M. V. Afonso, J. M. Bioucas-dias, and M. A. Figueiredo, An Augmented Lagrangian Approach to the Constrained Optimization Formulation of Imaging Inverse Problems, IEEE Transactions on Image Processing, vol.20, issue.3, pp.681-695, 2011.
DOI : 10.1109/TIP.2010.2076294

Y. Altmann, A. Wallace, and S. Mclaughlin, Spectral unmixing of multispectral lidar signals, tech. report, 2015.

S. Anthoine, J. Aujol, Y. Boursier, and C. Melot, Some proximal methods for CBCT and PET tomography, Wavelets and Sparsity XIV, pp.565-598, 2012.
DOI : 10.1117/12.893415

G. Aubert and J. Aujol, A Variational Approach to Removing Multiplicative Noise, SIAM Journal on Applied Mathematics, vol.68, issue.4, pp.925-946, 2008.
DOI : 10.1137/060671814

F. R. Bach, R. Jenatton, J. Mairal, and G. Obozinski, Optimization with sparsityinducing penalties, Machine Learning, pp.1-106, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00613125

H. H. Bauschke and P. L. Combettes, Convex analysis and monotone operator theory in Hilbert spaces, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00643354

B. Begovic, V. Stankovic, and L. Stankovic, Contrast enhancement and denoising of Poisson and Gaussian mixture noise for solar images, 2011 18th IEEE International Conference on Image Processing, pp.11-14, 2011.
DOI : 10.1109/ICIP.2011.6115829

F. Benvenuto, A. L. Camera, C. Theys, A. Ferrari, H. Lantéri et al., The study of an iterative method for the reconstruction of images corrupted by Poisson and Gaussian noise, Inverse Probl, vol.20, p.24, 2008.

R. I. Bot¸andbot¸bot¸and and C. Hendrich, Convergence analysis for a primal-dual monotone + skew splitting algorithm with applications to total variation minimization, J. Math. Imaging Vision, pp.49-551, 2014.

S. Bonettini and M. Prato, New convergence results for the scaled gradient projection method, tech. report, Feb, 2015.

G. Boracchi and A. Foi, Multiframe raw-data denoising based on block-matching and 3-D filtering for low-light imaging and stabilization, The 2008 International Workshop on Local and Non-Local Approximation in Image Processing, 2008.

X. Bresson, A short note for nonlocal TV minimization, 2009.

L. M. Arias and P. L. Combettes, A Monotone+Skew Splitting Model for Composite Monotone Inclusions in Duality, SIAM Journal on Optimization, vol.21, issue.4, pp.1230-1250, 2011.
DOI : 10.1137/10081602X
URL : https://hal.archives-ouvertes.fr/hal-00643797

A. Buades, B. Coll, and J. Morel, A Non-Local Algorithm for Image Denoising, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.60-65, 2005.
DOI : 10.1109/CVPR.2005.38

J. Cai, R. H. Chan, and M. Nikolova, Fast Two-Phase Image Deblurring Under Impulse Noise, Journal of Mathematical Imaging and Vision, vol.17, issue.1, pp.46-53, 2010.
DOI : 10.1007/s10851-009-0169-7

A. Chakrabarti and T. Zickler, Image restoration with signal-dependent camera noise, p.2994, 1204.

A. Chambolle and T. Pock, A First-Order Primal-Dual Algorithm for Convex Problems with??Applications to Imaging, Journal of Mathematical Imaging and Vision, vol.60, issue.5, pp.120-145, 2011.
DOI : 10.1007/s10851-010-0251-1
URL : https://hal.archives-ouvertes.fr/hal-00490826

R. Chan, H. Yang, and T. Zeng, A Two-Stage Image Segmentation Method for Blurry Images with Poisson or Multiplicative Gamma Noise, SIAM Journal on Imaging Sciences, vol.7, issue.1, pp.98-127, 2014.
DOI : 10.1137/130920241

C. Chaux, J. Pesquet, and N. Pustelnik, Nested Iterative Algorithms for Convex Constrained Image Recovery Problems, SIAM Journal on Imaging Sciences, vol.2, issue.2, pp.730-762, 2009.
DOI : 10.1137/080727749
URL : https://hal.archives-ouvertes.fr/hal-00621932

P. Chen, J. Huang, and X. Zhang, A primal???dual fixed point algorithm for convex separable minimization with applications to image restoration, Inverse Problems, vol.29, issue.2, pp.29-025011, 2013.
DOI : 10.1088/0266-5611/29/2/025011

P. L. Combettes, J. Pesquet, and . Douglas, A Douglas???Rachford Splitting Approach to Nonsmooth Convex Variational Signal Recovery, IEEE Journal of Selected Topics in Signal Processing, vol.1, issue.4, pp.564-574, 2007.
DOI : 10.1109/JSTSP.2007.910264
URL : https://hal.archives-ouvertes.fr/hal-00621820

H. H. Bauschke, R. Burachik, P. L. Combettes, V. Elser, D. R. Luke et al., Inverse Problems Proximal splitting methods in signal processing Proximal splitting methods in signal processing, in Fixed-Point Algorithms for, Fixed-Point Algorithms for Inverse Problems in Science and Engineering, pp.65014-185, 2008.

P. L. Combettes and V. R. 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

L. Condat, A Primal???Dual Splitting Method for Convex Optimization Involving Lipschitzian, Proximable and Linear Composite Terms, Journal of Optimization Theory and Applications, vol.23, issue.1???2, pp.460-479, 2013.
DOI : 10.1007/s10957-012-0245-9
URL : https://hal.archives-ouvertes.fr/hal-00609728

S. Delpretti, F. Luisier, S. Ramani, T. Blu, and M. Unser, Multiframe sure-let denoising of timelapse fluorescence microscopy images, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.14-17, 2008.
DOI : 10.1109/ISBI.2008.4540954

G. Demoment, Image reconstruction and restoration: overview of common estimation structures and problems, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.37, issue.12, pp.2024-2036, 1989.
DOI : 10.1109/29.45551

Y. Dong and T. Zeng, A Convex Variational Model for Restoring Blurred Images with Multiplicative Noise, SIAM Journal on Imaging Sciences, vol.6, issue.3, pp.1598-1625, 2013.
DOI : 10.1137/120870621

F. Dupé, J. M. Fadili, and J. 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

M. Elad, P. Milanfar, and R. Rubinstein, Analysis versus synthesis in signal priors, Inverse Problems, vol.23, issue.3, pp.947-968, 2007.
DOI : 10.1088/0266-5611/23/3/007

Y. C. Eldar, P. Kuppinger, and H. Bolcskei, Block-Sparse Signals: Uncertainty Relations and Efficient Recovery, IEEE Transactions on Signal Processing, vol.58, issue.6, pp.3042-3054, 2010.
DOI : 10.1109/TSP.2010.2044837

E. Esser, X. Zhang, and T. Chan, A General Framework for a Class of First Order Primal-Dual Algorithms for Convex Optimization in Imaging Science, SIAM Journal on Imaging Sciences, vol.3, issue.4, pp.1015-1046, 2010.
DOI : 10.1137/09076934X

A. Foi, Clipped noisy images: Heteroskedastic modeling and practical denoising, Signal Process, pp.2609-2629, 2009.
DOI : 10.1016/j.sigpro.2009.04.035
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.164.5641

A. Foi, M. Trimeche, V. Katkovnik, and K. Egiazarian, Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data, IEEE Transactions on Image Processing, vol.17, issue.10, pp.1737-1754, 2008.
DOI : 10.1109/TIP.2008.2001399

T. Fukushima, Precise and fast computation of Lambert -functions without transcendental function evaluations, Journal of Computational and Applied Mathematics, vol.244, pp.77-89, 2013.
DOI : 10.1016/j.cam.2012.11.021

D. Geman and G. Reynolds, Constrained restoration and the recovery of discontinuities, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.14, issue.3, pp.367-383, 1992.
DOI : 10.1109/34.120331

E. Gil-rodrigo, J. Portilla, D. Miraut, and R. Suarez-mesa, Efficient joint poisson-gauss restoration using multi-frame L2-relaxed-L0 analysis-based sparsity, 2011 18th IEEE International Conference on Image Processing, pp.11-14, 2011.
DOI : 10.1109/ICIP.2011.6115697

G. Gilboa and S. Osher, Nonlocal Operators with Applications to Image Processing, Multiscale Modeling & Simulation, vol.7, issue.3, pp.1005-1028, 2008.
DOI : 10.1137/070698592

J. Giovannelli and A. Coulais, Positive deconvolution for superimposed extended source and point sources, Astronomy and Astrophysics, vol.439, issue.1, pp.401-412, 2005.
DOI : 10.1051/0004-6361:20047011

S. Harizanov, J. Pesquet, and G. Steidl, Epigraphical Projection for Solving Least Squares Anscombe Transformed Constrained Optimization Problems, Lecture Notes in Computer Science, vol.7893, pp.125-136, 2013.
DOI : 10.1007/978-3-642-38267-3_11

B. He and X. Yuan, Convergence Analysis of Primal-Dual Algorithms for a Saddle-Point Problem: From Contraction Perspective, SIAM Journal on Imaging Sciences, vol.5, issue.1, pp.119-149, 2012.
DOI : 10.1137/100814494

Y. Huang, M. Ng, and Y. Wen, A New Total Variation Method for Multiplicative Noise Removal, SIAM Journal on Imaging Sciences, vol.2, issue.1, pp.20-40, 2009.
DOI : 10.1137/080712593

B. G. Jeong, B. C. Kim, Y. H. Moon, and I. K. Eom, Simplified noise model parameter estimation for signal-dependent noise, Signal Process, Part B, vol.96, pp.266-273, 2014.
DOI : 10.1016/j.sigpro.2013.10.002

T. Jeong, H. Woo, and S. Yun, Frame-based Poisson image restoration using a proximal linearized alternating direction method, Inverse Problems, vol.29, issue.7, pp.29-075007, 2013.
DOI : 10.1088/0266-5611/29/7/075007

A. Jezierska, C. Chaux, J. Pesquet, and H. Talbot, Iterative poisson-Gaussian noise parametric estimation for blind image denoising, 2014 IEEE International Conference on Image Processing (ICIP), pp.2014-2819, 2014.
DOI : 10.1109/ICIP.2014.7025570
URL : https://hal.archives-ouvertes.fr/hal-01060081

A. Jezierska, C. Chaux, J. Pesquet, H. Talbot, and G. Engler, An EM Approach for Time-Variant Poisson-Gaussian Model Parameter Estimation, IEEE Transactions on Signal Processing, vol.62, issue.1, pp.17-30, 2014.
DOI : 10.1109/TSP.2013.2283839
URL : https://hal.archives-ouvertes.fr/hal-00766686

A. Jezierska, E. Chouzenoux, J. Pesquet, and H. Talbot, A primal-dual proximal splitting approach for restoring data corrupted with poisson-gaussian noise, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.25-30, 2012.
DOI : 10.1109/ICASSP.2012.6288075
URL : https://hal.archives-ouvertes.fr/hal-00687634

N. Komodakis and J. Pesquet, Playing with Duality: An overview of recent primal?dual approaches for solving large-scale optimization problems, IEEE Signal Processing Magazine, vol.32, issue.6, 2014.
DOI : 10.1109/MSP.2014.2377273
URL : https://hal.archives-ouvertes.fr/hal-01246610

H. Lantéri and C. Theys, Restoration of Astrophysical Images???The Case of Poisson Data with Additive Gaussian Noise, EURASIP Journal on Advances in Signal Processing, vol.2005, issue.15, pp.2500-2513, 2005.
DOI : 10.1155/ASP.2005.2500

S. Lefkimmiatis, A. Bourquard, and M. Unser, Hessian-Based Norm Regularization for Image Restoration With Biomedical Applications, IEEE Transactions on Image Processing, vol.21, issue.3, pp.983-995, 2012.
DOI : 10.1109/TIP.2011.2168232

J. Li, Z. Shen, R. Jin, and X. Zhang, A reweighted ? 2 method for image restoration with Poisson and mixed Poisson-Gaussian noise, tech. report, 2012

P. L. Lions and B. Mercier, Splitting Algorithms for the Sum of Two Nonlinear Operators, SIAM Journal on Numerical Analysis, vol.16, issue.6, pp.964-979, 1979.
DOI : 10.1137/0716071

F. Luisier, T. Blu, and M. Unser, Image Denoising in Mixed Poisson–Gaussian Noise, IEEE Transactions on Image Processing, vol.20, issue.3, pp.696-708, 2011.
DOI : 10.1109/TIP.2010.2073477

J. J. Moreau, Proximit?? et dualit?? dans un espace hilbertien, Bulletin de la Société mathématique de France, vol.79, pp.273-299, 1965.
DOI : 10.24033/bsmf.1625
URL : http://archive.numdam.org/article/BSMF_1965__93__273_0.pdf

F. Murtagh, J. Starck, and A. Bijaoui, Image restoration with noise suppression using a multiresolution support, Astron. Astrophys, vol.112, pp.179-189, 1995.

T. E. Nichols, J. Qi, E. Asma, and R. M. Leahy, Spatiotemporal reconstruction of list-mode PET data, IEEE Transactions on Medical Imaging, vol.21, issue.4, pp.396-404, 2002.
DOI : 10.1109/TMI.2002.1000263

N. Parikh and S. Boyd, Proximal algorithms, Foundations and Trends in Optimization, pp.123-231, 2013.

N. Pustelnik, C. Chaux, and J. Pesquet, Parallel Proximal Algorithm for Image Restoration Using Hybrid Regularization, IEEE Transactions on Image Processing, vol.20, issue.9, pp.2450-2462, 2011.
DOI : 10.1109/TIP.2011.2128335
URL : https://hal.archives-ouvertes.fr/hal-00826121

H. Raguet, J. Fadili, and G. Peyré, A Generalized Forward-Backward Splitting, SIAM Journal on Imaging Sciences, vol.6, issue.3, pp.1199-1226, 2013.
DOI : 10.1137/120872802
URL : https://hal.archives-ouvertes.fr/hal-00613637

A. Repetti, E. Chouzenoux, and J. Pesquet, A penalized weighted least squares approach for restoring data corrupted with signal-dependent noise, Proc. 20th Eur. Sig. Proc. Conf, pp.27-31, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00733786

R. T. Rockafellar, Monotone Operators and the Proximal Point Algorithm, SIAM Journal on Control and Optimization, vol.14, issue.5, pp.877-898, 1976.
DOI : 10.1137/0314056

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.60-259, 1992.
DOI : 10.1016/0167-2789(92)90242-F

S. Setzer, G. Steidl, and T. Teuber, Deblurring Poissonian images by split Bregman techniques, Journal of Visual Communication and Image Representation, vol.21, issue.3, pp.193-199, 2010.
DOI : 10.1016/j.jvcir.2009.10.006

D. L. Snyder, A. M. Hammoud, and R. L. White, Image recovery from data acquired with a charge-coupled-device camera, Journal of the Optical Society of America A, vol.10, issue.5, pp.1014-1023, 1993.
DOI : 10.1364/JOSAA.10.001014

P. Tseng, A Modified Forward-Backward Splitting Method for Maximal Monotone Mappings, SIAM Journal on Control and Optimization, vol.38, issue.2, pp.431-446, 2000.
DOI : 10.1137/S0363012998338806

B. C. V?uv?u, A splitting algorithm for dual monotone inclusions involving cocoercive operators, Adv. Comput. Math, vol.38, pp.667-681, 2013.

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, Image Quality Assessment: From Error Visibility to Structural Similarity, IEEE Transactions on Image Processing, vol.13, issue.4, pp.600-612, 2004.
DOI : 10.1109/TIP.2003.819861

Y. Xiao, T. Zeng, J. Yu, and M. K. Ng, Restoration of images corrupted by mixed Gaussian-impulse noise via ? 1 -? 0 minimization, Pattern Recogn, pp.44-1708, 2011.

M. Yan, Restoration of Images Corrupted by Impulse Noise and Mixed Gaussian Impulse Noise Using Blind Inpainting, SIAM Journal on Imaging Sciences, vol.6, issue.3, pp.1227-1245, 2013.
DOI : 10.1137/12087178X