E. , L. Pennec, and S. Mallat, Sparse geometrical image approximation with bandelets, IEEE Transaction on Image Processing, 2004.

M. Zibulevsky and B. A. Pearlmutter, Blind Source Separation by Sparse Decomposition in a Signal Dictionary, Neural Computation, vol.1, issue.4, pp.863-882, 2001.
DOI : 10.1016/S0042-6989(97)00169-7

J. Starck, E. J. Cands, and D. L. Donoho, The curvelet transform for image denoising, IEEE TRANSACTIONS ON IMAGE PROCESSING, vol.2, issue.6, pp.670-684, 2002.

S. Mallat and Z. Zhang, Matching pursuits with time-frequency dictionaries, IEEE Transactions on Signal Processing, vol.41, issue.12, pp.3397-3415, 1993.
DOI : 10.1109/78.258082
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.335.5769

Y. C. Pati, R. Rezaiifar, and P. S. Krishnaprasad, Orthonormal matching pursuit : recursive function approximation with applications to wavelet decomposition, Proceedings of the Annual Asilomar Conf. on Signals, Systems and Computers, 1993.

S. S. Chen, D. L. Donoho, and M. A. Saunders, Atomic decomposition by basis pursuit, SIAM Journal on Scientific Computing, vol.20, issue.1, pp.30-61, 1998.

I. F. Gorodnitsky and B. D. Rao, Sparse signal reconstruction from limited data using FOCUSS: a re-weighted minimum norm algorithm, IEEE Transactions on Signal Processing, vol.45, issue.3, pp.600-616, 1997.
DOI : 10.1109/78.558475

J. A. Tropp, Greed is Good: Algorithmic Results for Sparse Approximation, IEEE Transactions on Information Theory, vol.50, issue.10, 2003.
DOI : 10.1109/TIT.2004.834793

R. Gribonval and P. Vandergheynst, On the exponential convergence of matching pursuits in quasi-incoherent dictionaries, IEEE Transactions on Information Theory, vol.52, issue.1, 2004.
DOI : 10.1109/TIT.2005.860474
URL : https://hal.archives-ouvertes.fr/inria-00544945

J. A. Tropp, Just relax: Convex programming methods for subset selection and sparse approximation, Tech. Rep., Institute for Computational Engineering and Sciences (ICES), 2004.

D. Donoho, M. Elad, and V. Temlyakov, Stable recovery of sparse overcomplete representations in the presence of noise, IEEE Transactions on Information Theory, vol.52, issue.1, 2004.
DOI : 10.1109/TIT.2005.860430

R. Gribonval and M. Nielsen, Highly sparse representations from dictionaries are unique and independent of the sparseness measure, Applied and Computational Harmonic Analysis, vol.22, issue.3, 2003.
DOI : 10.1016/j.acha.2006.09.003
URL : https://hal.archives-ouvertes.fr/inria-00544779

R. Gribonval, R. M. Figueras, P. Ventura, and . Vandergheynst, A simple test to check the optimality of sparse signal approximations, Tech. Rep., IRISA, 2004.
URL : https://hal.archives-ouvertes.fr/inria-00564503