Publications related to Looking beyond Pixels

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Volkan Cevher, Mikhail Kapralov, Jonathan Mark Scarlett, Amir Zandieh

The problem of approximately computing the

k

dominant Fourier coefficients of a vector

X

quickly, and using few samples in time domain, is known as the Sparse Fourier Transform (sparse FFT) problem. A long line of work on the sparse FFT has resulted in ...

2017

A Fourier dimensionality reduction model for big data interferometric imaging

Jean-Philippe Thiran, Yves Wiaux, Rafael Eduardo Carrillo Rangel, Vijay Kartik

Data dimensionality reduction in radio interferometry can provide savings of computational resources for image reconstruction through reduced memory footprints and lighter computations per iteration, which is important for the scalability of imaging method ...

Oxford Univ Press2017

Sparse inverse problems for Fourier imaging

Anna Auria Rasclosa

Many natural images have low intrinsic dimension (a.k.a. sparse), meaning that they can be represented with very few coefficients when expressed in an adequate domain. The recent theory of Compressed Sensing exploits this property offering a powerful frame ...

EPFL2017

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

Kyong Hwan Jin

While the recent theory of compressed sensing provides an opportunity to overcome the Nyquist limit in recovering sparse signals, a solution approach usually takes the form of an inverse problem of an unknown signal, which is crucially dependent on specifi ...

IEEE2017

Dictionary Learning Based on Sparse Distribution Tomography

Michaël Unser, Pedram Pad

We propose a new statistical dictionary learning algorithm for sparse signals that is based on an α-stable innovation model. The parameters of the underlying model—that is, the atoms of the dictionary, the sparsity index α and the dispersion of the transfo ...

P. Pad2017

On Denoising Crosstalk in Radio Interferometry

Paul Hurley, Matthieu Martin Jean-André Simeoni, Nezihe Merve Gürel

Noise reduction in radio interferometers is a formidable task due to the relatively weak signals under observation. The usual strategy is to compensate with a large number of antennas and extend the observation time. We showed recently that one could denoi ...

2017

Ultrafast ultrasound imaging as an inverse problem: Matrix-free sparse image reconstruction

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

Conventional ultrasound (US) image reconstruction methods rely on delay-and-sum (DAS) beamforming, which is a relatively poor solution of the image reconstruction problem. An alternative to DAS consists in using iterative techniques which require both an a ...

2017

Denoising radio interferometric images by subspace clustering

Paul Hurley, Matthieu Martin Jean-André Simeoni, Nezihe Merve Gürel

Radio interferometry usually compensates for high levels of noise in sensor/antenna electronics by throwing data and energy at the problem: observe longer, then store and process it all. Furthermore, only the end image is cleaned, reducing flexibility subs ...

2017

Single Image Reflection Suppression

Sabine Süsstrunk, Radhakrishna Achanta, Nikolaos Arvanitopoulos Darginis

Reflections are a common artifact in images taken through glass windows. Automatically removing the reflection artifacts after the picture is taken is an ill-posed problem. Attempts to solve this problem using optimization schemes therefore rely on various ...

Ieee2017

A method for reducing noise in measurements taken by a distributed sensor

Marcelo Alfonso Soto Hernandez

According to the present invention there is provided a method of sensing comprising the steps of, (a) acquiring plurality of measurement values using a distributed optical fibre sensor; (b) arranging the plurality of measurement values in a matrix having a ...

2016

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An Adaptive Sublinear-Time Block Sparse Fourier Transform

A Fourier dimensionality reduction model for big data interferometric imaging

Sparse inverse problems for Fourier imaging

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

Dictionary Learning Based on Sparse Distribution Tomography

On Denoising Crosstalk in Radio Interferometry

Ultrafast ultrasound imaging as an inverse problem: Matrix-free sparse image reconstruction

Denoising radio interferometric images by subspace clustering

Single Image Reflection Suppression

A method for reducing noise in measurements taken by a distributed sensor

A Fourier dimensionality reduction model for big data interferometric imaging

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Sparse inverse problems for Fourier imaging

Denoising radio interferometric images by subspace clustering

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

A method for reducing noise in measurements taken by a distributed sensor

On Denoising Crosstalk in Radio Interferometry

Dictionary Learning Based on Sparse Distribution Tomography

Ultrafast ultrasound imaging as an inverse problem: Matrix-free sparse image reconstruction

Single Image Reflection Suppression