Search Results for author: Yves Wiaux

Found 18 papers, 4 papers with code

R2D2 image reconstruction with model uncertainty quantification in radio astronomy

no code implementations26 Mar 2024 Amir Aghabiglou, Chung San Chu, Arwa Dabbech, Yves Wiaux

The ``Residual-to-Residual DNN series for high-Dynamic range imaging'' (R2D2) approach was recently introduced for Radio-Interferometric (RI) imaging in astronomy.

Astronomy Image Reconstruction +1

The R2D2 deep neural network series paradigm for fast precision imaging in radio astronomy

no code implementations8 Mar 2024 Amir Aghabiglou, Chung San Chu, Arwa Dabbech, Yves Wiaux

Recent image reconstruction techniques grounded in optimization theory have demonstrated remarkable capability for imaging precision, well beyond CLEAN's capability.

Astronomy Image Reconstruction

Plug-and-play imaging with model uncertainty quantification in radio astronomy

no code implementations12 Dec 2023 Matthieu Terris, Chao Tang, Adrian Jackson, Yves Wiaux

In a previous work, we introduced a class of convergent PnP algorithms, dubbed AIRI, relying on a forward-backward algorithm, with a differentiable data-fidelity term and dynamic range-specific denoisers trained on highly pre-processed unrelated optical astronomy images.

Astronomy Uncertainty Quantification

CLEANing Cygnus A deep and fast with R2D2

no code implementations6 Sep 2023 Arwa Dabbech, Amir Aghabiglou, Chung San Chu, Yves Wiaux

A novel deep learning paradigm for synthesis imaging by radio interferometry in astronomy was recently proposed, dubbed "Residual-to-Residual DNN series for high-Dynamic range imaging" (R2D2).

Astronomy Computational Efficiency +1

Deep network series for large-scale high-dynamic range imaging

no code implementations28 Oct 2022 Amir Aghabiglou, Matthieu Terris, Adrian Jackson, Yves Wiaux

We propose a residual DNN series approach, also interpretable as a learned version of matching pursuit, where the reconstructed image is a sum of residual images progressively increasing the dynamic range, and estimated iteratively by DNNs taking the back-projected data residual of the previous iteration as input.

Denoising Vocal Bursts Intensity Prediction

Image reconstruction algorithms in radio interferometry: from handcrafted to learned regularization denoisers

no code implementations25 Feb 2022 Matthieu Terris, Arwa Dabbech, Chao Tang, Yves Wiaux

The approach consists in learning a prior image model by training a deep neural network (DNN) as a denoiser, and substituting it for the handcrafted proximal regularization operator of an optimization algorithm.

Denoising Image Reconstruction +1

Learning Maximally Monotone Operators for Image Recovery

2 code implementations24 Dec 2020 Jean-Christophe Pesquet, Audrey Repetti, Matthieu Terris, Yves Wiaux

Recently, several works have proposed to replace the operator related to the regularization by a more sophisticated denoiser.

Automated Theorem Proving Image Restoration Optimization and Control Image and Video Processing 47H05, 90C25, 90C59, 65K10, 49M27, 68T07, 68U10, 94A08

CoverBLIP: accelerated and scalable iterative matched-filtering for Magnetic Resonance Fingerprint reconstruction

1 code implementation3 Oct 2018 Mohammad Golbabaee, Zhouye Chen, Yves Wiaux, Mike Davies

Current popular methods for Magnetic Resonance Fingerprint (MRF) recovery are bottlenecked by the heavy computations of a matched-filtering step due to the growing size and complexity of the fingerprint dictionaries in multi-parametric quantitative MRI applications.

Dimensionality Reduction

CoverBLIP: scalable iterative matched filtering for MR Fingerprint recovery

no code implementations6 Sep 2018 Mohammad Golbabaee, Zhouye Chen, Yves Wiaux, Mike E. Davies

Current proposed solutions for the high dimensionality of the MRF reconstruction problem rely on a linear compression step to reduce the matching computations and boost the efficiency of fast but non-scalable searching schemes such as the KD-trees.

Wideband Super-resolution Imaging in Radio Interferometry via Low Rankness and Joint Average Sparsity Models (HyperSARA)

no code implementations12 Jun 2018 Abdullah Abdulaziz, Arwa Dabbech, Yves Wiaux

We propose a new approach within the versatile framework of convex optimization to solve the radio-interferometric wideband imaging problem.

Image and Video Processing Instrumentation and Methods for Astrophysics Signal Processing

Fast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical Priors

no code implementations8 Feb 2018 Marica Pesce, Audrey Repetti, Anna Auría, Alessandro Daducci, Jean-Philippe Thiran, Yves Wiaux

High spatio-angular resolution diffusion MRI (dMRI) has been shown to provide accurate identification of complex neuronal fiber configurations, albeit, at the cost of long acquisition times.

Cover Tree Compressed Sensing for Fast MR Fingerprint Recovery

no code implementations23 Jun 2017 Mohammad Golbabaee, Zhouye Chen, Yves Wiaux, Mike E. Davies

We adopt data structure in the form of cover trees and iteratively apply approximate nearest neighbour (ANN) searches for fast compressed sensing reconstruction of signals living on discrete smooth manifolds.

Magnetic Resonance Fingerprinting

Robust sparse image reconstruction of radio interferometric observations with purify

1 code implementation7 Oct 2016 Luke Pratley, Jason D. McEwen, Mayeul d'Avezac, Rafael E. Carrillo, Alexandru Onose, Yves Wiaux

However, they produce reconstructed inter\-ferometric images that are limited in quality and scalability for big data.

Instrumentation and Methods for Astrophysics

Directional spin wavelets on the sphere

no code implementations22 Sep 2015 Jason D. McEwen, Boris Leistedt, Martin Büttner, Hiranya V. Peiris, Yves Wiaux

We construct a directional spin wavelet framework on the sphere by generalising the scalar scale-discretised wavelet transform to signals of arbitrary spin.

Information Theory Instrumentation and Methods for Astrophysics Information Theory

Sparsity averaging for radio-interferometric imaging

no code implementations11 Feb 2014 Rafael E. Carrillo, Jason D. McEwen, Yves Wiaux

We propose a novel regularization method for compressive imaging in the context of the compressed sensing (CS) theory with coherent and redundant dictionaries.

A Compressed Sensing Framework for Magnetic Resonance Fingerprinting

no code implementations9 Dec 2013 Mike Davies, Gilles Puy, Pierre Vandergheynst, Yves Wiaux

Inspired by the recently proposed Magnetic Resonance Fingerprinting (MRF) technique, we develop a principled compressed sensing framework for quantitative MRI.

Information Theory Information Theory

PURIFY: a new approach to radio-interferometric imaging

2 code implementations16 Jul 2013 Rafael E. Carrillo, Jason D. McEwen, Yves Wiaux

This approach was shown, in theory and through simulations in a simple discrete visibility setting, to have the potential to outperform significantly CLEAN and its evolutions.

Instrumentation and Methods for Astrophysics

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