Publications associées à Sparse non-negative super-resolution - simplified and stabilised

An Efficient Sampling Algorithm for Non-smooth Composite Potentials

We consider the problem of sampling from a density of the form p(x) ? exp(-f (x) - g(x)), where f : Rd-+ R is a smooth function and g : R-d-+ R is a convex and Lipschitz function. We propose a new algorithm based on the Metropolis-Hastings framework. Under ...

Microtome Publishing2022

Coarse graining and large-N behavior of the d-dimensional N-clock model

Matthias Ruf, Matthias Benjamin Ruf

We study the asymptotic behavior of the N-clock model, a nearest neighbors ferromagnetic spin model on the d-dimensional cubic epsilon-lattice in which the spin field is constrained to take values in a discretization S-N of the unit circle S-1 consisting o ...

2021

Functional registration and local variations: Identifiability, rank, and tuning

Victor Panaretos, Anirvan Chakraborty

We develop theory and methodology for the problem of nonparametric registration of functional data that have been subjected to random deformation (warping) of their time scale. The separation of this phase variation ("horizontal" variation) from the amplit ...

2021

A reflected forward-backward splitting method for monotone inclusions involving Lipschitzian operators

Volkan Cevher, Cong Bang Vu

In this paper, we propose a novel splitting method for finding a zero point of the sum of two monotone operators where one of them is Lipschizian. The weak convergence the method is proved in real Hilbert spaces. Applying the proposed method to composite m ...

2021

Transient fission matrix approach for assessing complex kinetics behavior in the ZEPHYR ZPR coupled core configurations

Axel Guy Marie Laureau

CEA is currently working on a new ZPR called ZEPHYR (Zero power Experimental PHYsics Reactor), to be built on the Cadarache Center in the next decade. Its awaited experimental capacities should go well beyond traditional needs, and in particular extended p ...

PERGAMON-ELSEVIER SCIENCE LTD2019

Non-local Functionals Related to the Total Variation and Connections with Image Processing

Hoài-Minh Nguyên

We present new results concerning the approximation of the total variation,

\int_{\Omega} |\nabla u|

, of a function

u

by non-local, non-convex functionals of the form $$ \Lambda_\delta u = \int_{\Omega} \int_{\Omega} \frac{\delta \varphi \big( |u(x) - ...

2018

Performing mathematical operations using high-index acoustic metamaterials

Romain Christophe Rémy Fleury, Farzad Zangeneh Nejad

The recent breakthrough in metamaterial-based optical computing devices (2014 Science 343 160) has inspired a quest for similar systems in acoustics, performing mathematical operations on sound waves. So far, acoustic analog computing has been demonstrated ...

2018

Wavevector-Selective Nonlinear Plasmonic Metasurfaces

Olivier Martin, Chen Yan, Jérémy Butet, Kuang-Yu Yang

Electromagnetic metasurfaces with strong non- linear responses and angular selectivity could o ff er many new avenues for designing ultrathin optics components. We investigated the optical second harmonic generation from plasmonic metasurfaces composed of ...

American Chemical Society (ACS)2017

Splines Are Universal Solutions of Linear Inverse Problems with Generalized TV Regularization

Michaël Unser, John Paul Ward, Julien René Pierre Fageot

Splines come in a variety of flavors that can be characterized in terms of some differential operator L. The simplest piecewise-constant model corresponds to the derivative operator. Likewise, one can extend the traditional notion of total variation by con ...

2017

Non-convex, non-local functionals converging to the total variation

Hoài-Minh Nguyên

We present new results concerning the approximation of the total variation, integral(Omega)vertical bar del u vertical bar, of a function u by non-local, non-convex functionals of the form Lambda delta(u) = integral(Omega)integral(Omega)delta phi(vertical ...

Elsevier2017

Sparse Gradient Optimization and its Applications in Image Processing

Nikolaos Arvanitopoulos Darginis

Millions of digital images are captured by imaging devices on a daily basis. The way imaging devices operate follows an integral process from which the information of the original scene needs to be estimated. The estimation is done by inverting the integra ...

EPFL2017

Scampi: a robust approximate message-passing framework for compressive imaging

Jean François Emmanuel Barbier, Florent Gérard Krzakala

Reconstruction of images from noisy linear measurements is a core problem in image processing, for which convex optimization methods based on total variation (TV) minimization have been the long-standing state-of-the-art. We present an alternative probabil ...

Iop Publishing Ltd2016

Characterization of the Solution of Linear Inverse Problems with Generalized TV Regularization

Michaël Unser

Ill-posed inverse problems are often constrained by imposing a bound on the total variation of the solution. Here, we consider a generalized version of total-variation regularization that is tied to some differential operator L. We then show that the gener ...

OSA2016

Optical Tomographic Image Reconstruction Based on Beam Propagation and Sparse Regularization

Michaël Unser, Cédric René Jean Vonesch, Ulugbek Kamilov, Demetri Psaltis

Optical tomographic imaging requires an accurate forward model as well as regularization to mitigate missing-data artifacts and to suppress noise. Nonlinear forward models can provide more accurate interpretation of the measured data than their linear coun ...

2016

A Methodology for Global Sensitivity Analysis for Time-Dependent Code Output Applied to Reflood Simulation in TRACE

Damar Canggih Wicaksono, Andreas Pautz, Omar Zerkak

Understanding properly the impact of model parameters and their interactions on the predictions is required for an appropriate model assessment. For simulation of reflooding following a LOCA, this requirement is justified because the important parameters a ...

2015

Improved Variational Denoising of Flow Fields with Application to Phase-Contrast MRI Data

Nikolaos Stergiopoulos, Michaël Unser, Emrah Bostan, Orestis Vardoulis, Stamatios Lefkimmiatis

We propose a new variational framework for the problem of reconstructing flow fields from noisy measurements. The formalism is based on regularizers penalizing the singular values of the Jacobian of the field. Specifically, we rely on the nuclear norm. Our ...

IEEE Institute of Electrical and Electronics Engineers2015

Cloaking via anomalous localized resonance. A connection between the localized resonance and the blow up of the power for doubly complementary media

Hoài-Minh Nguyên

This paper is devoted to the study of cloaking via anomalous localized resonance (CALR) in two and three dimensions in the quasistatic regime. Two key figures of CALR are (i) the localized resonance and (ii) the connection between the localized resonance a ...

Elsevier2015

Reconstruction and stability in acousto-optic imaging for absorption maps with bounded variation

Quoc Hung Nguyen

The aim of this paper is to propose for the first time a reconstruction scheme and a stability result for recovering from acousto-optic data absorption distributions with bounded variation. The paper extends earlier results in [3] and [5] on smooth absorpt ...

Academic Press Inc Elsevier Science2014

Digital Phase Reconstruction via Iterative Solutions of Transport-of-Intensity Equation

Michaël Unser, Emrah Bostan, Stamatios Lefkimmiatis, Emmanuel Augustin Julien Froustey

We develop a variational algorithm for reconstructing phase objects from a series of bright field micrographs. Our mathematical model is based on the transport-of-intensity equation (TIE), which links the phase of a complex field to the axial derivative of ...

Ieee2014

Convex Generalizations of Total Variation Based on the Structure Tensor with Applications to Inverse Problems

Michaël Unser, Stamatios Lefkimmiatis

We introduce a generic convex energy functional that is suitable for both grayscale and vector-valued images. Our functional is based on the eigenvalues of the structure tensor, therefore it penalizes image variation at every point by taking into account t ...

Springer2013