Publications

2017

• Large Scale Density-friendly Graph Decomposition via Convex Programming
  
  • Danisch Maximilien
  • Chan T-H. Hubert
  • Sozio Mauro
  , 2017.
• Robust dynamic range computation for high dynamic range content
  
  • Hulusic Vedad
  • Valenzise Giuseppe
  • Debattista Kurt
  • Dufaux Frederic
  , 2017. High dynamic range (HDR) imaging has become an important topic in both academic and industrial domains. Nevertheless, the concept of dynamic range (DR), which underpins HDR, and the way it is measured are still not clearly understood. The current approach to measure DR results in a poor correlation with perceptual scores (r ≈ 0.6). In this paper, we analyze the limitations of the existing DR measure, and propose several options to predict more accurately subjective DR judgments. Compared to the traditional DR estimates, the proposed measures show significant improvements in Spearman's and Pearson's correlations with subjective data (up to r ≈ 0.9). Despite their straightforward nature, these improvements are particularly evident in specific cases, where the scores obtained by using the classical measure have the highest error compared to the perceptual mean opinion score.
• Planck intermediate results - L. Evidence of spatial variation of the polarized thermal dust spectral energy distribution and implications for CMB B-mode analysis
  
  • Aghanim N.
  • Ashdown M.
  • Aumont J.
  • Baccigalupi C.
  • Ballardini M.
  • Banday A.J.
  • Barreiro R.B.
  • Bartolo N.
  • Basak S.
  • Benabed K.
  • Bernard Jean-Paul
  • Bersanelli M.
  • Bielewicz P.
  • Bonaldi A.
  • Bonavera L.
  • Bond J.R.
  • Borrill J.
  • Bouchet F.R.
  • Boulanger F.
  • Bracco A.
  • Burigana C.
  • Calabrese E.
  • Cardoso J.F.
  • Chiang H.C.
  • Colombo L.P.L.
  • Combet C.
  • Comis B.
  • Crill B.P.
  • Curto A.
  • Cuttaia F.
  • Davis R.J.
  • de Bernardis P.
  • de Rosa A.
  • de Zotti G.
  • Delabrouille J.
  • Delouis J. M.
  • Di Valentino E.
  • Dickinson C.
  • Diego J.M.
  • Dore O.
  • Douspis M.
  • Ducout A.
  • Dupac X.
  • Dusini S.
  • Efstathiou G.
  • Elsner F.
  • Ensslin T.A.
  • Eriksen H.K.
  • Falgarone E.
  • Fantaye Y.
  • Finelli F.
  • Frailis M.
  • Fraisse A.A.
  • Franceschi E.
  • Frolov A.
  • Galeotta S.
  • Galli S.
  • Ganga K.
  • Genova-Santos R.T.
  • Gerbino M.
  • Ghosh T.
  • Giard M.
  • Gonzalez-Nuevo J.
  • Gorski K.M.
  • Gregorio A.
  • Gruppuso A.
  • Gudmundsson J.E.
  • Hansen F.K.
  • Helou G.
  • Herranz D.
  • Hivon E.
  • Huang Z.
  • Jaffe A.H.
  • Jones W.C.
  • Keihanen E.
  • Keskitalo R.
  • Kisner T.S.
  • Krachmalnicoff N.
  • Kunz M.
  • Kurki-Suonio H.
  • Lagache G.
  • Lahteenmaki A.
  • Lamarre J.M.
  • Lasenby A.
  • Lattanzi M.
  • Lawrence C.R.
  • Le Jeune M.
  • Levrier F.
  • Liguori M.
  • Lilje P.B.
  • Lopez-Caniego M.
  • Lubin P.M.
  • Macias-Perez J.F.
  • Maggio G.
  • Maino D.
  • Mandolesi N.
  • Mangilli A.
  • Maris M.
  • Martin P.G.
  • Martinez-Gonzalez E.
  • Matarrese S.
  • Mauri N.
  • Mcewen J.D.
  • Melchiorri A.
  • Mennella A.
  • Migliaccio M.
  • Mitra S.
  • Miville-Deschenes M.A.
  • Molinari D.
  • Moneti A.
  • Montier L.
  • Morgante G.
  • Moss A.
  • Naselsky P.
  • Norgaard-Nielsen H.U.
  • Oxborrow C.A.
  • Pagano L.
  • Paoletti D.
  • Partridge B.
  • Patrizii L.
  • Perdereau O.
  • Perotto L.
  • Pettorino V.
  • Piacentini F.
  • Plaszczynski S.
  • Polenta G.
  • Puget J.L.
  • Rachen J.P.
  • Reinecke M.
  • Remazeilles M.
  • Renzi A.
  • Rocha G.
  • Rossetti M.
  • Roudier G.
  • Rubino-Martin J.A.
  • Ruiz-Granados B.
  • Salvati L.
  • Sandri M.
  • Savelainen M.
  • Scott D.
  • Sirignano C.
  • Sirri G.
  • Stanco L.
  • Suur-Uski A.S.
  • Tauber J.A.
  • Tenti M.
  • Toffolatti L.
  • Tomasi M.
  • Tristram M.
  • Trombetti T.
  • Valiviita J.
  • Vansyngel F.
  • van Tent F.
  • Vielva P.
  • Wandelt B.D.
  • Wehus I.K.
  • Zacchei A.
  • Zonca A.
  Astronomy & Astrophysics - A&A, EDP Sciences, 2017, 599, pp.A51. The characterization of the Galactic foregrounds has been shown to be the main obstacle in thechallenging quest to detect primordial B-modes in the polarized microwave sky. We make use of the Planck-HFI 2015 data release at high frequencies to place new constraints on the properties of the polarized thermal dust emission at high Galactic latitudes. Here, we specifically study the spatial variability of the dust polarized spectral energy distribution (SED), and its potential impact on the determination of the tensor-to-scalar ratio, r. We use the correlation ratio of the CBBℓ angular power spectra between the 217 and 353 GHz channels as a tracer of these potential variations, computed on different high Galactic latitude regions, ranging from 80% to 20% of the sky. The new insight from Planck data is a departure of the correlation ratio from unity that cannot be attributed to a spurious decorrelation due to the cosmic microwave background, instrumental noise, or instrumental systematics. The effect is marginally detected on each region, but the statistical combination of all the regions gives more than 99% confidence for this variation in polarized dust properties. In addition, we show that the decorrelation increases when there is a decrease in the mean column density of the region of the sky being considered, and we propose a simple power-law empirical model for this dependence, which matches what is seen in the Planck data. We explore the effect that this measured decorrelation has on simulations of the BICEP2-Keck Array/Planck analysis and show that the 2015 constraints from these data still allow a decorrelation between the dust at 150 and 353 GHz that is compatible with our measured value. Finally, using simplified models, we show that either spatial variation of the dust SED or of the dust polarization angle are able to produce decorrelations between 217 and 353 GHz data similar to the values we observe in the data. Key words: cosmic background radiation / cosmology: observations / submillimeter: ISM / dust, extinction⋆ Corresponding author: L. Montier, e-mail: Ludovic.Montier@irap.omp.eu; J. Aumont, e-mail: jonathan.aumont@ias.u-psud.fr (10.1051/0004-6361/201629164)
  DOI : 10.1051/0004-6361/201629164
• Very high resolution and interferometric SAR: Markovian and patch-based non-local mathematical models
  
  • Deledalle Charles-Alban
  • Denis Loïc
  • Ferraioli Giampaolo
  • Pascazio Vito
  • Schirinzi Gilda
  • Tupin Florence
  , 2017. This chapter is dedicated to very high resolution (VHR) SAR imagery, including interferometric applications. First, the principles of SAR data acquisition are presented as well as the different types of configurations. The widely adopted Gaussian complex model of fully developed speckle is described as well as more advanced statistical models for VHR SAR data that account for textures. The following two parts are devoted to SAR image estimation and to image denoising within two different frameworks. First, Markovian modeling is introduced and the associated optimization approaches are presented, including graph-cut based optimization. The second framework is the patch-based non-local modeling of SAR complex data. Both frameworks are adapted to SAR images through the use of statistical models specific to SAR imagery. Their applications to amplitude data, interferometry, and fusion with optical data are illustrated. A special focus is given to phase unwrapping applied to single and multi- channel interferometry, showing the usefulness of local and global contextual models. (10.1007/978-3-319-66330-2)
  DOI : 10.1007/978-3-319-66330-2
• Parallel Combining: Making Use of Free Cycles
  
  • Aksenov Vitaly
  • Kuznetsov Petr
  Computing Research Repository, ACM / ArXiv, 2017, abs/1710.07588.
• Classification of MRI data using deep learning and Gaussian process-based model selection
  
  • Bertrand Hadrien
  • Perrot Matthieu
  • Ardon Roberto
  • Bloch Isabelle
  , 2017, pp.745-748. The classification of MRI images according to the anatomical field of view is a necessary task to solve when faced with the increasing quantity of medical images. In parallel, advances in deep learning makes it a suitable tool for computer vision problems. Using a common architecture (such as AlexNet) provides quite good results, but not sufficient for clinical use. Improving the model is not an easy task, due to the large number of hyper-parameters governing both the architecture and the training of the network, and to the limited understanding of their relevance. Since an exhaustive search is not tractable, we propose to optimize the network first by random search, and then by an adaptive search based on Gaussian Processes and Probability of Improvement. Applying this method on a large and varied MRI dataset, we show a substantial improvement between the baseline network and the final one (up to 20% for the most difficult classes).
• Optimal two-step prediction in regression
  
  • Chételat Didier
  • Lederer Johannes
  • Salmon Joseph
  Electronic Journal of Statistics, Shaker Heights, OH : Institute of Mathematical Statistics, 2017, 11 (1), pp.2519-2546.
• Demonstration of 16QAM-OFDM UDWDM Transmission Using a Tunable Optical Flat Comb Source
  
  • Hraghi Abir
  • Chaibi Mohamed E.
  • Menif Mourad
  • Erasme Didier
  Journal of Lightwave Technology, Institute of Electrical and Electronics Engineers (IEEE)/Optical Society of America(OSA), 2017, 35 (2), pp.238-245. A new approach for designing broad and flattened spectrum multicarriers optical sources is presented leading to a 32 spectral lines source using a dual-arm Mach-Zehnder modulator (MZM) and a 41 spectral lines source from two-stage MZM. A modified simulated annealing-based optimization method is applied to derive the necessary settings allowing the optical flat comb source (OFCS) to be ultraflat. The OFCS is mooted as a technology to enhance the overall capacity of an access optical network by increasing the number of WDM channels. Here, we demonstrate an ultra-dense WDM (UDWDM) trans- mission for application to passive optical networks (PON) with (11x12.5Gbps) Quadrature Amplitude Modulation (QAM) based on a 4b/s/Hz spectral efficiency orthogonal frequency division multiplex (16QAM-OFDM) transmitter and direct detection. We use an OFCS to generate the 11 subcarriers spaced by 6.25GHz, made of a two-stage MZM. We study the performance of 3 filtered channels in terms of error vector magnitude (EVM) in back-to-back (B-to-B) conditions and after propagation through 25km and 100km standard single mode fiber (SSMF). (10.1109/JLT.2016.2636442)
  DOI : 10.1109/JLT.2016.2636442
• Parametric models of phase-amplitude coupling in neural time series
  
  • Dupré La Tour Tom
  • Grenier Yves
  • Gramfort Alexandre
  , 2017.
• Physical attacks
  
  • El Mrabet Nadia
  • Goubin Louis
  • Fournier Jacques Jean-Alain
  • Jauvart Damien
  • Guilley Sylvain
  • Moreau Martin
  • Rauzy Pablo
  • Rondepierre Franck
  , 2017.
• Yet another proof of the entropy power inequality
  
  • Rioul Olivier
  IEEE Transactions on Information Theory, Institute of Electrical and Electronics Engineers, 2017, 63 (6), pp.3595-3599. Yet another simple proof of the entropy power inequality is given, which avoids both the integration over a path of Gaussian perturbation and the use of Young’s inequality with sharp constant or Rényi entropies. The proof is based on a simple change of variables, is formally identical in one and several dimensions, and easily settles the equality case. (10.1109/TIT.2017.2676093)
  DOI : 10.1109/TIT.2017.2676093
• Formal Semantics of Behavior Specifications in the Architecture Analysis and Design Language Standard
  
  • Besnard Loic
  • Gautier Thierry
  • Le Guernic Paul
  • Guy Clément
  • Talpin Jean-Pierre
  • Larson Brian
  • Borde Etienne
  , 2017. (10.1007/978-981-10-4436-6_3)
  DOI : 10.1007/978-981-10-4436-6_3
• Les Communications par Fibres Optiques : La Fin de l'Age de Cuivre
  
  • Gallion Philippe
  , 2017, pp.8.
• Dynamic mitigation of EDFA power excursions with machine learning
  
  • Huang Yishen
  • Gutterman Craig L.
  • Samadi Payman
  • Cho Patricia B.
  • Samoud Wiem
  • Ware Cédric
  • Lourdiane Mounia
  • Zussman Gil
  • Bergman Keren
  Optics Express, Optical Society of America - OSA Publishing, 2017, 25 (3), pp.2245 - 2258. Dynamic optical networking has promising potential to support the rapidly changing traffic demands in metro and long-haul networks. However, the improvement in dynamicity is hindered by wavelength-dependent power excursions in gain-controlled erbium doped fiber amplifiers (EDFA) when channels change rapidly. We introduce a general approach that leverages machine learning (ML) to characterize and mitigate the power excursions of EDFA systems with different equipment and scales. An ML engine is developed and experimentally validated to show accurate predictions of the power dynamics in cascaded EDFAs. Recommended channel provisioning based on the ML predictions achieves within 1% error of the lowest possible power excursion over 94% of the time. We also showcase significant mitigation of EDFA power excursions in super-channel provisioning when compared to the first-fit wavelength assignment algorithm (10.1364/OE.25.002245)
  DOI : 10.1364/OE.25.002245
• Robust Downbeat Tracking Using an Ensemble of Convolutional Networks
  
  • Durand Simon
  • Bello Juan Pablo
  • David Bertrand
  • Richard Gael
  IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2017, 25 (1), pp.76-89. <div><p>In this paper, we present a novel state of the art system for automatic downbeat tracking from music signals. The audio signal is first segmented in frames which are synchronized at the tatum level of the music. We then extract different kind of features based on harmony, melody, rhythm and bass content to feed convolutional neural networks that are adapted to take advantage of the characteristics of each feature. This ensemble of neural networks is combined to obtain one downbeat likelihood per tatum. The downbeat sequence is finally decoded with a flexible and efficient temporal model which takes advantage of the assumed metrical continuity of a song. We then perform an evaluation of our system on a large base of 9 datasets, compare its performance to 4 other published algorithms and obtain a significant increase of 16.8 percent points compared to the second best system, for altogether a moderate cost in test and training. The influence of each step of the method is studied to show its strengths and shortcomings.</p></div> (10.1109/TASLP.2016.2623565)
  DOI : 10.1109/TASLP.2016.2623565
• Parameter estimation of perfusion models in dynamic contrast-enhanced imaging: a unified framework for model comparison
  
  • Romain Blandine
  • Rouet Laurence
  • Ohayon Daniel
  • Lucidarme Olivier
  • d'Alché-Buc Florence
  • Letort Véronique
  Medical Image Analysis, Elsevier, 2017, 35, pp.360--374. Patients follow-up in oncology is generally performed through the acquisition of dynamic sequences of contrast-enhanced images. Estimating parameters of appropriate models of contrast intake diffusion through tissues should help characterizing the tumour physiology. However, several models have been developed and no consensus exists on their clinical use. In this paper, we propose a unified framework to analyse models of perfusion and estimate their parameters in order to obtain reliable and relevant parametric images. After defining the biological context and the general form of perfusion models, we propose a methodological framework for model assessment in the context of parameter estimation from dynamic imaging data: global sensitivity analysis, structural and practical identifiability analysis, parameter estimation and model comparison. Then, we apply our methodology to five of the most widely used compartment models (Tofts model, extended Tofts model, two-compartment model, tissue-homogeneity model and distributed-parameters model) and illustrate the results by analysing the behaviour of these models when applied to data acquired on five patients with abdominal tumours. (10.1016/j.media.2016.07.008)
  DOI : 10.1016/j.media.2016.07.008
• Déborder l'expérience pour laisser une trace. Vidéophénoménographie d'un rappeur
  
  • Kneubühler Marine
  , 2017, pp.147-242.
• On some bounds for symmetric tensor rank of multiplication in finite fields
  
  • Ballet Stéphane
  • Pieltant Julia
  • Rambaud Matthieu
  • Sijsling Jeroen
  , 2017, 686, pp.93 - 121. We establish new upper bounds about symmetric bilinear complexity in any extension of finite fields. Note that these bounds are not asymptotical but uniform. Moreover, we discuss the validity of certain published bounds. (10.1090/conm/686/13779)
  DOI : 10.1090/conm/686/13779
• Conception d'absorbants à base de métasurfaces et Application de la Transformation d'Espace pour le contrôle du rayonnement d’une antenne imprimée
  
  • Lepage A. C.
  • Begaud Xavier
  , 2017.
• LISP EID Block
  
  • Iannone Luigi
  • Lewis Darrel
  • Meyer Dave
  • Fuller Vince
  , 2017.
• On perturbed proximal gradient algorithms
  
  • Atchadé Yves
  • Fort Gersende
  • Moulines Éric
  Journal of Machine Learning Research, Microtome Publishing, 2017, 18 (10), pp.1-33.
• Planck intermediate results. LI. Features in the cosmic microwave background temperature power spectrum and shifts in cosmological parameters
  
  • Aghanim N.
  • Akrami Yashar
  • Ashdown M.
  • Aumont J.
  • Ballardini M.
  • Banday A.J.
  • Barreiro R.B.
  • Bartolo N.
  • Basak S.
  • Benabed K.
  • Bersanelli M.
  • Bielewicz P.
  • Bonaldi A.
  • Bonavera L.
  • Bond J.R.
  • Borrill J.
  • Bouchet F.R.
  • Burigana C.
  • Calabrese E.
  • Cardoso J.F.
  • Challinor A.
  • Chiang H.C.
  • Colombo L.P.L.
  • Combet C.
  • Crill B.P.
  • Curto A.
  • Cuttaia F.
  • de Bernardis P.
  • de Rosa A.
  • de Zotti G.
  • Delabrouille J.
  • Di Valentino E.
  • Dickinson C.
  • Diego J.M.
  • Dore O.
  • Ducout A.
  • Dupac X.
  • Dusini S.
  • Efstathiou G.
  • Elsner F.
  • Ensslin T.A.
  • Eriksen H.K.
  • Fantaye Y.
  • Finelli F.
  • Forastieri F.
  • Frailis M.
  • Franceschi E.
  • Frolov A.
  • Galeotta S.
  • Galli S.
  • Ganga K.
  • Genova-Santos R.T.
  • Gerbino M.
  • Gonzalez-Nuevo J.
  • Gorski K.M.
  • Gruppuso A.
  • Gudmundsson J.E.
  • Herranz D.
  • Hivon E.
  • Huang Z.
  • Jaffe A.H.
  • Jones W.C.
  • Keihanen E.
  • Keskitalo R.
  • Kiiveri K.
  • Kim J.
  • Kisner T.S.
  • Knox L.
  • Krachmalnicoff N.
  • Kunz M.
  • Kurki-Suonio H.
  • Lagache G.
  • Lamarre J.M.
  • Lasenby A.
  • Lattanzi M.
  • Lawrence C.R.
  • Le Jeune M.
  • Levrier F.
  • Lewis A.
  • Lilje P.B.
  • Lilley M.
  • Lindholm V.
  • Lopez-Caniego M.
  • Lubin P.M.
  • Ma Y.Z.
  • Macias-Perez J.F.
  • Maggio G.
  • Maino D.
  • Mandolesi N.
  • Mangilli A.
  • Maris M.
  • Martin P.G.
  • Martinez-Gonzalez E.
  • Matarrese S.
  • Mauri N.
  • Mcewen J.D.
  • Meinhold P.R.
  • Mennella A.
  • Migliaccio M.
  • Millea M.
  • Miville-Deschenes M.A.
  • Molinari D.
  • Moneti A.
  • Montier L.
  • Morgante G.
  • Moss A.
  • Narimani A.
  • Natoli P.
  • Oxborrow C.A.
  • Pagano L.
  • Paoletti D.
  • Patanchon G.
  • Patrizii L.
  • Pettorino V.
  • Piacentini F.
  • Polastri L.
  • Polenta G.
  • Puget J.L.
  • Rachen J.P.
  • Racine B.
  • Reinecke M.
  • Remazeilles M.
  • Renzi A.
  • Rossetti M.
  • Roudier G.
  • Rubino-Martin J.A.
  • Ruiz-Granados B.
  • Salvati L.
  • Sandri M.
  • Savelainen M.
  • Scott D.
  • Sirignano C.
  • Sirri G.
  • Stanco L.
  • Suur-Uski A.S.
  • Tauber J.A.
  • Tavagnacco D.
  • Tenti M.
  • Toffolatti L.
  • Tomasi M.
  • Tristram M.
  • Trombetti T.
  • Valiviita J.
  • van Tent F.
  • Vielva P.
  • Villa Francesca
  • Vittorio N.
  • Wandelt B.D.
  • Wehus I.K.
  • White M.
  • Zacchei A.
  • Zonca A.
  Astronomy & Astrophysics - A&A, EDP Sciences, 2017, 607, pp.A95. The six parameters of the standard ΛCDM model have best-fit values derived from the Planck temperature power spectrum that are shifted somewhat from the best-fit values derived from WMAP data. These shifts are driven by features in the Planck temperature power spectrum at angular scales that had never before been measured to cosmic-variance level precision. We have investigated these shifts to determine whether they are within the range of expectation and to understand their origin in the data. Taking our parameter set to be the optical depth of the reionized intergalactic medium τ, the baryon density ωb, the matter density ωm, the angular size of the sound horizon θ∗, the spectral index of the primordial power spectrum, ns, and Ase− 2τ (where As is the amplitude of the primordial power spectrum), we have examined the change in best-fit values between a WMAP-like large angular-scale data set (with multipole moment ℓ < 800 in the Planck temperature power spectrum) and an all angular-scale data set (ℓ < 2500Planck temperature power spectrum), each with a prior on τ of 0.07 ± 0.02. We find that the shifts, in units of the 1σ expected dispersion for each parameter, are { Δτ,ΔAse− 2τ,Δns,Δωm,Δωb,Δθ∗ } = { −1.7,−2.2,1.2,−2.0,1.1,0.9 }, with a χ2 value of 8.0. We find that this χ2 value is exceeded in 15% of our simulated data sets, and that a parameter deviates by more than 2.2σ in 9% of simulated data sets, meaning that the shifts are not unusually large. Comparing ℓ < 800 instead to ℓ> 800, or splitting at a different multipole, yields similar results. We examined the ℓ < 800 model residuals in the ℓ> 800 power spectrum data and find that the features there that drive these shifts are a set of oscillations across a broad range of angular scales. Although they partly appear similar to the effects of enhanced gravitational lensing, the shifts in ΛCDM parameters that arise in response to these features correspond to model spectrum changes that are predominantly due to non-lensing effects; the only exception is τ, which, at fixed Ase− 2τ, affects the ℓ> 800 temperature power spectrum solely through the associated change in As and the impact of that on the lensing potential power spectrum. We also ask, “what is it about the power spectrum at ℓ < 800 that leads to somewhat different best-fit parameters than come from the full ℓ range?” We find that if we discard the data at ℓ < 30, where there is a roughly 2σ downward fluctuation in power relative to the model that best fits the full ℓ range, the ℓ < 800 best-fit parameters shift significantly towards the ℓ < 2500 best-fit parameters. In contrast, including ℓ < 30, this previously noted “low-ℓ deficit” drives ns up and impacts parameters correlated with ns, such as ωm and H0. As expected, the ℓ < 30 data have a much greater impact on the ℓ < 800 best fit than on the ℓ < 2500 best fit. So although the shifts are not very significant, we find that they can be understood through the combined effects of an oscillatory-like set of high-ℓ residuals and the deficit in low-ℓ power, excursions consistent with sample variance that happen to map onto changes in cosmological parameters. Finally, we examine agreement between PlanckTT data and two other CMB data sets, namely the Planck lensing reconstruction and the TT power spectrum measured by the South Pole Telescope, again finding a lack of convincing evidence of any significant deviations in parameters, suggesting that current CMB data sets give an internally consistent picture of the ΛCDM model.Key words: cosmology: observations / cosmic background radiation / cosmological parameters / cosmology: theory (10.1051/0004-6361/201629504)
  DOI : 10.1051/0004-6361/201629504
• Décomposition de séries temporelles d'images SAR pour la détection de changements
  
  • Lobry Sylvain
  • Denis L.
  • Zhao Weiying
  • Tupin Florence
  Traitement du Signal, Lavoisier, 2017.
• Demystifying the asymptotic behavior of global denoising
  
  • Houdard Antoine
  • Almansa Andrès
  • Delon Julie
  Journal of Mathematical Imaging and Vision, Springer Verlag, 2017. In this work, we revisit the global denoising framework recently introduced by Talebi and Milanfar. We analyze the asymptotic behavior of its mean-squared error restoration performance in the oracle case when the image size tends to infinity. We introduce precise conditions on both the image and the global filter to ensure and quantify this convergence. We also make a clear distinction between two different levels of oracle that are used in that framework. By reformulating global denoising with the classical formalism of diagonal estimation, we conclude that the second-level oracle can be avoided by using Donoho and Johnstone’s theorem, whereas the first-level oracle is mostly required in the sequel. We also discuss open issues concerning the most challenging aspect, namely the extension of these results to the case where neither oracle is required. (10.1007/s10851-017-0716-6)
  DOI : 10.1007/s10851-017-0716-6
• Quantitative analysis of normal and pathologic adrenal glands with 18F-FDOPA PET/CT
  
  • Moreau Aurélie
  • Giraudet Anne
  • Kryza David
  • Borson-Chazot Françoise
  • Bournaud Claire
  • Mognetti Thomas
  • Lifante Jean-Christophe
  • Combemale Patrick
  • Giammarile Francesco
  • Houzard Claire
  Nuclear Medicine Communications, Lippincott, Williams & Wilkins, 2017, 38 (9), pp.771-779. (10.1097/MNM.0000000000000708)
  DOI : 10.1097/MNM.0000000000000708