In digital video compression, apart from storage, successful transmission of the compressed video data over the bandwidth limited erroneous channels is another important issue. To enable a video codec for broadcasting application, it is required to implement the corresponding coding tools (e.g. error-resilient coding, rate control etc.). They are normally non-normative parts of a video codec and hence their specifications are not defined in the standard. In Dirac as well, the original codec is optimized for storage purpose only and so, several non-normative part of the encoding tools are still required in order to be able to use in other types of application. Being the "Research and Developments of the Dirac Video Codec" as the research title, phase I of the project is mainly focused on the error-resilient transmission over a noisy channel. The error-resilient coding method used here is a simple and low complex coding scheme which provides the error-resilient transmission of the compressed video bitstream of Dirac video encoder over the packet erasure wired network. The scheme combines source and channel coding approach where error-resilient source coding is achieved by data partitioning in the wavelet transformed domain and channel coding is achieved through the application of either Rate-Compatible Punctured Convolutional (RCPC) Code or Turbo Code (TC) using un-equal error protection between header plus MV and data. The scheme is designed mainly for the packet-erasure channel, i.e. targeted for the Internet broadcasting application. But, for a bandwidth limited channel, it is still required to limit the amount of bits generated from the encoder depending on the available bandwidth in addition to the error-resilient coding. So, in the 2nd phase of the project, a rate control algorithm is presented. The algorithm is based upon the Quality Factor (QF) optimization method where QF of the encoded video is adaptively changing in order to achieve average bitrate which is constant over each Group of Picture (GOP). A relation between the bitrate, R and the QF, which is called Rate-QF (R-QF) model is derived in order to estimate the optimum QF of the current encoding frame for a given target bitrate, R. In some applications like video conferencing, real-time encoding and decoding with minimum delay is crucial, but, the ability to do real-time encoding/decoding is largely determined by the complexity of the encoder/decoder. As we all know that motion estimation process inside the encoder is the most time consuming stage. So, reducing the complexity of the motion estimation stage will certainly give one step closer to the real-time application. So, as a partial contribution toward realtime application, in the final phase of the research, a fast Motion Estimation (ME) strategy is designed and implemented. It is the combination of modified adaptive search plus semi-hierarchical way of motion estimation. The same strategy was implemented in both Dirac and H.264 in order to investigate its performance on different codecs. Together with this fast ME strategy, a method which is called partial cost function calculation in order to further reduce down the computational load of the cost function calculation was presented. The calculation is based upon the pre-defined set of patterns which were chosen in such a way that they have as much maximum coverage as possible over the whole block. In summary, this research work has contributed to the error-resilient transmission of compressed bitstreams of Dirac video encoder over a bandwidth limited error prone channel. In addition to this, the final phase of the research has partially contributed toward the real-time application of the Dirac video codec by implementing a fast motion estimation strategy together with partial cost function calculation idea.

Recently, the transmission of vector quantization (VQ) over a code-division multiple access (CDMA) channel has received a considerable attention in research community. The complexity of the optimal decoding for VQ in CDMA communications is prohibitive for implementation, especially for systems with a medium or large number of users. A suboptimal approach to VQ decoding over a CDMA channel, disturbed by additive white Gaussian noise (AWGN), was recently developed. Such a suboptimal decoder is built from a soft-output multiuser detector (MUD), a soft bit estimator and the optimal soft VQ decoders of individual users. <p>Due to its lower complexity and good performance, such a decoding scheme is an attractive alternative to the complicated optimal decoder. It is necessary to extend this decoding scheme for a frequency-selective Rayleigh fading CDMA channel, a channel model typically seen in mobile wireless communications. This is precisely the objective of this thesis. <p>Furthermore, the suboptimal decoders are obtained not only for binary phase shift keying (BPSK), but also for M-ary pulse amplitude modulation (M-PAM). This extension offers a flexible trade-off between spectrum efficiency and performance of the systems. In addition, two algorithms based on distance measure and reliability processing are introduced as other alternatives to the suboptimal decoder. <p>Simulation results indicate that the suboptimal decoders studied in this thesis also performs very well over a frequency-selective Rayleigh fading CDMA channel.

Recently, the transmission of vector quantization (VQ) over a code-division multiple access (CDMA) channel has received a considerable attention in research community. The complexity of the optimal decoding for VQ in CDMA communications is prohibitive for implementation, especially for systems with a medium or large number of users. A suboptimal approach to VQ decoding over a CDMA channel, disturbed by additive white Gaussian noise (AWGN), was recently developed. Such a suboptimal decoder is built from a soft-output multiuser detector (MUD), a soft bit estimator and the optimal soft VQ decoders of individual users. <p>Due to its lower complexity and good performance, such a decoding scheme is an attractive alternative to the complicated optimal decoder. It is necessary to extend this decoding scheme for a frequency-selective Rayleigh fading CDMA channel, a channel model typically seen in mobile wireless communications. This is precisely the objective of this thesis. <p>Furthermore, the suboptimal decoders are obtained not only for binary phase shift keying (BPSK), but also for M-ary pulse amplitude modulation (M-PAM). This extension offers a flexible trade-off between spectrum efficiency and performance of the systems. In addition, two algorithms based on distance measure and reliability processing are introduced as other alternatives to the suboptimal decoder. <p>Simulation results indicate that the suboptimal decoders studied in this thesis also performs very well over a frequency-selective Rayleigh fading CDMA channel.

Distributed three-dimensional (3D) graphics applications exhibit both resemblance and uniqueness in comparison with conventional streaming media applications. The resemblance relates to the large data volume and the bandwidth-limited and error-prone transmission channel. The uniqueness is due to the polygon-based representation of 3D geometric meshes and their accompanying attributes such as textures. This specific data format introduces sophisticated rendering computation to display graphics models and therefore places an additional constraint on the streaming application. The objective of this research is to provide scalable, error-resilient, and time-efficient solutions for high-quality 3D graphics applications in distributed and resource-constrained environments. Resource constraints range from rate-limited and error-prone channels to insufficient data-reception, computing, and display capabilities of client devices. Optimal resource treatment with transmission and rendering scalability is important under such circumstances. The proposed research consists of three milestones. In the first milestone, we develop a joint mesh and texture optimization framework for scalable transmission and rendering of textured 3D models. Then, we address network behaviors and develop a hybrid retransmission and error protection mechanism for the on-demand delivery of 3D models. Next, we advance from individual 3D models to 3D scene databases, which contain numerous objects interacting in one geometric space, and study joint application and transport approaches. By properly addressing the properties of 3D scenes represented in multi-resolution hierarchies, we develop a joint source and channel coding method and a multi-streaming framework for streaming the content-rich 3D scene databases toward optimized transmission and rendering scalability under resource constraints.

The efficient and reliable communication of data from multiple sources to a single receiver plays an important role in emerging applications such as wireless sensor networks. The correlation among observations picked-up by spatially distributed sensors in such a network can be exploited to enhance the efficiency and reliability of communication. In particular, information theory shows that optimal communication of information from correlated sources requires distributed joint source-channel (DJSC) coding. This dissertation develops new approaches to designing DJSC codes based on low density parity check (LDPC) codes. The existence of low complexity code optimization algorithms and decoding algorithms make these codes ideal for joint optimization and decoding of multiple codes operating on correlated sources. The well known EXIT analysis-based LDPC code optimization method for channel coding in single-user point-to-point systems is extended to the optimization of two-user LDPC codes for DJSC coding in multi-access channels (MACs) with correlated users. Considering an orthogonal MAC with two correlated binary sources, an asymptotically optimal DJSC code construction capable of achieving any rate-pair in the theoretically-achievable two-user rate-region is presented. A practical approach to realizing this scheme using irregular LDPC codes is then developed. Experimental results are presented which demonstrate that the proposed codes can approach theoretical bounds when the codeword length is increased. For short codeword length and high inter-source correlation, these DJSC codes are shown to significantly outperform separate source and channel codes. Next, the DJSC code design for the transmission of a pair of correlated binary sources over a Gaussian MAC (GMAC) is investigated. The separate source and channel coding is known to be sub-optimal in this case. For the optimization of a pair of irregular LDPC codes, the EXIT analysis for message passing in a joint factor-graph decoder is analyzed, and an approach to modeling the probability density functions of messages associated with graph nodes which represent the inter-source dependence is proposed. Simulation results show that, for sufficiently large codeword lengths and high inter-source correlation, the proposed DJSC codes for GMAC can achieve rates higher than the theoretical upper bound for separate source and channel coding.

The efficient and reliable communication of data from multiple sources to a single receiver plays an important role in emerging applications such as wireless sensor networks. The correlation among observations picked-up by spatially distributed sensors in such a network can be exploited to enhance the efficiency and reliability of communication. In particular, information theory shows that optimal communication of information from correlated sources requires distributed joint source-channel (DJSC) coding. This dissertation develops new approaches to designing DJSC codes based on low density parity check (LDPC) codes. The existence of low complexity code optimization algorithms and decoding algorithms make these codes ideal for joint optimization and decoding of multiple codes operating on correlated sources. The well known EXIT analysis-based LDPC code optimization method for channel coding in single-user point-to-point systems is extended to the optimization of two-user LDPC codes for DJSC coding in multi-access channels (MACs) with correlated users. Considering an orthogonal MAC with two correlated binary sources, an asymptotically optimal DJSC code construction capable of achieving any rate-pair in the theoretically-achievable two-user rate-region is presented. A practical approach to realizing this scheme using irregular LDPC codes is then developed. Experimental results are presented which demonstrate that the proposed codes can approach theoretical bounds when the codeword length is increased. For short codeword length and high inter-source correlation, these DJSC codes are shown to significantly outperform separate source and channel codes. Next, the DJSC code design for the transmission of a pair of correlated binary sources over a Gaussian MAC (GMAC) is investigated. The separate source and channel coding is known to be sub-optimal in this case. For the optimization of a pair of irregular LDPC codes, the EXIT analysis for message passing in a joint factor-graph decoder is analyzed, and an approach to modeling the probability density functions of messages associated with graph nodes which represent the inter-source dependence is proposed. Simulation results show that, for sufficiently large codeword lengths and high inter-source correlation, the proposed DJSC codes for GMAC can achieve rates higher than the theoretical upper bound for separate source and channel coding.