Publications by Martin Vetterli

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The method of wavelet thresholding for removing noise, or denoising, has been researched extensively due to its effectiveness and simplicity. Much of the literature has focused on developing the best uniform threshold or best basis selection. However, not much has been done to make the threshold values adaptive to the spatially changing statistics of images. Such adap- tivity can improve the wavelet thresholding performance because it allows additional local information of the image (such as the identificat

In recent work, it was proposed to use lossy compression to remove noise from corrupted signals, based on the rationale that a reasonable compression method retains the dominant signal features more than the randomness of the noise. To further understand and substantiate this theory, we first explain why compression (via coefficient quantization) is appropriate for filter thresholding for denoising. That is, denoising is mainly due to the zero-zone and that the full precision of the thresholded coefficients

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 ...

In recent years, the “Internet Multicast Backbone,” or MBone, has risen from a small, research curiosity to a large- scale and widely used communications infrastructure. A driving force behind this growth was the development of multipoint audio, video, and shared whiteboard conferencing applications. Because these real-time media are transmitted at a uniform rate to all of the receivers in the network, a source must either run at the bottleneck rate or overload portions of its multicast distribution tree. W

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 ...

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 ...

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 ...

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 ...

The authors formalize the description of the buffer-constrained adaptive quantization problem. For a given set of admissible quantizers used to code a discrete nonstationary signal sequence in a buffer-constrained environment, they formulate the optimal solution. They also develop slightly suboptimal but much faster approximations. These solutions are valid for any globally minimum distortion criterion, which is additive over the individual elements of the sequence. As a first step, they define the problem

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 ...

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 ...

In opportunistic routing, each node maintains a group of candidate next-hops to reach a particular destination, and transmits packets to any node in this group. The choice of candidate next-hops at each node is a key question that is central to the performance of opportunistic routing. This paper addresses the least-cost opportunistic routing (LCOR) problem: how to assign the set of candidate next-hops at each node for a given destination such that the expected cost of forwarding a packet to the destination

In this paper, we discuss a framework for the distributed compression of vector sources, based on our previous work on distributed transform coding. In particular, our goal is to develop a strategy of first applying a suitable distributed Karhunen-Loeve transform, whereafter each component can be andled by standard distributed compression techniques. In the present paper, we first study the scenario where all but one terminal furnish a noisy approximation of their observation. For the case where the underly

is paper deals with the deterministic analysis of oversampled A/D conversion (ADC), the properties derivable from such an analysis, and the consequences on reconstruc- tion using nonlinear decoding. Given a bandlimited input X producing a quantized version C , we consider the set of all input signals that are bandlimited and produce C. We call any element of this set a consistent estimate of X. Regardless of the type of encoder (simple, predictive, or noise-shaping), we show that this set is convex, and as

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 ...

We consider the problem of video multicast over networks that enforce fair bandwidth allocations in the routers. State-of-the-art layered IP multicast systems perform well for moderately sized sessions, but suffer from three basic problems that prevent their massive deployment: (a) lack of fairness among different multicast sessions, (b) lack of fairness to competing TCP flows, and (c) high complexity requirements to scale up to potentially large numbers of users and sessions. In this work we present an ent

The matching pursuit algorithm can be used to derive signal decompositions in terms of the elements of a dictionary of time-frequency atoms. Using a structured overcomplete dictionary yields a signal model that is both parametric and signal-adaptive. In this paper, we apply matching pursuit to the derivation of signal expansions based on damped sinusoids. It is shown that expansions in terms of complex damped sinusoids can be efficiently derived using simple recursive filter banks. We discuss a subspace ext

Accuracy of oversampled analog-to-digital (A/D) conversion, the dependence of accuracy on the sampling interval, t, and on the bit rate are characteristics fundamental to A/D conversion but not completely understood. These characteristics are studied in this paper for oversampled A/D conversion of band-limited signals in L^2(R). We show that the digital sequence obtained in the process of oversampled A/D conversion describes the corresponding analog signal with an error which tends to zero as t^2 in energy,

In signal processing systems, aliasing is normally treated as a disturbing signal. That motivates the need for effective analog, optical and digital anti-aliasing filters. However, aliasing conveys also valuable information on the signal above the Nyquist frequency. Hence, an effective processing of the samples, based on a model of the input signal, would allow to virtually increase the sampling frequency using slower and cheaper converters. In this paper, we present such an algorithm for bandlimited signal

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 ...

Martin Vetterli

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Spatially adaptive wavelet thresholding with context modeling for image denoising

Lossy compression and wavelet thresholding for image denoising

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

Low-complexity video coding for receiver-driven layered multicast

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

Sequences with Minimal Time-Frequency Spreads

Computationally efficient background subtraction in the light field domain

Euclidean Distance Matrices: Essential Theory, Algorithms and Applications

Optimal trellis-based buffered compression and fast approximations

VITRAIL : Acquisition, Modelling and Rendering of Stained Glass

How Asynchronous Events Encode Video

Least-Cost Opportunistic Routing

On Compression Using the Distributed Karhunen-Loeve Transform

Deterministic analysis of oversampled A/D conversion and decoding improvement based on consistent estimates

Topology Optimization For Energy-Efficient Communications In Consensus Wireless Networks

Video multicast over fair queueing networks

Matching pursuit and atomic signal models based on recursive filter banks

On simple oversampled A/D conversion in L2(R)

How to take advantage of aliasing in bandlimited signals

Reproducing Sound Fields Using MIMO Acoustic Channel Inversion