Publications related to A Fourier dimensionality reduction model for big data interferometric imaging

Fast Robust PCA on Graphs

Pierre Vandergheynst, Gilles Puy, Nathanaël Perraudin, Nauman Shahid, Vasilis Kalofolias

Mining useful clusters from high dimensional data has received significant attention of the computer vision and pattern recognition community in the recent years. Linear and non-linear dimensionality reduction has played an important role to overcome the c ...

Ieee-Inst Electrical Electronics Engineers Inc2016

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Michaël Unser, Martin Kurt Storath

We consider

L ^{ 1 }

-TV regularization of univariate signals with values on the real line or on the unit circle. While the real data space leads to a convex optimization problem, the problem is nonconvex for circle-valued data. In this paper, we deriv ...

SIAM2016

Global Optimization for Image Restoration in Optical/IR Interferometry

Ferréol Arnaud Marie Soulez

Many image reconstruction algorithms have been proposed to cope with optical/IR interferometric data. A first difficulty is to deal with the sparsity of the data and the uneven u-v coverage. This is usually overcome by imposing a priori constraints to the ...

SPIE2016

Robust sparse image reconstruction of radio interferometric observations with PURIFY

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

Next-generation radio interferometers, such as the Square Kilometre Array (SKA), will revolutionise our understanding of the universe through their unprecedented sensitivity and resolution. However, to realise these goals significant challenges in image an ...

Wiley-Blackwell2016

A compressed beamforming framework for ultrafast ultrasound imaging

Jean-Philippe Thiran, Yves Wiaux, Dimitris Perdios, Rafael Eduardo Carrillo Rangel, Marcel Arditi, Adrien Georges Jean Besson, Olivier Bernard

Classical beamforming methods, based on Delay- And-Sum (DAS) require an extensive number of samples and delay calculations to obtain high-quality images. Compressed Beamforming (CB) proposes an alternative to DAS, based on compressed sensing, which aims at ...

Ieee2016

Imaging in radio interferometry by iterative subset scanning using a modified amp algorithm

Paul Hurley, Matthieu Martin Jean-André Simeoni, Giovanni Cherubini, Sanaz Kazemi

Imaging techniques in radio interferometry often face a significant challenge posed by the large number of antenna signals received, from which the image information needs to be extracted. Beam- forming is envisaged to reduce the rate required for transpor ...

2016

A randomised primal-dual algorithm for distributed radio-interferometric imaging

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

Next generation radio telescopes, like the Square Kilometre Array, will acquire an unprecedented amount of data for radio astronomy. The development of fast, parallelisable or distributed algorithms for handling such large-scale data sets is of prime impor ...

Ieee2016

Spectral based Discontinuous Galerkin Reduced Basis Element method for parametrized Stokes problems

Alfio Quarteroni, Paolo Pacciarini

In this work we extend to the Stokes problem the Discontinuous Galerkin Reduced Basis Element (DGRBE) method introduced in Antonietti et al. (2015). By this method we aim at reducing the computational cost for the approximation of a parametrized Stokes pro ...

Pergamon-Elsevier Science Ltd2016

MATHICSE Technical Report : Spectral based discontinuous Galerkin reduced basis element method for parametrized Stokes problems

Alfio Quarteroni, Paolo Pacciarini

In this work we extend to the Stokes problem the Discontinuous Galerkin Reduced Basis Element (DGRBE) method introduced in [1]. By this method we aim at reducing the computational cost for the approximation of a parametrized Stokes problem on a domain part ...

MATHICSE2016

Dimension embedding for big data in radio interferometry

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Vijay Kartik

As radio telescope data is now increasingly high-dimensional, data reduction has become essential to reduce computational load while preserving accurate signal reconstruction. Gridding the continuous Fourier visibilities represents the standard approach to ...

2015

A Fourier dimensionality reduction model for big data interferometric imaging

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Fast Robust PCA on Graphs

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Global Optimization for Image Restoration in Optical/IR Interferometry

Robust sparse image reconstruction of radio interferometric observations with PURIFY

A compressed beamforming framework for ultrafast ultrasound imaging

Imaging in radio interferometry by iterative subset scanning using a modified amp algorithm

A randomised primal-dual algorithm for distributed radio-interferometric imaging

Spectral based Discontinuous Galerkin Reduced Basis Element method for parametrized Stokes problems

MATHICSE Technical Report : Spectral based discontinuous Galerkin reduced basis element method for parametrized Stokes problems

Dimension embedding for big data in radio interferometry

Imaging in radio interferometry by iterative subset scanning using a modified amp algorithm

A compressed beamforming framework for ultrafast ultrasound imaging

Global Optimization for Image Restoration in Optical/IR Interferometry

MATHICSE Technical Report : Spectral based discontinuous Galerkin reduced basis element method for parametrized Stokes problems

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

A randomised primal-dual algorithm for distributed radio-interferometric imaging

Fast Robust PCA on Graphs

Robust sparse image reconstruction of radio interferometric observations with PURIFY

Spectral based Discontinuous Galerkin Reduced Basis Element method for parametrized Stokes problems

Dimension embedding for big data in radio interferometry