The increasing number of simultaneous input and output channels utilized in immersive audio configurations primarily in broadcasting applications has renewed industrial requirements for efficient audio coding schemes with low bit-rate and complexity. This thesis presents a comprehensive review and extension of conventional approaches for perceptual coding of arbitrary multichannel audio signals. Particular emphasis is given to use cases ranging from two-channel stereophonic to six-channel 5.1-surround setups with or without the application-specific constraint of low algorithmic coding latency. Conventional perceptual audio codecs share six common algorithmic components, all of which are examined extensively in this thesis. The first is a signal-adaptive filterbank, constructed using instances of the real-valued modified discrete cosine transform (MDCT), to obtain spectral representations of successive portions of the incoming discrete time signal. Within this MDCT spectral domain, various intra- and inter-channel optimizations, most of which are of ...

In recent years, the usage of digital video has steadily been increasing. Since the amount of data for uncompressed digital video representation is very high, lossy source coding techniques are usually employed in digital video systems to compress that information and make it more suitable for storage and transmission. The source coding algorithms for video compression can be grouped into two big classes: the traditional and the scalable techniques. The goal of the traditional video coders is to maximize the compression efficiency corresponding to a given amount of compressed data. The goal of scalable video coding is instead to give a scalable representation of the source, such that subsets of it are able to describe in an optimal way the same video source but with reduced resolution in the temporal, spatial and/or quality domain. This thesis is focused on the ...

The objectives of the research were to develop embedded and non-embedded lossy coding algorithms for images based on lattice vector quantisation and the discrete wavelet transform. We also wanted to develop context-based entropy coding methods (as opposed to simple first order entropy coding). The main objectives can therefore be summarised as follows: (1) To develop algorithms for intra and inter-band formed vectors (vectors with coefficients from the same sub-band or across different sub-bands) which compare favourably with current high performance wavelet based coders both in terms of rate/distortion performance of the decoded image and also subjective quality; (2) To develop new context-based coding methods (based on vector quantisation). The alternative algorithms we have developed fall into two categories: (a) Entropy coded and Binary uncoded successive approximation lattice vector quantisation (SALVQ- E and SA-LVQ-B) based on quantising vectors formed intra-band. This ...

With the joint development of networking and digital coding technologies multimedia and more particularly video services are clearly becoming one of the major consumers of the new information networks. The rapid growth of the Internet and computer industry however results in a very heterogeneous infrastructure commonly overloaded. Video service providers have nevertheless to oer to their clients the best possible quality according to their respective capabilities and communication channel status. The Quality of Service is not only inuenced by the compression artifacts, but also by unavoidable packet losses. Hence, the packet video stream has clearly to fulll possibly contradictory requirements, that are coding eciency and robustness to data loss. The rst contribution of this thesis is the complete modeling of the video Quality of Service (QoS) in standard and more particularly MPEG-2 applications. The performance of Forward Error Control (FEC) ...

This thesis proposes different methods to reduce the computational complexity as well as increasing the adaptation rate of adaptive broadband beamformers. This is performed exemplarily for the generalised sidelobe canceller (GSC) structure. The GSC is an alternative implementation of the linearly constrained minimum variance beamformer, which can utilise well-known adaptive filtering algorithms, such as the least mean square (LMS) or the recursive least squares (RLS) to perform unconstrained adaptive optimisation. A direct DFT implementation, by which broadband signals are decomposed into frequency bins and processed by independent narrowband beamforming algorithms, is thought to be computationally optimum. However, this setup fail to converge to the time domain minimum mean square error (MMSE) if signal components are not aligned to frequency bins, resulting in a large worst case error. To mitigate this problem of the so-called independent frequency bin (IFB) processor, overlap-save ...

Digital holography is a discipline of science that measures or reconstructs the wavefield of light by means of interference. The wavefield encodes three-dimensional information, which has many applications, such as interferometry, microscopy, non-destructive testing and data storage. Moreover, digital holography is emerging as a display technology. Holograms can recreate the wavefield of a 3D object, thereby reproducing all depth cues for all viewpoints, unlike current stereoscopic 3D displays. At high quality, the appearance of an object on a holographic display system becomes indistinguishable from a real one. High-quality holograms need large volumes of data to be represented, approaching resolutions of billions of pixels. For holographic videos, the data rates needed for transmitting and encoding of the raw holograms quickly become unfeasible with currently available hardware. Efficient generation and coding of holograms will be of utmost importance for future holographic displays. ...

In this work, we study the application of wavelet analysis for robust speech processing. Reliable time-scale features (TS) which characterize the relevant phonetic classes such as voiced (V), unvoiced (UV), silence (S), mixed-excitation, and stop sounds are extracted. By training neural and Bayesian networks, the classification rates provided by only 7 TS features are mostly similar to the ones obtained by 13 MFCC features. The TS features are further enhanced to design a reliable and low-complexity V/UV/S classifier. Quantile filtering and slope tracking are used for deriving adaptive thresholds. A robust voice activity detector is then built and used as a pre-processing stage to improve the performance of a speaker verification system. Based on wavelet shrinkage, a statistical wavelet filtering (SWF) method is designed for speech enhancement. Non-stationary and colored noise is handled by employing quantile filtering and time-frequency adaptive ...

There are an increasing number of problems that can be solved using paraunitary filter banks. The design of optimal orthonormal filter banks for the efficient coding of signals has received considerable interest over the years. In contrast, very little attention has been given to the problem of constructing paraunitary matrices for the purpose of broadband signal subspace estimation. This thesis begins by relating these two areas of research. A frequency-domain method of diagonalising parahermitian polynomial matrices is proposed and shown to have fundamental limitations. Then the thesis focuses on the development of a novel time-domain technique that extends the eigenvalue decomposition to polynomial matrices, referred to as the second order sequential best rotation (SBR2) algorithm. This technique imposes strong decorrelation on its input signals by applying a sequence of elementary paraunitary matrices which constitutes a generalisation of the classical Jacobi ...

A wide range of techniques for coding a single-channel speech and audio signal has been developed over the last few decades. In addition to pure redundancy reduction, sophisticated source and receiver models have been considered for reducing the bit-rate. Traditionally, speech and audio coders are based on different principles and thus each of them offers certain advantages. With the advent of high capacity channels, networks, and storage systems, the bit-rate versus quality compromise will no longer be the major issue; instead, attributes like low-delay, scalability, computational complexity, and error concealments in packet-oriented networks are expected to be the major selling factors. Typical audio coders such as MP3 and AAC are based on subband or transform coding techniques that are not easily reconcilable with a low-delay requirement. The reasons for their inherently longer delay are the relatively long band splitting filters ...

In nowadays communication systems, error correction provides robust data transmission through imperfect (noisy) channels. Error correcting codes are a crucial component in most storage and communication systems – wired or wireless –, e.g. GSM, UMTS, xDSL, CD/DVD. At least as important as the data integrity issue is the recent realization that error correcting codes fundamentally change the trade-offs in system design. High-integrity, low redundancy coding can be applied to increase data rate, or battery life time or by reducing hardware costs, making it possible to enter mass market. When it comes to the design of error correcting codes and their properties, there are two main theories that play an important role in this work. Classical coding theory aims at finding the best code given an available block length. This thesis focuses on the ubiquitous Reed-Solomon codes, one of the major ...

Scalable representation of a source (e.g., image/video/3D mesh) enables decoding of the encoded bit-stream on a variety of end-user terminals with varying display, storage and processing capabilities. Furthermore, it allows for source communication via channels with different transmission bandwidths, as the source rate can be easily adapted to match the available channel bandwidth. From a different perspective, error-resilience against channel losses is also very important when transmitting scalable source streams over lossy transmission channels. Driven by the aforementioned requirements of scalable representation and error-resilience, this dissertation focuses on the analysis and design of scalable single and multiple description scalar quantizers. In the first part of this dissertation, we consider the design of scalable wavelet-based semi-regular 3D mesh compression systems. In this context, our design methodology thoroughly analyzes different modules of the mesh coding system in order to single-out appropriate design ...

This thesis faces the problem of automatically classifying environmental sounds, i.e., any non-speech or non-music sounds that can be found in the environment. Broadly speaking, two main processes are needed to perform such classification: the signal feature extraction so as to compose representative sound patterns and the machine learning technique that performs the classification of such patterns. The main focus of this research is put on the former, studying relevant signal features that optimally represent the sound characteristics since, according to several references, it is a key issue to attain a robust recognition. This type of audio signals holds many differences with speech or music signals, thus specific features should be determined and adapted to their own characteristics. In this sense, new signal features, inspired by the human auditory system and the human perception of sound, are proposed to improve ...

This thesis deals with the coding of images with multiple coding schemes and their dynamic selection. In our society of information highways, electronic communication is taking everyday a bigger place in our lives. The number of transmitted images is also increasing everyday. Therefore, research on image compression is still an active area. However, the current trend is to add several functionalities to the compression scheme such as progressiveness for more comfortable browsing of web-sites or databases. Classical image coding schemes have a rigid structure. They usually process an image as a whole and treat the pixels as a simple signal with no particular characteristics. Second generation schemes use the concept of objects in an image, and introduce a model of the human visual system in the design of the coding scheme. Dynamic coding schemes, as their name tells us, make ...

Distributed source coding is a technique that allows to compress several correlated sources, without any cooperation between the encoders, and without rate loss provided that the decoding is joint. Motivated by this principle, distributed video coding has emerged, exploiting the correlation between the consecutive video frames, tremendously simplifying the encoder, and leaving the task of exploiting the correlation to the decoder. The first part of our contributions in this thesis presents the asymmetric coding of binary sources that are not uniform. We analyze the coding of non-uniform Bernoulli sources, and that of hidden Markov sources. For both sources, we first show that exploiting the distribution at the decoder clearly increases the decoding capabilities of a given channel code. For the binary symmetric channel modeling the correlation between the sources, we propose a tool to estimate its parameter, thanks to an ...

Video signals are sequences of natural images, where images are often modeled as piecewise-smooth signals. Hence, video can be seen as a 3D piecewise-smooth signal made of piecewise-smooth regions that move through time. Based on the piecewise-smooth model and on related theoretical work on rate-distortion performance of wavelet and oracle based coding schemes, one can better analyze the appropriate coding strategies that adaptive video codecs need to implement in order to be efficient. Efficient video representations for coding purposes require the use of adaptive signal decompositions able to capture appropriately the structure and redundancy appearing in video signals. Adaptivity needs to be such that it allows for proper modeling of signals in order to represent these with the lowest possible coding cost. Video is a very structured signal with high geometric content. This includes temporal geometry (normally represented by motion ...