Thomas Oberlin
Thomas Oberlin
ISAE-SUPAERO, Université de Toulouse
Verified email at - Homepage
Cited by
Cited by
Time-frequency reassignment and synchrosqueezing: An overview
F Auger, P Flandrin, YT Lin, S McLaughlin, S Meignen, T Oberlin, HT Wu
IEEE Signal Processing Magazine 30 (6), 32-41, 2013
Second-order synchrosqueezing transform or invertible reassignment? Towards ideal time-frequency representations
T Oberlin, S Meignen, V Perrier
IEEE Transactions on Signal Processing 63 (5), 1335-1344, 2015
The Fourier-based synchrosqueezing transform
T Oberlin, S Meignen, V Perrier
2014 IEEE international conference on acoustics, speech and signal …, 2014
A new algorithm for multicomponent signals analysis based on synchrosqueezing: With an application to signal sampling and denoising
S Meignen, T Oberlin, S McLaughlin
IEEE transactions on Signal Processing 60 (11), 5787-5798, 2012
Theoretical analysis of the second-order synchrosqueezing transform
R Behera, S Meignen, T Oberlin
Applied and Computational Harmonic Analysis 45 (2), 379-404, 2018
An alternative formulation for the empirical mode decomposition
T Oberlin, S Meignen, V Perrier
IEEE Transactions on Signal Processing 60 (5), 2236-2246, 2012
The second-order wavelet synchrosqueezing transform
T Oberlin, S Meignen
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
Adaptive multimode signal reconstruction from time–frequency representations
S Meignen, T Oberlin, P Depalle, P Flandrin, S McLaughlin
Philosophical Transactions of the Royal Society A: Mathematical, Physical …, 2016
Synchrosqueezing transforms: From low-to high-frequency modulations and perspectives
S Meignen, T Oberlin, DH Pham
Comptes Rendus Physique 20 (5), 449-460, 2019
Bayesian EEG source localization using a structured sparsity prior
F Costa, H Batatia, T Oberlin, C d'Giano, JY Tourneret
NeuroImage 144, 142-152, 2017
The monogenic synchrosqueezed wavelet transform: a tool for the decomposition/demodulation of AM–FM images
M Clausel, T Oberlin, V Perrier
Applied and Computational Harmonic Analysis 39 (3), 450-486, 2015
The ASTRES toolbox for mode extraction of non-stationary multicomponent signals
D Fourer, J Harmouche, J Schmitt, T Oberlin, S Meignen, F Auger, ...
2017 25th European Signal Processing Conference (EUSIPCO), 1130-1134, 2017
Reduced-complexity end-to-end variational autoencoder for on board satellite image compression
V Alves de Oliveira, M Chabert, T Oberlin, C Poulliat, M Bruno, C Latry, ...
Remote Sensing 13 (3), 447, 2021
Hyperspectral and multispectral image fusion under spectrally varying spatial blurs–Application to high dimensional infrared astronomical imaging
C Guilloteau, T Oberlin, O Berné, N Dobigeon
IEEE Transactions on Computational Imaging 6, 1362-1374, 2020
Satellite image compression and denoising with neural networks
VA de Oliveira, M Chabert, T Oberlin, C Poulliat, M Bruno, C Latry, ...
IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2022
Factor analysis of dynamic PET images: beyond Gaussian noise
YC Cavalcanti, T Oberlin, N Dobigeon, C Févotte, S Stute, MJ Ribeiro, ...
IEEE transactions on medical imaging 38 (9), 2231-2241, 2019
Fast reconstruction of atomic-scale STEM-EELS images from sparse sampling
E Monier, T Oberlin, N Brun, X Li, M Tencé, N Dobigeon
Ultramicroscopy 215, 112993, 2020
Phase retrieval with Bregman divergences and application to audio signal recovery
PH Vial, P Magron, T Oberlin, C Févotte
IEEE Journal of Selected Topics in Signal Processing 15 (1), 51-64, 2021
Ordinal non-negative matrix factorization for recommendation
O Gouvert, T Oberlin, C Févotte
International Conference on Machine Learning, 3680-3689, 2020
A novel time-frequency technique for multicomponent signal denoising
T Oberlin, S Meignen, S McLaughlin
21st European Signal Processing Conference (EUSIPCO 2013), 1-5, 2013
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