Starck, A Proximal Iteration for Deconvolving Poisson Noisy Images Using Sparse Representations, IEEE Transactions on Image Processing, vol.18, issue.2, pp.310-321, 2009.
DOI : 10.1109/TIP.2008.2008223

C. Chaux, P. L. Combettes, J. Pesquet, and V. Wajs, A forwardbackward algorithm for image restoration with sparse representations, Signal Processing with Adaptative Sparse Structured Representations (SPARS'05), pp.49-52, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00017658

W. Yin, S. Osher, D. Goldfarb, and J. Darbon, Bregman Iterative Algorithms for $\ell_1$-Minimization with Applications to Compressed Sensing, SIAM Journal on Imaging Sciences, vol.1, issue.1, pp.143-168, 2006.
DOI : 10.1137/070703983

A. Chambolle, An algorithm for total variation minimization and applications, J. Math. Imaging Vis, vol.20, issue.12, pp.89-97, 2004.