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Exact Sampling Results for Some Classes of Parametric Non-Bandlimited 2-D Signals

Publications associées (37)

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On the Bandwidth of the Plenoptic Function

Martin Vetterli, Minh Do, Davy Marchand-Maillet

The plenoptic function (POF) provides a powerful conceptual tool for describing a number of problems in image/video processing, vision, and graphics. For example, image based-rendering can be seen as sampling and interpolation of the POF. In such applicati ...

Institute of Electrical and Electronics Engineers2012

On Sampling and Coding for Distributed Acoustic Sensing

Martin Vetterli, Emre Telatar, Robert Konsbruck

The issue of how to efficiently represent the data collected by a network of microphones recording spatio-temporal acoustic wave fields is addressed. Each sensor node in the network samples the sound field, quantizes the samples and transmits the encoded s ...

2012

Sampling Trajectories for Mobile Sensing

Martin Vetterli, Jayakrishnan Unnikrishnan

Classical sampling theory for sampling and reconstructing bandlimited fields in

\Re^d

addresses the problem of sampling on lattice points. We consider a generalization of this problem, in which one samples the field along

1

-dimensional spatial trajecto ...

2011

A novel sampling theorem on the sphere

Yves Wiaux, Jason Douglas McEwen

We develop a novel sampling theorem on the sphere and corresponding fast algorithms by associating the sphere with the torus through a periodic extension. The fundamental property of any sampling theorem is the number of samples required to represent a ban ...

Institute of Electrical and Electronics Engineers2011

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

Martin Vetterli, Olivier Roy, Yue Lu, 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

Sensing and Recovery under Sparsity Constraints

Ali Hormati

Popular transforms, like the discrete cosine transform or the wavelet transform, owe their success to the fact that they promote sparsity. These transforms are capable of extracting the structure of a large class of signals and representing them by a few t ...

EPFL2010

Polar codes for channel and source coding

Satish Babu Korada

The two central topics of information theory are the compression and the transmission of data. Shannon, in his seminal work, formalized both these problems and determined their fundamental limits. Since then the main goal of coding theory has been to find ...

EPFL2009

Parallel architecture for high-speed analog-to-digital conversion

Guillaume Ding

Nowadays digital signal processing systems used for radar applications, communication systems or RF measurement equipments, require very high sample-rates. Sometimes these sample-rates are beyond the possibilities offered by conventional ADCs. To overcome ...

EPFL2009

Inverse problems in acoustic tomography

Ivana Jovanovic

Acoustic tomography aims at recovering the unknown parameters that describe a field of interest by studying the physical characteristics of sound propagating through the considered field. The tomographic approach is appealing in that it is non-invasive and ...

EPFL2008

Consistent Sampling and Signal Recovery

Michaël Unser

An attractive formulation of the sampling problem is based on the principle of a consistent signal reconstruction. The requirement is that the reconstructed signal is indistinguishable from the input in the sense that it yields the exact same measurements. ...

Institute of Electrical and Electronics Engineers2007