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Martin Vetterli

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Related publications (262)

Page 3 of 14

Distributed Sampling of Signals Linked by Sparse Filtering: Theory and Applications

Martin Vetterli, Yue Lu, Olivier Roy, Ali Hormati

We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin to a Slepian-Wolf setup, but in the sampling rather than the lossless compres ...

2010

CPGD: Cadzow Plug-and-Play Gradient Descent for Generalised FRI

Martin Vetterli, Paul Hurley, Matthieu Martin Jean-André Simeoni, Adrien Georges Jean Besson

Finite rate of innovation (FRI) is a powerful reconstruction framework enabling the recovery of sparse Dirac streams from uniform low-pass filtered samples. An extension of this framework, called generalised FRI (genFRI), has been recently proposed for han ...

2020

Sequences with Minimal Time-Frequency Spreads

Martin Vetterli, Yann Barbotin, Reza Parhizkar

For a given time or frequency spread, one can always find continuous- time signals, which achieve the Heisenberg uncertainty principle bound. This is known, however, not to be the case for discrete-time sequences; only widely spread sequences asymptoticall ...

Ieee2013

Computationally efficient background subtraction in the light field domain

Martin Vetterli, Mahdad Hosseini Kamal, Alireza Ghasemi

Since the invention of first camera, people have always thought of new ways to capture moments. With the advent of digital photography, not only imaging systems have progressed, but also technology provides new user experience. The recently introduced ligh ...

International Society for Optics and Photonics2014

Euclidean Distance Matrices: Essential Theory, Algorithms and Applications

Martin Vetterli, Ivan Dokmanic, Juri Ranieri, Reza Parhizkar

Euclidean distance matrices (EDMs) are matrices of the squared distances between points. The definition is deceivingly simple; thanks to their many useful properties, they have found applications in psychometrics, crystallography, machine learning, wireles ...

2015

VITRAIL : Acquisition, Modelling and Rendering of Stained Glass

Martin Vetterli, Paolo Prandoni, Loïc Arnaud Baboulaz, Niranjan Thanikachalam

Stained glass windows are designed to reveal their powerful artistry under diverse and time-varying lighting conditions; virtual relighting of stained glass, therefore represents an exceptional tool for the appreciation of this age old art form. However, a ...

Institute of Electrical and Electronics Engineers2016

How Asynchronous Events Encode Video

Martin Vetterli, Adam James Scholefield, Karen Adam

As event-based sensing gains in popularity, theoretical understanding is needed to harness this technology’s potential. Instead of recording video by capturing frames, event-based cameras have sensors that emit events when their inputs change, thus encodin ...

IEEE2021

Topology Optimization For Energy-Efficient Communications In Consensus Wireless Networks

Martin Vetterli, Benjamin Bejar Haro

Over the past years there has been an increasing interest in developing distributed computation methods over wireless networks. A new communication paradigm has emerged where distributed algorithms such as consensus have played a key role in the developmen ...

IEEE2014

Reproducing Sound Fields Using MIMO Acoustic Channel Inversion

Martin Vetterli, Christof Faller, Mihailo Kolundzija

Sound fields are essentially band-limited phenomena, both temporally and spatially. This implies that a spatially sampled sound field respecting the Nyquist criterion is effectively equivalent to its continuous original. We describe Sound Field Reconstruct ...

2011

On The Move: Localization With Kinetic Euclidean Distance Matrices

Martin Vetterli, Ivan Dokmanic

In this paper, we propose kinetic Euclidean distance matrices (KEDMs) a new algebraic tool for localization of moving points from spatio temporal distance measurements. KEDMs are inspired by the well-known Euclidean distance matrices (EDM) which model stat ...

IEEE2019

Power, Spatio-Temporal Bandwidth, and Distortion in Large Sensor Networks

Martin Vetterli, Michael Christoph Gastpar

For a class of sensor networks, the task is to monitor an underlying physical phenomenon over space and time through an imperfect observation process. The sensors can communicate back to a central data collector over a noisy channel. The key pa- rameters i ...

Institute of Electrical and Electronics Engineers2005

Low-Rate Reduced Complexity Image Compression using Directionlets

Martin Vetterli, Pier Luigi Dragotti, Vladan Velisavljevic

The standard separable two-dimensional (2-D) wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth images. However, it fails to capture efficiently one-dimensional (1-D) disco ...

2006

Sampling and Reconstruction of Shapes with Algebraic Boundaries

Martin Vetterli, Arash Amini, Mitra Fatemi

We present a sampling theory for a class of binary images with finite rate of innovation (FRI). Every image in our model is the restriction of

\mathds{1}_{\{p\leq0\}}

to the image plane, where

\mathds{1}

denotes the indicator function and

p

is some r ...

2016

Signal Reconstruction from Multiple Unregistered Sets of Samples using Groebner Bases

Martin Vetterli, Luciano Sbaiz, Patrick Vandewalle

We present a new method for signal reconstruction from multiple sets of samples with unknown offsets. We rewrite the reconstruction problem as a set of polynomial equations in the unknown signal parameters and the offsets between the sets of samples. Then, ...

2006

Unlabeled Sensing: Reconstruction Algorithm and Theoretical Guarantees

Martin Vetterli, Adam James Scholefield, Benjamin Bejar Haro, Golnooshsadat Elhami

It often happens that we are interested in reconstructing an unknown signal from partial measurements. Also, it is typically assumed that the location (temporal or spatial) of the samples is known and that the only distortion present in the observations is ...

Ieee2017

Sampling High-Dimensional Bandlimited Fields on Low-Dimensional Manifolds

Martin Vetterli, Jayakrishnan Unnikrishnan

Consider the task of sampling and reconstructing a bandlimited spatial field in

\Re^2

using moving sensors that take measurements along their path. It is inexpensive to increase the sampling rate along the paths of the sensors but more expensive to incre ...

Institute of Electrical and Electronics Engineers2013

Rate-Constrained Collaborative Noise Reduction for Wireless Hearing Aids

Martin Vetterli, Olivier Roy

Hearing aids are electronic, battery-operated sensing devices which aim at compensating various kinds of hearing impairments. Recent advances in low-power electronics coupled with progresses made in digital signal processing offer the potential for substan ...

2009

Blind as a Bat: Audible Echolocation on Small Robots

Martin Vetterli, Adam James Scholefield, Mihailo Kolundzija, Frederike Dümbgen, Adrien Guillaume Olivier Hoffet

For safe and efficient operation, mobile robots need to perceive their environment, and in particular, perform tasks such as obstacle detection, localization, and mapping. Although robots are often equipped with microphones and speakers, the audio modality ...

2022

Scale-invariant representation of light field images for object recognition and tracking

Martin Vetterli, Alireza Ghasemi

Achieving perfect scale-invariance is usually not possible using classical color image features. This is mostly because of the fact that a traditional image is a two-dimensional projection of the real world. In contrast, light field imaging makes available ...

International Society for Optics and Photonics2014

Sampling and Reconstruction of Time-Varying Atmospheric Emissions

Martin Vetterli, Ivan Dokmanic, Juri Ranieri

We study the spatio-temporal sampling of physical fields representing the dispersion of a substance in the atmosphere. We consider the following setup: N sensors are deployed at ground level and measure the concentration of a particular substance, while M ...

Ieee2012