High compression ratio, scalability and reliability are the main issues for transmitting multimedia content over best effort networks. Scalable image and video coding meets the user requirements by truncating the scalable bitstream at different quality, resolution and frame rate. However, the performance of scalable coding deteriorates rapidly over packet networks if the base layer packets are lost during transmission. Multiple description coding (MDC) has emerged as an effective source coding technique for robust image and video transmission over lossy networks. In this research problem of incorporating scalability in MDC for robust image and video transmission over best effort network is addressed. The first contribution of this thesis is to propose a strategy for generating more than two descriptions using multiple description scalar quantizer (MDSQ) with an objective to jointly decoded any number of descriptions in balanced and unbalanced manner. The ...

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 ...

In the current heterogeneous communication environments, the great variety of multimedia systems and applications combined with fast evolution of networking architectures and topologies, give rise to new research problems related to the various elements of the communication chain. This includes, the ever present problem in video communications, which results from the need for coping with transmission errors and losses. In this context, video streaming with path diversity appeared as a novel communication framework, involving different technological fields and posing several research challenges. The research work carried out in this thesis is a contribution to robust video coding and adaptation techniques in the field of Multiple Description Coding (MDC) for multipath video streaming. The thesis starts with a thorough study of MDC and its theoretical basis followed by a description of the most important practical implementation aspects currently available in literature. ...

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 ...

Advanced nuclear medical imaging systems collect multiple attributes of a large number of photon events, resulting in extremely large datasets which present challenges to image reconstruction and assessment. This dissertation addresses several of these challenges. The image formation process in nuclear medical imaging can be posed as a parametric estimation problem where the image pixels are the parameters of interest. Since nuclear medical imaging applications are often ill-posed inverse problems, unbiased estimators result in very noisy, high-variance images. Typically, smoothness constraints and a priori information are used to reduce variance in medical imaging applications at the cost of biasing the estimator. For such problems, there exists an inherent tradeoff between the recovered spatial resolution of an estimator, overall bias, and its statistical variance; lower variance can only be bought at the price of decreased spatial resolution and/or increased overall bias. ...

In the last decade, one of the most significant technological developments that led to the new broadband wireless generation is the communication via multiple-input multiple-output (MIMO) systems. MIMO technologies have been adopted by many wireless standards such as Long Term Evolution (LTE), Wordlwide interoperability for Microwave Access (WiMAX) and Wireless Local Area Network (WLAN). This is mainly due to their ability to increase the maximum transmission rates, together with the achieved reliability and coverage of current wireless communications, all without the need for additional bandwidth nor transmit power. Nevertheless, the advantages provided by MIMO systems come at the expense of a substantial increase in the cost to deploy multiple antennas and also in the receiver complexity, which has a major impact on the power consumption. Therefore, the design of low-complexity receivers is an important issue which is tackled throughout this ...

Wideband wireless access based on direct-sequence code-division multiple access (DS-CDMA) has been adopted for third-generation mobile communications systems. Hence, DS-CDMA downlink communications systems form the platform for the work in this thesis. The principles of the spread spectrum concept and DS-CDMA technology are first outlined, including a description of the system model and the conventional receiver. The two classes of codes used in this system, namely spreading codes and forward error correction codes (including Turbo codes), are discussed. Due to the fact that practical communications channels are non-ideal, the performance of an individual user is interference limited. As a result, the capacity of the system is greatly restricted. Fortunately, multiuser detection is a scheme that can effectively counteract this multiple access interference. However, the optimum multiuser detection scheme is far too computationally intensive for practical use. Hence, the fundamental interest ...

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Adaptive filtering techniques are used in a wide range of applications, including echo cancellation, adaptive equalization, adaptive noise cancellation, and adaptive beamforming. The performance of an adaptive filtering algorithm is evaluated based on its convergence rate, misadjustment, computational requirements, and numerical robustness. We attempt to improve the performance by developing new adaptation algorithms and by using "unconventional" structures for adaptive filters. Part I of this dissertation presents a new adaptation algorithm, which we have termed the Normalized LMS algorithm with Orthogonal Correction Factors (NLMS-OCF). The NLMS-OCF algorithm updates the adaptive filter coefficients (weights) on the basis of multiple input signal vectors, while NLMS updates the weights on the basis of a single input vector. The well-known Affine Projection Algorithm (APA) is a special case of our NLMS-OCF algorithm. We derive convergence and tracking properties of NLMS-OCF using a simple model ...

Multiple-input multiple-output (MIMO) systems have recently emerged as one of the most significant wireless techniques, as they can greatly improve the channel capacity and link reliability of wireless communications. These benefits have encouraged extensive research on a virtual MIMO system where the transmitter has multiple antennas and each of the receivers has a single antenna. Single-antenna receivers can work together to form a virtual antenna array and reap some performance benefits of MIMO systems. The idea of receiver-side local cooperation is attractive for wireless networks since a wireless receiver may not have multiple antennas due to size and cost limitations. In this thesis we investigate a virtual-MIMO wireless system using the receiver-side cooperation with the compress-and-forward (CF) protocol. Firstly, to perform CF at the relay, we propose to use standard source coding techniques, based on the analysis of its expected ...

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 ...

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One desideratum in designing cognitive robots is autonomous learning of communication skills, just like humans. The primary step towards this goal is vocabulary acquisition. Being different from the training procedures of the state-of-the-art automatic speech recognition (ASR) systems, vocabulary acquisition cannot rely on prior knowledge of language in the same way. Like what infants do, the acquisition process should be data-driven with multi-level abstraction and coupled with multi-modal inputs. To avoid lengthy training efforts in a word-by-word interactive learning process, a clever learning agent should be able to acquire vocabularies from continuous speech automatically. The work presented in this thesis is entitled \emph{Constrained Non-negative Matrix Factorization for Vocabulary Acquisition from Continuous Speech}. Enlightened by the extensively studied techniques in ASR, we design computational models to discover and represent vocabularies from continuous speech with little prior knowledge of the language to ...

Feedback in wireless communications is tied to a long-standing and successful history, facilitating robust and spectrally efficient transmission over the uncertain wireless medium. Since the application of multiple antennas at both ends of the communication link, enabling multiple-input multiple-output (MIMO) transmission, the importance of feedback information to achieve the highest performance is even more pronounced. Especially when multiple antennas are employed by the transmitter to handle the interference between multiple users, channel state information (CSI) is a fundamental prerequisite. The corresponding multi-user MIMO, interference alignment and coordination techniques are considered as a central part of future cellular networks to cope with the growing inter-cell-interference, caused by the unavoidable densification of base stations to support the exponentially increasing demand on network capacities. However, this vision can only be implemented with efficient feedback algorithms that provide accurate CSI at the transmitter without ...