Publications

Sparse matrix factorization and blind source separation

Blind source separation

J.Bobin , J. Rapin, J.L. Starck and A. Larue, Sparsity and adaptivity for the blind separation of partially correlated sources, IEEE TSP, 63(5), 2015.

Y.Moudden and J.Bobin, Hyperspectral BSS using GMCA with spatio-spectral sparsity constraints – IEEE Transactions on image processing – Vol 20. Issue 3. pages 872-879 (2011).

J.Bobin, J.-L. Starck, J. Fadili, Y.Moudden, Sparsity and Morphological Diversity in Blind Source Separation, IEEE Transactions on Image Processing, Vol.16, N.11, p. 2662-2674, November 2007.

J. Bobin, Y. Moudden, J.-L. Starck and M. Elad, Morphological Diversity and Source Separation, IEEE Signal Processing Letters, Vol.13, N.7, p. 409-412, July 2006.

Sparse Non-Negative Matrix Factorization (NMF)

J.Rapin, J.Bobin, A. Larue and J.L. Starck, Sparse and non-negative BSS for noisy data, IEEE Tr. on signal processing, Vol. 61, Issue 22, 2013.

Robust BSS

C.Chenot, J.Bobin, , SIAM Imaging Science, Blind Source Separation with outliers in transformed domains, accepted, 2018.

C.Chenot, J.Bobin, Unsupervised separation of sparse sources in the presence of outliers, Signal Processing, in press, 2017.

C.Chenot, J.Bobin, J.Rapin, Robust sparse blind source separation, IEEE Sig. Proc. Letters, in press, 2015.

BSS in the large-scale regime

C. Kervazo, J.Bobin, C.Chenot, Blind separation of a large number of sparse sources, revised, 2017.


Sparsity and signal processing

S.R. Becker, J.Bobin and E. Candes, Nesta: a fast and accurate first-order method for compressed sensing – 2009 – SIAM Journal of Imaging Science, Vol 4 #11 (2011). 

J.-L. Starck and J.Bobin, Astronomical Data Analysis and Sparsity: from Wavelets to Compressed Sensing – 2009 – proceedings of the IEEE, special issue – Vol 98 – Issue 5 (2010).

J. Fadili, J.-L. Starck, J.Bobin and Y. Moudden, Image decomposition and separation using sparse representations: an overview – 2009 – proceedings of the IEEE, special issue – Vol 98 – Issue 5 (2010).
J.-L. Starck, Y.Moudden and J.Bobin, Polarized Wavelets and Curvelets on the sphere – A&A – 2009.
J.Bobin, J.-L. Starck and R. Ottensamer, Compressed Sensing in Astronomy, IEEE Journal of Selected Topics in Signal Processing, 2008 – in press.
J.Bobin, Y.Moudden, J. Fadili, J.-L. Starck, Morphological Diversity and Sparsity for Multivariate Data Restoration, Journal of Mathematical Imaging and Vision, 2008 – in press.
J.Bobin, J.-L. Starck, J. Fadili, Y. Moudden, and D.L. Donoho, Morphological Component Analysis : An Adaptive Thresholding Strategy, IEEE Transactions on Image Processing, Vol.16, N.11, p. 2675-2681, November 2007.
P.Abrial, Y. Moudden, J.L. Starck, J. Bobin, M.J. Fadili, B. Afeyan and M. Nguyen, Morphological Component Analysis and Inpainting on the Sphere: Application in Physics and Astrophysics,  Journal of Fourier Analysis and Applications  (JFAA), special issue on “Analysis on the Sphere”, Vol.13, N.6, pp 729-748, 2007.

Applications in cosmology and astrophysics

Cosmological microwave background

J.Bobin, F.Sureau, J-L Starck, CMB estimation from the WMAP and Planck PR2 data, A&A, revised, 2016.

J.Bobin, F.Sureau, J.-L. Starck, Polarized CMB map recovery with sparse component separation, A&A, in press, 2015.

A.Rassat, J-L Starck, P. Paykari, F. Sureau and J.Bobin, Planck CMB anomalies: astrophysical and cosmological foregrounds and the curse of masking, A&A, 2014.

P.Paykari, F.Lanusse, J.L. Starck, F.Sureau and J.Bobin, PRISM : Sparse recovery of the primordial power spectrum, A&A, 2014.
J.Bobin, F. Sureau,  J.L. Starck, A. Rassat and P. Paykari, Joint Planck and WMAP CMB map reconstruction, A&A, 563, A105, 2014.
J. Bobin, F. Sureau, P.Paykari, A. Rassat, S. Basak and J.L. Starck, WMAP nine-year CMB estimation using sparsity, A&A, 553, L4, 2013.

J.Bobin, J.-L. Starck, F. Sureau and S. Basak, Sparse component separation for accurate CMB map estimation, A&A, 550, K.2013.

J. Bobin, J.-L. Starck, F. Sureau, and J. Fadili, CMB Map restoration, Advances in Astronomy Vol. 2012.
L. Perotto, J. Bobin, S. Plaszczynski, J.-L. Starck, A. Lavabre, Reconstruction of the cosmic microwave background lensing for Planck, A&A – 2009.
S.M.Leach, J.-F.Cardoso, C.Baccigalupi, R.B.Barreiro, M.Betoule, J.Bobin, A.Bonaldi, G.de Zotti, J.Delabrouille, C.Dickinson, H.K.Eriksen, J.Gonzalez-Nuevo, F.K.Hansen, D.Herranz, M.LeJeune, M.Lopez-Caniego, E.Martinez-Gonzalez, M.Massardi, J.-B.Melin, M.-A.Miville-Deschenes, G.Patanchon, S.Prunet, S.Ricciardi, E.Salerno, J.L.Sanz, J.-L.Starck, F.Stivoli, V.Stolyarov, R.Stompor and P.Vielva, Component separation methods for the Planck mission, Astronomy and Astrophysics, 2008 – in press.
J.Bobin, Y.Moudden, J.-L. Starck, J. Fadili, N. Aghanim, SZ and CMB reconstruction using GMCA, Statistical Methodology, 2008 – Vol. 4, p.307-317.

Astrophysical foregrounds

M. Irfan, J.Bobin, Sparse estimation of model-based diffuse thermal dust emission, MNRAS, in press, 2017.

F. Sureau,  J.L. Starck, J.Bobin, P. Paykari A. Rassat, Sparse point-source removal for full-sky CMB experiments: application to WMAP 9-year data, A&A, In press, 2014.

Radio-interferometry

M. Jiang, J.Bobin, J-L Starck, Joint Multichannel Deconvolution and Blind Source Separation, SIAM Imaging Science, in press, 2017.

E.Chapman, A.Bonaldi, G.Harker, V.Jelic, F.Abdalla, G.Bernardi, J.Bobin, F.Dulwich, B.Mort, M.Santos and J-L.Starck Cosmic dawn and Epoch of Reionization foreground removal with the SKA, accepted to the SKA science book ‘Advancing astrophysics with the Square Kilometre Array’, 2015.

E. Chapman, F. Abdalla, J.Bobin, J.L. Starck, G. Harker, V. Jelic, P. Labropoulos, S. Zaroubi, M. Brentjens, A. De Bruyn and L. Koopmanx, The scale of the problem: recovering images of reionization with GMCA, MNRAS, 459, 2013

Weak lensing

A. Pujol, F. Sureau, J.Bobin, M. Gentile, F. Courbin, M.Kilbinger, Shear measurement bias: dependencies on methods, simulation parameters and measured parameters, A&A, in revision, 2017.

Applications of machine learning in astrophysics

M. Frontera-Pons, F.Sureau, J.Bobin, E Le Floc’h, Unsupervised feature learning for galaxy SEDs with denoising autoencoders, A&A, 603, A60, 2017.


Applications in bio-medical signal processing

J.Rapin, A.Souloumiac, J.Bobin, A.Larue, C.Junot, M.Ouethrani, J-L Starck, Application of NMF to LC/MS data, submitted to Signal Processing, accepted, 2015.

Applications in optical signal processing

J.Fade, E. Perrotin, J.Bobin, Two-pixel polarimetric camera by compressive sensing, Applied Optics, in press, 2017.

V. Studer, J. Bobin, M. Chahid, H. Mousavi, E. Candes, and M. Dahan, Compressive fluorescence microscopy for biological and hyperspectral imaging, PNAS 2012 109 (26).


Book chapter :

J.Bobin, J.-L. Starck, Y.Moudden, J. Fadili, Blind Source Separation: the Sparsity Revolution, Advances in Imaging and

Electron Physics, Vol. 152, p. 221-298 – Peter W. Hawkes Ed. – 2008.

Misc :

Technical report :

S.Ben Hadj, J.Bobin, A. Woiselle, Local subspace projection-based anomaly detection for complex multi-spectral images, Technical report – CEA Saclay, 2015.

R.Lguensat, J. Bobin, F.Sureau, Non-linear optimization under sparsity constraint, Technical report – CEA Saclay, September 2014.

Q.Leone, E. LeFloch, J.Bobin, A new method for galaxy classification, an application to cluster detection, Technical report – CEA Saclay, July 2014.

J. Bobin, Y. Zheng, Multichannel data analysis via sparse/low rank matrix decomposition, Technical report – CEA Saclay, June 2011.

J. Bobin, J.-L. Starck, Compressed Sensing for Hershel, Technical report – CEA Saclay, September 2006.

PhD dissertation (in French):

J.Bobin, Diversite morphologique et analyse de donnees multivaluees (morphological diversity and multivalued data analysis) – 2008.

HDR dissertation (in French): 

J.Bobin, De la parcimonie pour l’analyse de données multispectrales et ses applications en cosmologie, 2015