C. Anil and . Kokaram, Line registration for jittered video In Motion Picture Restoration : Digital Algorithms for Artefact Suppression in Degraded Motion Picture Film and Video, pp.99-118

A. Kokaram, P. Rayner, P. Van-roosmalen, and J. Biemond, Line registration of jittered video, Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'97, pp.2553-2556, 1997.
DOI : 10.1109/icassp.1997.595309

L. Laborelli, Removal of video line jitter using a dynamic programming approach, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), pp.331-335, 2003.
DOI : 10.1109/ICIP.2003.1246684

J. Shen, Bayesian Video Dejittering by the BV Image Model, SIAM Journal on Applied Mathematics, vol.64, issue.5, pp.1691-1708, 2004.
DOI : 10.1137/S0036139902418699

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.192.638

S. H. Kang and J. Shen, Video dejittering by bake and shake, Image and Vision Computing, vol.24, issue.2, pp.143-152, 2006.
DOI : 10.1016/j.imavis.2005.09.022

P. Perona and J. Malik, Scale-space and edge detection using anisotropic diffusion, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.12, issue.7, pp.629-639, 1990.
DOI : 10.1109/34.56205

URL : http://authors.library.caltech.edu/6498/1/PERieeetpami90.pdf

S. H. Kang and J. Shen, Image Dejittering Based on Slicing Moments, Image Processing Based on Partial Differential Equations : Proceedings of the International Conference on PDE-Based Image Processing and Related Inverse Problems, pp.35-55, 2005.
DOI : 10.1007/978-3-540-33267-1_3

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.111.1006

M. Nikolova, One-iteration dejittering of digital video images, Journal of Visual Communication and Image Representation, vol.20, issue.4, pp.254-274, 2009.
DOI : 10.1016/j.jvcir.2009.03.004

M. Nikolova, Fast Dejittering for Digital Video Frames, Scale Space and Variational Methods in Computer Vision : Second International Conference Proceedings, pp.439-451, 2009.
DOI : 10.1137/S0036139902418699

F. Lenzen and O. Scherzer, Partial Differential Equations for Zooming, Deinterlacing and??Dejittering, International Journal of Computer Vision, vol.12, issue.5, pp.162-176, 2011.
DOI : 10.1007/3-540-31272-2_19

G. Huisken, Flow by mean curvature of convex surfaces into spheres, Journal of Differential Geometry, vol.20, issue.1, pp.237-266, 1984.
DOI : 10.4310/jdg/1214438998

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.413.6583

F. Catté, P. Lions, J. Morel, and T. Coll, Image Selective Smoothing and Edge Detection by Nonlinear Diffusion, SIAM Journal on Numerical Analysis, vol.29, issue.1, pp.182-193, 1992.
DOI : 10.1137/0729012

G. Dong, O. Aniello-raffaele-patrone, O. Scherzer, and . Öktem, Infinite Dimensional Optimization Models and PDEs for Dejittering, Scale Space and Variational Methods in Computer Vision : 5th International Conference Proceedings, pp.678-689, 2015.
DOI : 10.1007/978-3-319-18461-6_54

M. Ghodstinat, A. Bruhn, and J. Weickert, Deinterlacing with motioncompensated anisotropic diffusion, Statistical and Geometrical Approaches to Visual Motion Analysis : International Dagstuhl Seminar, pp.91-106, 2008.
DOI : 10.1007/978-3-642-03061-1_5

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.434.6014

S. Keller, F. Lauze, and M. Nielsen, A Total Variation Motion Adaptive Deinterlacing Scheme, Scale Space and PDE Methods in Computer Vision : 5th International Conference, Scale-Space 2005. Proceedings, pp.408-418, 2005.
DOI : 10.1007/11408031_35

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.92.4281

S. H. Keller, F. Lauze, and M. Nielsen, Deinterlacing Using Variational Methods, IEEE Transactions on Image Processing, vol.17, issue.11, pp.2015-2028, 2008.
DOI : 10.1109/TIP.2008.2003394

A. Almansa, V. Caselles, G. Haro, and B. Rougé, Restoration and Zoom of Irregularly Sampled, Blurred, and Noisy Images by Accurate Total Variation Minimization with Local Constraints, Multiscale Modeling & Simulation, vol.5, issue.1, pp.235-272, 2006.
DOI : 10.1137/050634086

G. Facciolo and A. Almansa, Irregular to Regular Sampling, Denoising, and Deconvolution, Multiscale Modeling & Simulation, vol.7, issue.4, pp.1574-1608, 2009.
DOI : 10.1137/080719443

URL : https://hal.archives-ouvertes.fr/hal-00988783

T. Brox and J. Malik, Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.3, pp.500-513, 2011.
DOI : 10.1109/TPAMI.2010.143

D. Fortun, P. Bouthemy, and C. Kervrann, Optical flow modeling and computation: A survey, Computer Vision and Image Understanding, vol.134, pp.1-21, 2015.
DOI : 10.1016/j.cviu.2015.02.008

URL : https://hal.archives-ouvertes.fr/hal-01104081

B. Mercier, Lectures on Topics in Finite Element Solution of Elliptic Problems, 1979.
DOI : 10.1007/978-3-662-00973-4

J. Eckstein and D. P. Bertsekas, On the Douglas???Rachford splitting method and the proximal point algorithm for maximal monotone operators, Mathematical Programming, pp.293-318, 1992.
DOI : 10.2140/pjm.1970.33.209

L. Patrick and . Combettes, Solving monotone inclusions via compositions of nonexpansive averaged operators. Optimization, pp.475-504, 2004.

L. Patrick, J. Combettes, and . Pesquet, Proximal Splitting Methods in Signal Processing, pp.185-212, 2011.

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 : 10.1007/978-3-540-74936-3_22

URL : https://hal.archives-ouvertes.fr/hal-00490826

L. Condat, A generic proximal algorithm for convex optimization ? application to total variation minimization, IEEE Signal Processing Letters, vol.21, issue.8, pp.985-989, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01120544

K. P. Berthold, B. G. Horn, and . Schunck, Determining optical flow, Artificial Intelligence, vol.17, issue.1, pp.185-203, 1981.

C. Zach, T. Pock, and H. Bischof, A Duality Based Approach for Realtime TV-L 1 Optical Flow, pp.214-223, 2007.
DOI : 10.1007/978-3-540-74936-3_22

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.135.1632

A. Wedel, T. Pock, C. Zach, H. Bischof, and D. Cremers, An Improved Algorithm for TV-L 1 Optical Flow, pp.23-45, 2009.
DOI : 10.1007/978-3-642-03061-1_2

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.4239

F. Steinbrücker, T. Pock, and D. Cremers, Large displacement optical flow computation without warping, Proc. IEEE 12th International Conference on Computer Vision, pp.1609-1614, 2009.

D. Geman and C. Yang, Nonlinear image recovery with half-quadratic regularization, IEEE Transactions on Image Processing, vol.4, issue.7, pp.932-946, 1995.
DOI : 10.1109/83.392335

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.53.7349

L. Patrick, . Combettes, R. Valã-c-rie, and . Wajs, Signal recovery by proximal forward-backward splitting, SIAM Multiscale Modeling & Simulation, vol.4, issue.4, pp.1168-1200, 2005.