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2020 – today
- 2024
[i33]Utsav Akhaury, Pascale Jablonka, Jean-Luc Starck, Frédéric Courbin:
Ground-based image deconvolution with Swin Transformer UNet. CoRR abs/2405.07842 (2024)- 2023
- [j61]Zaccharie Ramzi
, Kevin Michalewicz, Jean-Luc Starck, Thomas Moreau, Philippe Ciuciu:
Wavelets in the Deep Learning Era. J. Math. Imaging Vis. 65(1): 240-251 (2023) - [i32]Tobías I. Liaudat, Jean-Luc Starck, Martin Kilbinger, Pierre-Antoine Frugier:
Point spread function modelling for astronomical telescopes: a review focused on weak gravitational lensing studies. CoRR abs/2306.07996 (2023) - [i31]Benjamin Naoto Chiche, Julien N. Girard, Joana Frontera-Pons, Arnaud Woiselle, Jean-Luc Starck:
Deep learning-based deconvolution for interferometric radio transient reconstruction. CoRR abs/2306.13909 (2023) - 2022
- [j60]Emma Tolley, D. Korber, A. Galan, Austin Peel, M. T. Sargent, Jean-Paul Kneib, Frédéric Courbin, Jean-Luc Starck:
Lightweight HI source finding for next generation radio surveys. Astron. Comput. 41: 100631 (2022) - [j59]Zaccharie Ramzi, Chaithya G. R., Jean-Luc Starck, Philippe Ciuciu:
NC-PDNet: A Density-Compensated Unrolled Network for 2D and 3D Non-Cartesian MRI Reconstruction. IEEE Trans. Medical Imaging 41(7): 1625-1638 (2022) - [c40]Benjamin Naoto Chiche, Arnaud Woiselle, Joana Frontera-Pons, Jean-Luc Starck:
Stable Long-Term Recurrent Video Super-Resolution. CVPR 2022: 827-836 - [c39]Zaccharie Ramzi, Florian Mannel, Shaojie Bai, Jean-Luc Starck, Philippe Ciuciu, Thomas Moreau:
SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models. ICLR 2022 - [c38]Yanis Guimard, Ming Jiang, Zhenghao Zhu, Huanyuan Shan, Jalal Fadili, Jean-Luc Starck:
Statistical and morphological component separation of foregrounds in convolved HI skymaps. SiPS 2022: 1-6 - [i30]Benjamin Remy, François Lanusse, Niall Jeffrey, Jia Liu, Jean-Luc Starck, Ken Osato, Tim Schrabback:
Probabilistic Mass Mapping with Neural Score Estimation. CoRR abs/2201.05561 (2022) - [i29]Tobías I. Liaudat, Jean-Luc Starck, Martin Kilbinger, Pierre-Antoine Frugier:
Rethinking data-driven point spread function modeling with a differentiable optical model. CoRR abs/2203.04908 (2022) - [i28]Denise Lanzieri, François Lanusse, Jean-Luc Starck:
Hybrid Physical-Neural ODEs for Fast N-body Simulations. CoRR abs/2207.05509 (2022) - 2021
- [j58]Matthew J. Muckley, Bruno Riemenschneider, Alireza Radmanesh, Sunwoo Kim, Geunu Jeong, Jingyu Ko, Yohan Jun, Hyungseob Shin, Dosik Hwang, Mahmoud Mostapha, Simon Arberet, Dominik Nickel, Zaccharie Ramzi, Philippe Ciuciu, Jean-Luc Starck, Jonas Teuwen, Dimitrios Karkalousos, Chaoping Zhang, Anuroop Sriram, Zhengnan Huang, Nafissa Yakubova, Yvonne W. Lui, Florian Knoll:
Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction. IEEE Trans. Medical Imaging 40(9): 2306-2317 (2021) - [c37]Zaccharie Ramzi, Jean-Luc Starck, Philippe Ciuciu:
Density Compensated Unrolled Networks For Non-Cartesian MRI Reconstruction. ISBI 2021: 1443-1447 - [i27]Zaccharie Ramzi, Philippe Ciuciu, Jean-Luc Starck:
Density Compensated Unrolled Networks for Non-Cartesian MRI Reconstruction. CoRR abs/2101.01570 (2021) - [i26]Benjamin Naoto Chiche, Arnaud Woiselle, Joana Frontera-Pons, Jean-Luc Starck:
Deep Unrolled Network for Video Super-Resolution. CoRR abs/2102.11720 (2021) - [i25]Zaccharie Ramzi, Florian Mannel, Shaojie Bai, Jean-Luc Starck, Philippe Ciuciu, Thomas Moreau:
SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models. CoRR abs/2106.00553 (2021) - [i24]Zaccharie Ramzi, Alexandre Vignaud, Jean-Luc Starck, Philippe Ciuciu:
Is good old GRAPPA dead? CoRR abs/2106.00753 (2021) - [i23]Tobías I. Liaudat, Jean-Luc Starck, Martin Kilbinger, Pierre-Antoine Frugier:
Rethinking the modeling of the instrumental response of telescopes with a differentiable optical model. CoRR abs/2111.12541 (2021) - [i22]Benjamin Naoto Chiche, Arnaud Woiselle, Joana Frontera-Pons, Jean-Luc Starck:
Stable Long-Term Recurrent Video Super-Resolution. CoRR abs/2112.08950 (2021) - 2020
- [j57]Samuel Farrens, Antoine Grigis, Loubna El Gueddari, Zaccharie Ramzi, Chaithya G. R., Sophie Starck, Benoît Sarthou, Hamza Cherkaoui, Philippe Ciuciu, Jean-Luc Starck:
PySAP: Python Sparse Data Analysis Package for multidisciplinary image processing. Astron. Comput. 32: 100402 (2020) - [j56]Khanh-Hung Tran, Fred Maurice Ngolè Mboula, Jean-Luc Starck, Vincent Prost:
Semisupervised Dictionary Learning with Graph Regularized and Active Points. SIAM J. Imaging Sci. 13(2): 724-745 (2020) - [j55]Radamanthys Stivaktakis, Grigorios Tsagkatakis, Bruno Moraes, Filipe B. Abdalla, Jean-Luc Starck, Panagiotis Tsakalides:
Convolutional Neural Networks for Spectroscopic Redshift Estimation on Euclid Data. IEEE Trans. Big Data 6(3): 460-476 (2020) - [c36]Zaccharie Ramzi, Jean-Luc Starck, Thomas Moreau, Philippe Ciuciu:
Wavelets in the Deep Learning Era. EUSIPCO 2020: 1417-1421 - [c35]Benjamin Naoto Chiche, Joana Frontera-Pons, Arnaud Woiselle, Jean-Luc Starck:
Deep Unrolled Network for Video Super-Resolution. IPTA 2020: 1-6 - [c34]Zaccharie Ramzi, Philippe Ciuciu, Jean-Luc Starck:
Benchmarking Deep Nets MRI Reconstruction Models on the Fastmri Publicly Available Dataset. ISBI 2020: 1441-1445 - [i21]Khanh-Hung Tran, Fred Maurice Ngolè Mboula, Jean-Luc Starck, Vincent Prost:
Semi-supervised dictionary learning with graph regularization and active points. CoRR abs/2009.05964 (2020) - [i20]Khanh-Hung Tran, Fred Maurice Ngolè Mboula, Jean-Luc Starck:
Manifold attack. CoRR abs/2009.05965 (2020) - [i19]Zaccharie Ramzi, Philippe Ciuciu, Jean-Luc Starck:
XPDNet for MRI Reconstruction: an Application to the fastMRI 2020 Brain Challenge. CoRR abs/2010.07290 (2020) - [i18]Zaccharie Ramzi, Benjamin Remy, François Lanusse, Jean-Luc Starck, Philippe Ciuciu:
Denoising Score-Matching for Uncertainty Quantification in Inverse Problems. CoRR abs/2011.08698 (2020) - [i17]Matthew J. Muckley, Bruno Riemenschneider, Alireza Radmanesh, Sunwoo Kim, Geunu Jeong, Jingyu Ko, Yohan Jun, Hyungseob Shin, Dosik Hwang, Mahmoud Mostapha, Simon Arberet, Dominik Nickel, Zaccharie Ramzi, Philippe Ciuciu, Jean-Luc Starck, Jonas Teuwen, Dimitrios Karkalousos, Chaoping Zhang, Anuroop Sriram, Zhengnan Huang, Nafissa Yakubova, Yvonne W. Lui, Florian Knoll:
State-of-the-Art Machine Learning MRI Reconstruction in 2020: Results of the Second fastMRI Challenge. CoRR abs/2012.06318 (2020)
2010 – 2019
- 2018
- [j54]Morgan A. Schmitz, Matthieu Heitz, Nicolas Bonneel, Fred Maurice Ngolè Mboula, David Coeurjolly, Marco Cuturi, Gabriel Peyré, Jean-Luc Starck:
Wasserstein Dictionary Learning: Optimal Transport-Based Unsupervised Nonlinear Dictionary Learning. SIAM J. Imaging Sci. 11(1): 643-678 (2018) - [c33]Hamza Cherkaoui, Loubna El Gueddari, Carole Lazarus, Antoine Grigis, Fabrice Poupon, Alexandre Vignaud, Samuel Farrens, Jean-Luc Starck, Philippe Ciuciu:
Analysis vs Synthesis-based Regularization for Combined Compressed Sensing and Parallel MRI Reconstruction at 7 Tesla. EUSIPCO 2018: 36-40 - [c32]Konstantinos E. Themelis, François Lanusse, Niall Jeffrey, Austin Peel, Jean-Luc Starck, Filipe B. Abdalla:
Modelling Data with both Sparsity and a Gaussian Random Field: Application to Dark Matter Mass Mapping in Cosmology. EUSIPCO 2018: 376-379 - [c31]Joana Frontera-Pons, Florent Sureau, Bruno Moraes, Jérôme Bobin, Filipe B. Abdalla, Jean-Luc Starck:
Dictionary Learning for Photometric Redshift Estimation. EUSIPCO 2018: 1740-1744 - [i16]Athanasia Panousopoulou, Samuel Farrens, Konstantina Fotiadou, Arnaud Woiselle, Grigorios Tsagkatakis, Jean-Luc Starck, Panagiotis Tsakalides:
A Distributed Learning Architecture for Scientific Imaging Problems. CoRR abs/1809.05956 (2018) - [i15]Julian Merten, Carlo Giocoli, Marco Baldi, Massimo Meneghetti, Austin Peel, Florian Lalande, Jean-Luc Starck, Valeria Pettorino:
On the dissection of degenerate cosmologies with machine learning. CoRR abs/1810.11027 (2018) - [i14]Khanh-Hung Tran, Fred Maurice Ngolè Mboula, Jean-Luc Starck:
Semi-supervised dual graph regularized dictionary learning. CoRR abs/1812.04456 (2018) - 2017
- [j53]Fred Maurice Ngolè Mboula, Jean-Luc Starck:
Point Spread Function Field Learning Based on Optimal Transport Distances. SIAM J. Imaging Sci. 10(3): 1549-1578 (2017) - [j52]Ming Jiang, Jérôme Bobin, Jean-Luc Starck:
Joint Multichannel Deconvolution and Blind Source Separation. SIAM J. Imaging Sci. 10(4): 1997-2021 (2017) - [c30]Athanasia Panousopoulou, Sammuel Farrens, Yiannis Mastorakis, Jean-Luc Starck, Panagiotis Tsakalides:
A distributed learning architecture for big imaging problems in astrophysics. EUSIPCO 2017: 1440-1444 - [i13]Ming Jiang, Jérôme Bobin, Jean-Luc Starck:
Joint Multichannel Deconvolution and Blind Source Separation. CoRR abs/1703.02650 (2017) - [i12]Fred Maurice Ngolè Mboula, Jean-Luc Starck:
PSF field learning based on Optimal Transport Distances. CoRR abs/1703.06066 (2017) - [i11]Morgan A. Schmitz, Matthieu Heitz, Nicolas Bonneel, Fred Maurice Ngolè Mboula, David Coeurjolly, Marco Cuturi, Gabriel Peyré, Jean-Luc Starck:
Wasserstein Dictionary Learning: Optimal Transport-based unsupervised non-linear dictionary learning. CoRR abs/1708.01955 (2017) - 2016
- [j51]Jérémy Rapin, Antoine Souloumiac, Jérôme Bobin, Anthony Larue, Christophe Junot, Minale Ouethrani, Jean-Luc Starck:
Application of non-negative matrix factorization to LC/MS data. Signal Process. 123: 75-83 (2016) - [i10]Fred Maurice Ngolè Mboula, Jean-Luc Starck, Koryo Okumura, Jérôme Amiaux, Patrick Hudelot:
Constraint matrix factorization for space variant PSFs field restoration. CoRR abs/1608.08104 (2016) - [i9]Vinayak Abrol, Olivier Absil, Pierre-Antoine Absil, Sandrine Anthoine, Philippe Antoine, Thomas Arildsen, Nancy Bertin, Folkert Bleichrodt, Jérôme Bobin, Anne Bol, Antoine Bonnefoy, Francesco Caltagirone, Valerio Cambareri, Cecile Chenot, Vladimir S. Crnojevic, Marie Danková, Kévin Degraux, Jens Eisert, Mohamed-Jalal Fadili, Marylou Gabrié, Nicolas Gac, Daniele Giacobello, Carlos A. Gomez Gonzalez, Adriana Gonzalez, Pierre-Yves Gousenbourger, Mads Græsbøll Christensen, Rémi Gribonval, Stéphanie Guérit, Shaoguang Huang, Paul Irofti, Laurent Jacques, Ulugbek S. Kamilov, Srdan Kitic, Martin Kliesch, Florent Krzakala, John A. Lee, Wenzhi Liao, Tobias Lindstrøm Jensen, Andre Manoel, Hassan Mansour, Ali Mohammad-Djafari, Amirafshar Moshtaghpour, Fred Maurice Ngolè Mboula, Benoît Pairet, Marko Panic, Gabriel Peyré, Aleksandra Pizurica, Pavel Rajmic, Matthieu Roblin, Ingo Roth, Anil Kumar Sao, Pulkit Sharma, Jean-Luc Starck, Eric W. Tramel, Toon van Waterschoot, Dejan Vukobratovic, Li Wang, Benedikt Wirth, Gerhard Wunder, Hongyan Zhang:
Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16). CoRR abs/1609.04167 (2016) - 2015
- [j50]Jérôme Bobin, Jérémy Rapin, Anthony Larue, Jean-Luc Starck:
Sparsity and Adaptivity for the Blind Separation of Partially Correlated Sources. IEEE Trans. Signal Process. 63(5): 1199-1213 (2015) - [c29]M. Jiang, Julien N. Girard, Jean-Luc Starck, S. Corbel, Cyril Tasse:
Compressed sensing and radio interferometry. EUSIPCO 2015: 1646-1650 - [c28]George Tzagkarakis, Panagiotis Tsakalides, Jean-Luc Starck:
Compressive Video Sensing with Adaptive Measurement Allocation for Improving MPEGx Performance. VISAPP (1) 2015: 254-259 - [r3]Jean-Luc Starck, Fionn Murtagh, Mario Bertero:
Starlet Transform in Astronomical Data Processing. Handbook of Mathematical Methods in Imaging 2015: 2053-2098 - 2014
- [j49]Jérémy Rapin, Jérôme Bobin, Anthony Larue, Jean-Luc Starck:
NMF with Sparse Regularizations in Transformed Domains. SIAM J. Imaging Sci. 7(4): 2020-2047 (2014) - [c27]Grigorios Tsagkatakis, Panagiotis Tsakalides, Arnaud Woiselle, Marc Bousquet, George Tzagkarakis, Jean-Luc Starck:
Compressed sensing reconstruction of convolved sparse signals. ICASSP 2014: 3340-3344 - [c26]Jérôme Bobin, Jean-Luc Starck, Jérémy Rapin, Anthony Larue:
Sparse blind source separation for partially correlated sources. ICIP 2014: 6021-6025 - [i8]Jérémy Rapin, Jérôme Bobin, Anthony Larue, Jean-Luc Starck:
NMF with Sparse Regularizations in Transformed Domains. CoRR abs/1407.7691 (2014) - [i7]Laurent Jacques, Christophe De Vleeschouwer, Yannick Boursier, Prasad Sudhakar, C. De Mol, Aleksandra Pizurica, Sandrine Anthoine, Pierre Vandergheynst, Pascal Frossard, Cagdas Bilen, Srdan Kitic, Nancy Bertin, Rémi Gribonval, Nicolas Boumal, Bamdev Mishra, Pierre-Antoine Absil, Rodolphe Sepulchre, Shaun Bundervoet, Colas Schretter, Ann Dooms, Peter Schelkens, Olivier Chabiron, François Malgouyres, Jean-Yves Tourneret, Nicolas Dobigeon, Pierre Chainais, Cédric Richard, Bruno Cornelis, Ingrid Daubechies, David B. Dunson, Marie Danková, Pavel Rajmic, Kévin Degraux, Valerio Cambareri, Bert Geelen, Gauthier Lafruit, Gianluca Setti, Jean-François Determe, Jérôme Louveaux, François Horlin, Angélique Drémeau, Patrick Héas, Cédric Herzet, Vincent Duval, Gabriel Peyré, Alhussein Fawzi, Mike E. Davies, Nicolas Gillis, Stephen A. Vavasis, Charles Soussen, Luc Le Magoarou, Jingwei Liang, Jalal Fadili, Antoine Liutkus, David Martina, Sylvain Gigan, Laurent Daudet, Mauro Maggioni, Stanislav Minsker, Nate Strawn, C. Mory, Fred Maurice Ngolè Mboula, Jean-Luc Starck, Ignace Loris, Samuel Vaiter, Mohammad Golbabaee, Dejan Vukobratovic:
Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14). CoRR abs/1410.0719 (2014) - [i6]Fred Maurice Ngolè Mboula, Jean-Luc Starck, Samuel Ronayette, Koryo Okumura, Jérôme Amiaux:
Super-resolution method using sparse regularization for point-spread function recovery. CoRR abs/1410.7679 (2014) - [i5]Jérôme Bobin, Jérémy Rapin, Anthony Larue, Jean-Luc Starck:
Sparsity and adaptivity for the blind separation of partially correlated sources. CoRR abs/1412.4005 (2014) - 2013
- [j48]George Tzagkarakis, Panagiotis Tsakalides, Jean-Luc Starck:
Covariation-based subspace-augmented MUSIC for joint sparse support recovery in impulsive environments. Signal Process. 93(5): 1365-1373 (2013) - [j47]Jérémy Rapin, Jérôme Bobin, Anthony Larue, Jean-Luc Starck:
Sparse and Non-Negative BSS for Noisy Data. IEEE Trans. Signal Process. 61(22): 5620-5632 (2013) - [c25]Jérémy Rapin, Jérôme Bobin, Anthony Larue, Jean-Luc Starck:
Sparse redundant formulations and non-negativity in Blind Source Separation. EUSIPCO 2013: 1-5 - [c24]George Tzagkarakis, Alin Achim, Panagiotis Tsakalides, Jean-Luc Starck:
Joint reconstruction of compressively sensed ultrasound RF echoes by exploiting temporal correlations. ISBI 2013: 632-635 - [i4]Simon Beckouche, Jean-Luc Starck, Jalal Fadili:
Astronomical Image Denoising Using Dictionary Learning. CoRR abs/1304.3573 (2013) - [i3]Jérémy Rapin, Jérôme Bobin, Anthony Larue, Jean-Luc Starck:
Sparse and Non-Negative BSS for Noisy Data. CoRR abs/1308.5546 (2013) - 2012
- [j46]David L. Donoho, Yaakov Tsaig, Iddo Drori, Jean-Luc Starck:
Sparse Solution of Underdetermined Systems of Linear Equations by Stagewise Orthogonal Matching Pursuit. IEEE Trans. Inf. Theory 58(2): 1094-1121 (2012) - [c23]George Tzagkarakis, Grigorios Tsagkatakis, Jean-Luc Starck, Panagiotis Tsakalides:
Compressive video classification in a low-dimensional manifold with learned distance metric. EUSIPCO 2012: 155-159 - [c22]George Tzagkarakis, Pavlos Charalampidis, Grigorios Tsagkatakis, Jean-Luc Starck, Panagiotis Tsakalides:
Compressive video classification for decision systems with limited resources. PCS 2012: 353-356 - [c21]George Tzagkarakis, Arnaud Woiselle, Panagiotis Tsakalides, Jean-Luc Starck:
Design of a Compressive Remote Imaging System Compensating a Highly Lightweight Encoding with a Refined Decoding Scheme. VISAPP (1) 2012: 46-55 - 2011
- [j45]Arnaud Woiselle, Jean-Luc Starck, Jalal Fadili:
3-D Data Denoising and Inpainting with the Low-Redundancy Fast Curvelet Transform. J. Math. Imaging Vis. 39(2): 121-139 (2011) - [j44]Jean-Luc Starck, Jalal Fadili, Michael Elad, Robert D. Nowak, Panagiotis Tsakalides:
Introduction to the issue on Adaptive Sparse Representation of Data and Applications in Signal and Image Processing. IEEE J. Sel. Top. Signal Process. 5(5): 893-895 (2011) - [c20]George Tzagkarakis, Jean-Luc Starck, Panagiotis Tsakalides:
Joint sparse signal ensemble reconstruction in a WSN using decentralized Bayesian matching pursuit. EUSIPCO 2011: 338-342 - [c19]Jérôme Bobin, Florent Sureau, Jean-Luc Starck:
Source separation in cosmology, from global to local models. ICIP 2011: 1297-1300 - [c18]François-Xavier Dupé, Mohamed-Jalal Fadili, Jean-Luc Starck:
Data augmentation for galaxy density map reconstruction. ICIP 2011: 1301-1304 - [c17]François-Xavier Dupé, Mohamed-Jalal Fadili, Jean-Luc Starck:
Inverse problems with poisson noise: Primal and primal-dual splitting. ICIP 2011: 1901-1904 - [c16]François-Xavier Dupé, Jalal Fadili, Jean-Luc Starck:
Linear inverse problems with various noise models and mixed regularizations. VALUETOOLS 2011: 621-626 - 2010
- [b3]Jean-Luc Starck, Fionn Murtagh, Mohamed-Jalal Fadili:
Sparse Image and Signal Processing - Wavelets, Curvelets, Morphological Diversity. Cambridge University Press 2010, ISBN 978-0-521-11913-9, pp. I-XVII, 1-316 - [j43]Mohamed-Jalal Fadili, Jean-Luc Starck, Michael Elad, David L. Donoho:
MCALab: Reproducible Research in Signal and Image Decomposition and Inpainting. Comput. Sci. Eng. 12(1): 44-63 (2010) - [j42]Mohamed-Jalal Fadili, Jean-Luc Starck, Jérôme Bobin, Yassir Moudden:
Image Decomposition and Separation Using Sparse Representations: An Overview. Proc. IEEE 98(6): 983-994 (2010) - [j41]Jean-Luc Starck, Jérôme Bobin:
Astronomical Data Analysis and Sparsity: From Wavelets to Compressed Sensing. Proc. IEEE 98(6): 1021-1030 (2010) - [j40]Gabriel Peyré, Jalal Fadili, Jean-Luc Starck:
Learning the Morphological Diversity. SIAM J. Imaging Sci. 3(3): 646-669 (2010) - [j39]Sandrine Pires, Jean-Luc Starck, Alexandre Refregier:
Light on dark matter with weak gravitational lensing. IEEE Signal Process. Mag. 27(1): 76-85 (2010)
2000 – 2009
- 2009
- [j38]Mohamed-Jalal Fadili, Jean-Luc Starck, Fionn Murtagh:
Inpainting and Zooming Using Sparse Representations. Comput. J. 52(1): 64-79 (2009) - [j37]Fionn Murtagh, Pedro Contreras, Jean-Luc Starck:
Scale-Based Gaussian Coverings: Combining Intra and Inter Mixture Models in Image Segmentation. Entropy 11(3): 513-528 (2009) - [j36]Jérôme Bobin, Yassir Moudden, Jalal Fadili, Jean-Luc Starck:
Morphological Diversity and Sparsity for Multichannel Data Restoration. J. Math. Imaging Vis. 33(2): 149-168 (2009) - [j35]François-Xavier Dupé, Mohamed-Jalal Fadili, Jean-Luc Starck:
A Proximal Iteration for Deconvolving Poisson Noisy Images Using Sparse Representations. IEEE Trans. Image Process. 18(2): 310-321 (2009) - [c15]Christophe Chesneau, Mohamed-Jalal Fadili, Jean-Luc Starck:
Image deconvolution by stein block thresholding. ICIP 2009: 1329-1332 - [c14]Jean-Luc Starck, Mohamed-Jalal Fadili:
An overview of inverse problem regularization using sparsity. ICIP 2009: 1453-1456 - [c13]Mohamed-Jalal Fadili, Jean-Luc Starck:
Monotone operator splitting for optimization problems in sparse recovery. ICIP 2009: 1461-1464 - [c12]Jérôme Bobin, Yassir Moudden, Jean-Luc Starck, Mohamed-Jalal Fadili:
Sparsity and morphological diversity for hyperspectral data analysis. ICIP 2009: 1481-1484 - [c11]Yassir Moudden, Jérôme Bobin, Jean-Luc Starck, Jalal Fadili:
Blind Source Separation with Spatio-SpectralSparsity Constraints - Application to Hyperspectral Data Analysis. ICA 2009: 523-531 - [r2]Jalal Fadili, Jean-Luc Starck:
Curvelets and Ridgelets. Encyclopedia of Complexity and Systems Science 2009: 1718-1738 - [r1]Jean-Luc Starck, Jalal Fadili:
Numerical Issues When Using Wavelets. Encyclopedia of Complexity and Systems Science 2009: 6352-6368 - [i2]Fionn Murtagh, Pedro Contreras, Jean-Luc Starck:
Scale-Based Gaussian Coverings: Combining Intra and Inter Mixture Models in Image Segmentation. CoRR abs/0909.0481 (2009) - 2008
- [j34]Jérôme Bobin, Jean-Luc Starck, Roland Ottensamer:
Compressed Sensing in Astronomy. IEEE J. Sel. Top. Signal Process. 2(5): 718-726 (2008) - [j33]Fionn Murtagh, Jean-Luc Starck:
Wavelet and curvelet moments for image classification: Application to aggregate mixture grading. Pattern Recognit. Lett. 29(10): 1557-1564 (2008) - [j32]Bo Zhang, Mohamed-Jalal Fadili, Jean-Luc Starck:
Wavelets, Ridgelets, and Curvelets for Poisson Noise Removal. IEEE Trans. Image Process. 17(7): 1093-1108 (2008) - [c10]François-Xavier Dupé, Mohamed-Jalal Fadili, Jean-Luc Starck:
Image deconvolution under poisson noise using sparse representations and proximal thresholding iteration. ICASSP 2008: 761-764 - [c9]François-Xavier Dupé, Mohamed-Jalal Fadili, Jean-Luc Starck:
Deconvolution of confocal microscopy images using proximal iteration and sparse representations. ISBI 2008: 736-739 - [i1]Fionn Murtagh, Jean-Luc Starck:
Wavelet and Curvelet Moments for Image Classification: Application to Aggregate Mixture Grading. CoRR abs/0802.3528 (2008) - 2007
- [j31]Jean-Luc Starck, Jalal Fadili, Fionn Murtagh:
The Undecimated Wavelet Decomposition and its Reconstruction. IEEE Trans. Image Process. 16(2): 297-309 (2007) - [j30]Jérôme Bobin, Jean-Luc Starck, Jalal Fadili, Yassir Moudden:
Sparsity and Morphological Diversity in Blind Source Separation. IEEE Trans. Image Process. 16(11): 2662-2674 (2007) - [j29]Jérôme Bobin, Jean-Luc Starck, Jalal Fadili, Yassir Moudden, David L. Donoho:
Morphological Component Analysis: An Adaptive Thresholding Strategy. IEEE Trans. Image Process. 16(11): 2675-2681 (2007) - [c8]Jérôme Bobin, Yassir Moudden, Jalal Fadili, Jean-Luc Starck:
Morphological Diversity and Sparsity in Blind Source Separation. ICA 2007: 349-356 - [c7]Mohamed-Jalal Fadili, Jean-Luc Starck, Larbi Boubchir:
Morphological Diversity and Sparse Image Denoising. ICASSP (1) 2007: 589-592 - [c6]Bo Zhang, Jalal Fadili, Jean-Luc Starck, Jean-Christophe Olivo-Marin:
Multiscale Variance-Stabilizing Transform for Mixed-Poisson-Gaussian Processes and its Applications in Bioimaging. ICIP (6) 2007: 233-236 - 2006
- [b2]Jean-Luc Starck, Fionn Murtagh:
Astronomical Image and Data Analysis, Second Edition. Astronomy and Astrophysics Library, Springer 2006, ISBN 978-3-540-33024-0, pp. I-XIV, 1-335 - [j28]D. Benaouda, Fionn Murtagh, Jean-Luc Starck, Olivier Renaud:
Wavelet-based nonlinear multiscale decomposition model for electricity load forecasting. Neurocomputing 70(1-3): 139-154 (2006) - [j27]Jérôme Bobin, Yassir Moudden, Jean-Luc Starck, Michael Elad:
Morphological diversity and source separation. IEEE Signal Process. Lett. 13(7): 409-412 (2006) - [c5]Bo Zhang, Mohamed-Jalal Fadili, Jean-Luc Starck:
Multi-Scale Variance Stabilizing Transform for Multi-Dimensional Poisson Count Image Denoising. ICASSP (2) 2006: 81-84 - [c4]Jérôme Bobin, Yassir Moudden, Jean-Luc Starck:
Enhanced Source Separation by Morphological Component Analysis. ICASSP (5) 2006: 833-836 - 2005
- [j26]