Publications related to Sensing and Recovery under Sparsity Constraints

Sampling Continuous-time Sparse Signals: A Frequency-domain Perspective

We address the problem of sampling and reconstruction of sparse signals with finite rate of innovation. We derive general conditions under which perfect reconstruction is possible for sampling kernels satisfying Strang-Fix conditions. Previous results on t ...

2018

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Jean-Philippe Thiran, Martin Vetterli, Dimitris Perdios, Eric Bezzam, Adrien Georges Jean Besson, Hanjie Pan

In this paper we show that it is sufficient to recover the locations of K strong reflectors within an insonified medium from three receive elements and 2K+1 samples per element. The proposed approach leverages advances in sampling signals with a finite rat ...

IEEE2018

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Jean-Philippe Thiran, Martin Vetterli, Dimitris Perdios, Eric Bezzam, Adrien Besson, Hanjie Pan

In this paper we show that it is sufficient to recover the locations of K strong reflectors within an insonified medium from three receive elements and 2K+1 samples per element. The proposed approach leverages advances in sampling signals with a finite rat ...

IEEE2018

Phaseless Diffraction Tomography With Regularized Beam Propagation

Michaël Unser, Demetri Psaltis, Thanh-An Michel Pham, Emmanuel Emilien Louis Soubies, Ferréol Arnaud Marie Soulez, Alexandre Goy, Joowon Lim

In recent years, researchers have obtained impressive reconstructions of the refractive index (RI) of biological objects through the combined use of advanced physics (nonlinear forward model) and regularization. Here, we propose an adaptation of these tech ...

IEEE2018

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

Towards Generalized FRI Sampling with an Application to Source Resolution in Radioastronomy

Martin Vetterli, Thierry Blu, Hanjie Pan

It is a classic problem to estimate continuous-time sparse signals, like point sources in a direction-of-arrival problem, or pulses in a time-of-flight measurement. The earliest occurrence is the estimation of sinusoids in time series using Prony's method. ...

Institute of Electrical and Electronics Engineers2017

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

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

Media item relighting technique

Martin Vetterli, Loïc Arnaud Baboulaz, Damien Firmenich, Niranjan Thanikachalam

The present invention concerns a method of method of relighting a media item comprising media elements. The method comprises, for at least some of the media elements: determining, in a first signal domain, a light transport function describing the appearan ...

2017

Signal Analysis Based on Complex Wavelet Signs

Martin Kurt Storath

We propose a signal analysis tool based on the sign (or the phase) of complex wavelet coefficients, which we call a signature. The signature is defined as the fine-scale limit of the signs of a signal's complex wavelet coefficients. We show that the signat ...

Elsevier2017

Sensing and Recovery under Sparsity Constraints

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Sampling Continuous-time Sparse Signals: A Frequency-domain Perspective

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Phaseless Diffraction Tomography With Regularized Beam Propagation

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Towards Generalized FRI Sampling with an Application to Source Resolution in Radioastronomy

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

Sparse inverse problems for Fourier imaging

Media item relighting technique

Signal Analysis Based on Complex Wavelet Signs

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Phaseless Diffraction Tomography With Regularized Beam Propagation

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

Sparse inverse problems for Fourier imaging

Media item relighting technique

Signal Analysis Based on Complex Wavelet Signs

Sampling Continuous-time Sparse Signals: A Frequency-domain Perspective

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Towards Generalized FRI Sampling with an Application to Source Resolution in Radioastronomy