M. Tegmark and A. De-oliveira-costa, Removing Point Sources from Cosmic Microwave Background Maps, The Astrophysical Journal, vol.500, issue.2, 1998.
DOI : 10.1086/311410

J. L. Sanz, D. Herranz, and E. Martínez-gónzalez, Optimal Detection of Sources on a Homogeneous and Isotropic Background, The Astrophysical Journal, vol.552, issue.2, pp.484-492, 2001.
DOI : 10.1086/320550

D. Herranz, J. L. Sanz, M. P. Hobson, R. B. Barreiro, J. M. Diego et al., Filtering techniques for the detection of Sunyaev-Zel'dovich clusters in multifrequency maps, Monthly Notices of the Royal Astronomical Society, vol.336, issue.4, pp.1057-1068, 2002.
DOI : 10.1046/j.1365-8711.2002.05704.x

D. Herranz and J. L. Sanz, Matrix Filters for the Detection of Extragalactic Point Sources in Cosmic Microwave Background Images, IEEE Journal of Selected Topics in Signal Processing, vol.2, issue.5, 2008.
DOI : 10.1109/JSTSP.2008.2005339

L. Cayón, J. L. Sanz, R. B. Barreiro, E. Martínez-gonzález, P. Vielva et al., Isotropic wavelets: a powerful tool to extract point sources from cosmic microwave background maps, Monthly Notices of the Royal Astronomical Society, vol.315, issue.4, pp.757-761, 2002.
DOI : 10.1046/j.1365-8711.2000.03462.x

J. González-nuevo, F. Argeso, M. López-caniego, L. Toffolatti, J. L. Sanz et al., The Mexican hat wavelet family: application to point-source detection in cosmic microwave background maps, Monthly Notices of the Royal Astronomical Society, vol.369, issue.4, pp.1603-1610, 2006.
DOI : 10.1111/j.1365-2966.2006.10442.x

M. López-caniego, D. Herranz, R. B. Barreiro, and J. L. Sanz, Filter design for the detection of compact sources based on the Neyman-Pearson detector, Monthly Notices of the Royal Astronomical Society, vol.359, issue.3, pp.993-1006, 2005.
DOI : 10.1111/j.1365-2966.2005.08961.x

M. López-caniego, D. Herranz, J. González-nuevo, R. B. Sanz, P. Vielva et al., Comparison of filters for the Fig

P. Carvalho, G. Rocha, M. P. Graca, and . Hobson, A fast bayesian approach to discrete object detection in astronomical datasets -powellsnakes i, " ArXiv e-prints, 2008.

J. Fuchs, Recovery of exact sparse representations in the prsence of noise, Acoustics, Speech, and Signal Processing, IEEE International Conference on, pp.533-536, 2004.

E. J. Candés, J. K. Romberg, and T. Tao, Stable signal recovery from incomplete and inaccurate measurements, Communications on Pure and Applied Mathematics, vol.7, issue.8, pp.1207-1223, 2006.
DOI : 10.1002/cpa.20124

J. Bobin, Y. Moudden, J. Starck, and M. Elad, Morphological diversity and source separation, IEEE Signal Processing Letters, vol.13, issue.7, pp.409-412, 2006.
DOI : 10.1109/LSP.2006.873141

URL : https://hal.archives-ouvertes.fr/hal-00196328

D. L. Donoho, M. Elad, and V. N. Temlyakov, Stable recovery of sparse overcomplete representations in the presence of noise, IEEE Transactions on Information Theory, vol.52, issue.1, pp.6-18, 2006.
DOI : 10.1109/TIT.2005.860430

J. A. Tropp, Just relax: convex programming methods for identifying sparse signals in noise, IEEE Transactions on Information Theory, vol.52, issue.3, pp.1030-1051, 2006.
DOI : 10.1109/TIT.2005.864420

A. K. Fletchera, S. Rangan, V. K. Goyal, and K. Ramchandran, Denoising by Sparse Approximation: Error Bounds Based on Rate-Distortion Theory, EURASIP Journal on Advances in Signal Processing, vol.6, issue.2, pp.1-19, 2006.
DOI : 10.1155/ASP/2006/26318

M. J. Wainwright, Sharp thresholds for high-dimensional and noisy recovery of sparsity, Proc. Allerton Conference on Communication, Control and Computing, 2006.

A. Blake and A. Zissermann, Visual Reconstruction, 1987.