Publications by Martin Vetterli

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This paper deals with multiwavelets which are a recent generalization of wavelets in the context of multirate filter banks and with their applications to signal processing and especially compression. By their inherent structure, multiwavelets are fit for processing multi-channel signals. First, we will recall some general results on multifilters by looking at them as time-varying filters. Then, we will link this to multiwavelets, looking closely at the convergence of the iterated matrix product leading to t

Wireless sensor networks are often designed to perform two tasks: sensing a physical field and transmitting the data to end-users. A crucial aspect of the design of a WSN is the minimization of the overall energy consumption. Previous researchers aim at optimizing the energy spent for the communication, while mostly ignoring the energy cost due to sensing. Recently, it has been shown that considering the sensing energy cost can be beneficial for further improving the overall energy efficiency. More precisel

The successful design of sensor network architectures depends crucially on the structure of the sampling, observation, and communication processes. One of the most fundamental questions concerns the sufficiency of discrete approximations in time, space, an ...

According to a first aspect of the present invention there is provided a method of estimating, jointly, a set of multipath channels having a common path support, the method comprising the steps of, estimating jointly the common path support of the set of m ...

We address the problem of distributed compression in acoustic sensor networks. A typical scenario consists of a set of microphones that record a sound source located at some unknown position. The goal then is to convey the corresponding audio signals to a ...

With a novel, less classical approach to the subject, the authors have written a book with the conviction that signal processing should be taught to be fun. The threatment is therefore less focused on the mathematics and more on the conceptual aspects, the idea being to allow the readers to think about the subject at a higher conceptual level, thus building the foundations for more advanced topics. The book remains an engineering text, with the goal of helping students solve real-world problems. In this vei

Gossip algorithms have recently received significant attention, mainly because they constitute simple and robust mes- sage-passing schemes for distributed information processing over networks. However, for many topologies that are realistic for wire- less ...

This chapter is a review of multiresolution source and channel coding techniques as applicable in wireless transmission. The focus is on image and video compression and transmission. Section 1 gives an introduction and a review of the separation principle and its limitations. Section 2 is an overview of multiresolution source coding techniques. Section 3 present multiresolution channel coding techniques. Section 4 develops multiresolution joint source and channel coding and Section 5 gives the conclusion.

Fourier transforms are an often necessary component in many computational tasks, and can be computed efficiently through the fast Fourier transform (FFT) algorithm. However, many applications involve an underlying continuous signal, and a more natural choi ...

The Karhunen–Loève transform (KLT) is optimal for trans- form coding of a Gaussian source. This is established for all scale-invariant quantizers, generalizing previous results. A backward adaptive technique for combating the data dependence of the KLT is proposed and analyzed. When the adapted transform converges to a KLT, the scheme is universal among transform coders. A variety of convergence results are proven.

Hearing aids are electronic, battery-operated sensing devices which aim at compensating various kinds of hearing impairments by means of appropriate signal processing. Most of today's hearing aid systems consist of two appliances working independently of e ...

Frequently, we use the Moore-Penrose pseudoinverse (MPP) even in cases when we do not require all of its defining properties. But if the running time and the storage size are critical, we can do better. By discarding some constraints needed for the MPP, we gain freedom to optimize other aspects of the new pseudoinverse. A sparser pseudoinverse reduces the amount of computation and storage. We propose a method to compute a sparse pseudoinverse and show that it offers sizable improvements in speed and storage

Relightable photographs are alternatives to traditional photographs as they provide a richer viewing experience. However, the complex acquisition systems of existing techniques have restricted its usage to specialized setups. We introduce an easy-to-use an ...

The polyphase representation with respect to sampling lattices in multidimensional (M-D) multirate signal processing allows us to identify perfect reconstruction (PR) filter banks with unimodular Laurent polynomial matrices, and various problems in the design and analysis of invertible MD multirate systems can be algebraically formulated with the aid of this representation. While the resulting algebraic problems can be solved in one dimension (1-D) by the Euclidean Division Algorithm, we show that Gröbner b

Oversampled analog-to-digital conversion is a technique which permits high conversion resolution using coarse quantization. Classically, by lowpass filtering the quantized oversampled signal, it is possible to reduce the quantization error power in proportion to the oversampling ratio R. In other words, the reconstruction mean-squared error (MSE) is in

Coefficient quantization has peculiar qualitative ef- fects on representations of vectors in R^n with respect to over- complete sets of vectors. These effects are investigated in two settings: frame expansions (representations obtained by forming inner products with each element of the set) and matching pursuit expansions (approximations obtained by greedily forming linear combinations). In both cases, based on the concept of consistency, it is shown that traditional linear reconstruction methods are subopt

Recent methods for localization of microphones in a microphone array exploit sound sources at a priori unknown locations. This is convenient for ad-hoc arrays, as it requires little additional infrastructure. We propose a flexible localization algorithm by ...

Estimation of the quantities of harmful substances emitted into the atmosphere is one of the main challenges in modern environmen- tal sciences. In most of the cases, this estimation requires solving a linear inverse problem. A key difficulty in evaluating the performance of any algorithm to solve this linear inverse problem is that the ground truth is typically unknown. In this paper we show that the noise encountered in this linear inverse problem is non-Gaussian. Next, we develop an algorithm to deal wit

Packet video is investigated from a systems point of view. The most important issues to its transmission are identified and studied in the context of a layered architecture model. This leads to a better understanding of the interactions between network and signal handling. The functions at a particular layer can thereby be made least dependent on network implementation and signal format. In the model, the higher layers provide format conversion, hierarchical source coding, error recovery, resynchronization,

In this paper, we briefly review the connection between subband coding, wavelet approximation and general compression problems. Wavelet or subband coding is successful in compression applications partly because of the good approximation properties of wavelets. First, we revisit some rate-distortion bounds for wavelet approximation of piecewise smooth functions. We contrast these results with rate-distortion bounds achievable using oracle based methods. We indicate that such bounds are achievable in practice

Martin Vetterli

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Balanced MultiWavelets - Theory and Design

DASS: Distributed Adaptive Sparse Sensing

Sensing reality and communicating bits: A dangerous liaison

ESTIMATING SPARSE MIMO CHANNELS HAVING COMMON SUPPORT

Distributed Compression in Acoustic Sensor Networks Using Oversampled A/D Conversion

Signal Processing for Communications

Order-Optimal Consensus Through Randomized Path Averaging

Multiresolution Joint Source and Channel Coding

pyFFS: A Python Library for Fast Fourier Series Computation and Interpolation with GPU Acceleration

Transform coding with backwards adaptive updates

Collaborating Hearing Aids

Beyond Moore-Penrose: Sparse Pseudoinverse

Handheld reflectance acquisition of paintings

Groebner bases and multidimensional FIR multirate systems

Lower Bound on the Mean-Squared Error in Oversampled Quantization of Periodic Signals Using Vector Quantization Analysis

Quantized overcomplete expansions in IRN: Analysis, synthesis and algorithms

Relax and Unfold: Microphone Localization with Euclidean Distance Matrices

Outlier removal for improved source estimation in atmospheric inverse problems

Packet video and its integration into the network architecture

Wavelets: approximation and compression--a review