Publications related to On Optimal Sampling Trajectories for Mobile Sensing

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

Compressed Optical Imaging

Aurélien Bourquard

We address the resolution of inverse problems where visual data must be recovered from incomplete information optically acquired in the spatial domain. The optical acquisition models that are involved share a common mathematical structure consisting of a l ...

EPFL2013

Super-resolution from unregistered aliased images with unknown scalings and shifts

Martin Vetterli, Feng Yang

We consider the problem of super-resolution from unregistered aliased images with unknown spatial scaling factors and shifts. Due to the limitation of pixel size in the image sensor, the sampling rate for each image is lower than the Nyquist rate of the sc ...

2012

Diffractionless Fourier Domain Microscopy

Theo Lasser, Rainer Leitgeb, Cédric Blatter, Tilman Schmoll

Several methods have been proposed and realized to increase the lateral resolution in microscopy and ultimately to beat the actual diffraction limit as stated by Abbe. Structured illumination for example enhances the lateral resolution by virtually extendi ...

2011

Multichannel Sampling with Unknown Gains and Offsets: A Fast Reconstruction Algorithm

Martin Vetterli, Yue Lu

We study a multichannel sampling scheme, where different channels observe scaled and shifted versions of a common bandlimited signal. The channel gains and offsets are unknown a priori, and each channel samples at sub-Nyquist rates. This setup appears in m ...

2010

Signal Processing in Space and Time

Francisco Pereira Correia Pinto

Sound waves propagate through space and time by transference of energy between the particles in the medium, which vibrate according to the oscillation patterns of the waves. These vibrations can be captured by a microphone and translated into a digital sig ...

EPFL2010

Registration for Super-Resolution: Theory, Algorithms, and Applications in Image and Mobile Video Enhancement

Martin Vetterli, Luciano Sbaiz, Patrick Vandewalle

The relation between sensor resolution and the optics of a digital camera is determined by the Nyquist sampling theorem: the sampling frequency should be larger than twice the maximum frequency of the image content coming out of the optical system. If a lo ...

Taylor& Francis / CRC Press2010

Compressive Sampling of Pulse Trains : Spread the Spectrum !

Pierre Vandergheynst, Rémi Gribonval, Laurent Jacques

In this paper we consider the problem of sampling far below the Nyquist rate signals that are sparse linear superpositions of shifts of a known, potentially wide-band, pulse. This signal model is key for applications such as Ultra Wide Band (UWB) communica ...

2009

Source coding in sensor networks

Robert Konsbruck

Wireless sensor networks have emerged as versatile tools to monitor the evolution of physical fields over large areas by means of self-powered and low-cost sensing devices. Although their development was originally motivated by military applications, they ...

EPFL2009

Super-Resolution from Unregistered and Totally Aliased Signals Using Subspace Methods

Martin Vetterli, Luciano Sbaiz, Patrick Vandewalle

In many applications, the sampling frequency is limited by the physical characteristics of the components: the pixel pitch, the rate of the A/D converter, etc. A low-pass filter is then often applied before the sampling operation to avoid aliasing. However ...

Institute of Electrical and Electronics Engineers2007

On Optimal Sampling Trajectories for Mobile Sensing

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Sampling High-Dimensional Bandlimited Fields on Low-Dimensional Manifolds

Compressed Optical Imaging

Super-resolution from unregistered aliased images with unknown scalings and shifts

Diffractionless Fourier Domain Microscopy

Multichannel Sampling with Unknown Gains and Offsets: A Fast Reconstruction Algorithm

Signal Processing in Space and Time

Registration for Super-Resolution: Theory, Algorithms, and Applications in Image and Mobile Video Enhancement

Compressive Sampling of Pulse Trains : Spread the Spectrum !

Source coding in sensor networks

Super-Resolution from Unregistered and Totally Aliased Signals Using Subspace Methods

Sampling High-Dimensional Bandlimited Fields on Low-Dimensional Manifolds

Compressed Optical Imaging

Multichannel Sampling with Unknown Gains and Offsets: A Fast Reconstruction Algorithm

Source coding in sensor networks

Super-resolution from unregistered aliased images with unknown scalings and shifts

Signal Processing in Space and Time

Registration for Super-Resolution: Theory, Algorithms, and Applications in Image and Mobile Video Enhancement

Compressive Sampling of Pulse Trains : Spread the Spectrum !

Super-Resolution from Unregistered and Totally Aliased Signals Using Subspace Methods

Diffractionless Fourier Domain Microscopy