Publications by Martin Vetterli

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Multiple description (MD) coding is a source coding technique for information transmission over unreliable networks. In MD coding, the coder generates several different descriptions of the same signal and the decoder can produce a useful reconstruction of the source with any received subset of these descriptions. In this paper, we study the problem of MD coding of stationary Gaussian sources with memory. First, we compute an approximate MD rate distortion region for these sources, which we prove to be asymp

Recently, we have proposed a new image device called gigavision camera whose most important characteristic is that pixels have binary response. The response function of a gigavision sensor is non-linear and similar to a logarithmic function, which makes the camera suitable for high dynamic range imaging. One important parameter in the gigavision camera is the threshold for generating binary pixels. Threshold T relates to the number of photo-electrons necessary for the pixel output to switch from "0" to "1".

This paper presents novel coding algorithms based on tree-structured segmentation, which achieve the correct asymp- totic rate-distortion (R-D) behavior for a simple class of signals, known as piecewise polynomials, by using an R-D based prune and join sch ...

Les capteurs sans fil s’organisent automatiquement en réseaux pour enregistrer les données de notre environnement physique et transmettre les informations. C’est la théorie, mais la réalité pratique n’est pas si simple. L’article décrit un réseau de capteurs sans fil installé à l’EPFL.

Solving a linear inverse problem may include difficulties such as the presence of outliers and a mixing matrix with a large condition number. In such cases a regularized robust estimator is needed. We propose a new tau-type regularized robust estimator that is simultaneously highly robust against outliers, highly efficient in the presence of purely Gaussian noise, and also stable when the mixing matrix has a large condition number. We also propose an algorithm to compute the estimates, based on a regularize

We consider the task of recovering correlated vectors at a central decoder based on fixed linear measurements obtained by distributed sensors. Two different scenarios are considered: In the case of universal reconstruction, we look for a sensing and recove ...

We study the spatialization of the sound field in a room, in particular the evolution of room impulse responses as function of their spatial positions. The presented technique allows us to completely characterize the sound field in any arbitrary location if the sound field is known in a certain finite number of positions. In this paper, we include an analytical solution of the problem for any rectangular room. Further results on reconstruction of the sound field by interpolation of the Plenacoustic function

An alternative structure for adaptive linear prediction is proposed in which the adaptive filter is replaced by a cascade of inde- pendently adapting, low-order stages, and the prediction is generated by means of successive refinements. When the adaptation algorithm for the stages is LMS, the associated short filters are less affected by eigenvalue spread and mode coupling problems and display a faster convergence to their steady-state value. Experimental results show that a cascade of second-order LMS filt

The emergence of wavelets has led to a convergence of linear expansion methods used in signal processing and applied mathematics. In particular, subband coding methods and their associated filters are closely related to wavelet constructions. We first review such constructions with a signal processing perspective. We then discuss the idea behind signal adapted bases and associated algorithms before showing how wavelets and subband coding methods are used in signal compression applications.

The purpose of this paper is to develop methods that can reconstruct a bandlimited discrete-time signal from an irreg- ular set of samples at unknown locations. We define a solution to the problem using first a geometric and then an algebraic point of view. We find the locations of the irregular set of samples by treating the problem as a combinatorial optimization problem. We employ an exhaustive method and two descent methods: the random search and cyclic coordinate methods. The numerical simulations were

Lensless cameras replace traditional optics with thin masks, leading to highly multiplexed measurements akin to encryption. However, static masks in conventional designs leave systems vulnerable to simple attacks. This work explores the use of programmable masks to enhance security by dynamically varying the mask patterns. We perform our experiments with a low-cost system (around 100 USD) based on a liquid crystal display. Experimental results demonstrate that variable masks successfully block a variety of

We study network capacity limits and optimal routing algorithms for regular sensor networks, namely, square and torus grid sensor networks, in both, the static case (no node failures) and the dynamic case (node failures). For static networks, we derive upper bounds on the network capacity and then we characterize and provide optimal routing algorithms whose rate per node is equal to this upper bound, thus, obtaining the exact analytical expression for the network capacity. We also provide the scaling law fo

We consider the problem of low-complexity channel estimation in digital ultra-wideband receivers. We extend some of our recent sampling results for certain classes of parametric non-bandlimited signals and develop several methods that take advantage of transform techniques to estimate channel parameters from a low-dimensional subspace of a received signal, that is, by sampling the signal below the Nyquist rate. By lowering the sampling rate we reduce computational requirements compared to current digital so

We consider the problem of sampling signals which are not bandlimited, but still have a finite number of degrees of freedom per unit of time, such as, for example, piecewise polynomials. We demonstrate that by using an adequate sampling kernel and a sampling rate greater or equal to the number of degrees of freedom per unit of time, one can uniquely reconstruct such signals. This proves a sampling theorem for a wide class of signals beyond bandlimited signals. Applications of this sampling theorem can be fo

We propose a quadtree segmentation based denoising algo- rithm, which attempts to capture the underlying geometrical structure hidden in real images corrupted by random noise. The algorithm is based on the quadtree coding scheme pro- posed in our earlier work [12, 13] and on the key insight that the lossy compression of a noisy signal can provide the fil- tered/denoised signal. The key idea is to treat the denoising problem as the compression problem at low rates. The in- tuition is that, at low rates, the

This paper studies the rate distortion behavior of sparse memoryless sources that serve as models of sparse signal representations. For the Hamming distortion criterion,

R(D)

is shown to be essentially linear. For the mean squared error measure, two models are analyzed: the mixed discrete/continuous spike processes and Gaussian mixtures. The latter are shown to be a better model for ``natural'' data such as sparse wavelet coefficients. Finally, the geometric mean of a continuous random variable is introdu

Subband and wavelet decompositions are powerful tools in image coding because of their decorrelating effects on image pixels, the concentration of energy in a few coefficients, their multirate/multiresolution framework, and their frequency splitting, which allows for efficient coding matched to the statistics of each frequency band and to the characteristics of the human visual system. Vector quantization (VQ) provides a means of converting the decomposed signal into bits in a manner that takes advantage of

Gradient based microphone arrays, the horizontal sound field's plane wave decomposition, and the corresponding circular harmonics decomposition are reviewed. Further, a general relation between directivity patterns of the horizontal sound field gradients and the circular harmonics of any order is derived. Based on this relation, a number of example differential microphone arrays are analyzed, including arrays capable of approximating the sound pressure gradients necessary for obtaining the circular harmonic

Considers the construction of orthogonal time-varying filter banks. By examining the time domain description of the two-channel orthogonal filter bank the authors find it possible to construct a set of orthogonal boundary filters, which allows to apply the filter bank to one-sided or finite-length signals, without redundancy or distortion. The method is constructive and complete. There is a whole space of orthogonal boundary solutions, and there is considerable freedom for optimization. This may be used to

Recently we have proposed a new image device called the gigavision camera. The main feature of this camera is that the pixels have a binary response. The response function of a gigavision sensor is non-linear and similar to a logarithmic function, which ma ...

Martin Vetterli

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Optimal Filter Banks for Multiple Description Coding: Analysis and Synthesis

On Pixel Detection Threshold in the Gigavision Camera

Rate-Distortion Optimized Tree-Structured Compression Algorithms for Piecewise Polynomial Images

Notre environnement devient intelligent

A new robust and efficient estimator for ill-conditioned linear inverse problems with outliers

Distributed Sensing of Signals under a Sparse Filtering Model

Acoustic Based Rendering by Interpolation of the Plenacoustic Function

An FIR cascade structure for adaptive linear prediction

Wavelets, subband coding, and best bases

Reconstruction of irregularly sampled discrete-time bandlimited signals with unknown sampling locations

Encryption and Authentication with a Lensless Camera Based on a Programmable Mask

Lattice Sensor Networks: Capacity Limits, Optimal Routing and Robustness to Failures

Low-Complexity Subspace Methods for Channel Estimation and Synchronization in Ultra-Wideband Systems

A sampling theorem for periodic piecewise polynomial signals

Geometrical Image Denoising Using Quadtree Segmentation

Rate Distortion Behavior of Sparse Sources

Vector quantization of image subbands: a survey

Sound Field Recording by Measuring Gradients

Orthogonal time-varying filter banks and wavelet packets

Image Reconstruction in the Gigavision Camera