S. Farsiu, D. Robinson, M. Elad, and P. Milanfar, Advances and challenges in super-resolution, International Journal of Imaging Systems and Technology, vol.19, issue.2, pp.47-57, 2004.
DOI : 10.1002/ima.20007

J. Tian and K. Ma, A survey on super-resolution imaging, Signal, Image and Video Processing, pp.329-342, 2011.
DOI : 10.1007/s11760-010-0204-6

M. Nikolova, A Variational Approach to Remove Outliers and Impulse Noise, Journal of Mathematical Imaging and Vision, vol.20, issue.1/2, pp.99-120, 2004.
DOI : 10.1023/B:JMIV.0000011920.58935.9c

S. Farsiu, M. D. Robinson, M. Elad, and P. Milanfar, Fast and Robust Multiframe Super Resolution, IEEE Transactions on Image Processing, vol.13, issue.10, pp.1327-1344, 2004.
DOI : 10.1109/TIP.2004.834669

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.2875

K. Yap, Y. He, Y. Tian, and L. Chau, A Nonlinear -Norm Approach for Joint Image Registration and Super- Resolution, Signal Processing Letters, IEEE, vol.16, pp.981-984, 2009.

Y. Traonmilin, S. Ladjal, and A. Almansa, On the amount of regularization for Super-Resolution interpolation, 20th European Signal Processing Conference 2012, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00824670

E. J. Candes and T. Tao, Decoding by linear programming Information Theory, IEEE Transactions on, vol.51, pp.4203-4215, 2005.

A. Cohen, W. Dahmen, and R. Devore, Compressed sensing and best $k$-term approximation, Journal of the American Mathematical Society, vol.22, issue.1, 2009.
DOI : 10.1090/S0894-0347-08-00610-3

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.148.5477

Y. Traonmilin, S. Ladjal, and A. Almansa, Outlier Removal Power of the L1-Norm Super-Resolution, Scale Space and Variational Methods in Computer Vision, pp.198-209, 2013.
DOI : 10.1007/978-3-642-38267-3_17

URL : https://hal.archives-ouvertes.fr/hal-00803695

I. Daubechies, R. Devore, M. Fornasier, and C. S. Güntürk, Iteratively reweighted least squares minimization for sparse recovery, Communications on Pure and Applied Mathematics, vol.58, issue.1, pp.1-38, 2010.
DOI : 10.1002/cpa.20303

F. Champagnat, G. L. Besnerais, and C. Kulcsár, Statistical performance modeling for superresolution: a discrete data-continuous reconstruction framework, Journal of the Optical Society of America A, vol.26, issue.7, pp.1730-1746, 2009.
DOI : 10.1364/JOSAA.26.001730