Iterative joint design of source codes and multiresolution channel codes

We propose an iterative design algorithm for jointly optimizing source and channel codes. The joint design combines channel-optimized vector quantization (COVQ) for the source code with rate-compatible punctured convolutional (RCPC) coding for the channel code. Our objective is to minimize the average end-to-end distortion. For a given channel SNR and transmission rate, our joint source and channel code design achieves an optimal allocation of bits between the source and channel coders. This optimal allocation can reduce distortion by up to 6 dB over suboptimal allocations for the source data set considered. We also compare the distortion of our joint iterative design with that of two suboptimal design techniques: COVQ optimized for a given channel bit-error-probability, and RCPC channel coding optimized for a given vector quantizer. We conclude by relaxing the fixed transmission rate constraint and jointly optimizing the transmission rate, source code, and channel code

Combined source-channel coding for a power and bandwidth constrained noisy channel

This thesis proposes a framework for combined source-channel coding under power and bandwidth constrained noisy channel. The framework is then applied to progressive image coding transmission using constant envelope M-ary Phase Shift Key (MPSK) signaling over an Additive White Gaussian Channel (AWGN) channel. First the framework for uncoded MPSK signaling is developed. Then, its extended to include coded modulation using Trellis Coded Modulation (TCM) for MPSK signaling. Simulation results show that coded MPSK signaling performs 3.1 to 5.2 dB better than uncoded MPSK signaling depending on the constellation size. Finally, an adaptive TCM system is presented for practical implementation of the proposed scheme, which outperforms uncoded MPSK system over all signal to noise ratio (Es/No) ranges for various MPSK modulation formats. In the second part of this thesis, the performance of the scheme is investigated from the channel capacity point of view. Using powerful channel codes like Turbo and Low Density Parity Check (LDPC) codes, the combined source-channel coding scheme is shown to be within 1 dB of the performance limit with MPSK channel signaling

Error-resilient performance of Dirac video codec over packet-erasure channel

Video transmission over the wireless or wired network requires error-resilient mechanism since compressed video bitstreams are sensitive to transmission errors because of the use of predictive coding and variable length coding. This paper investigates the performance of a simple and low complexity error-resilient coding scheme which combines source and channel coding to protect compressed bitstream of wavelet-based Dirac video codec in the packet-erasure channel. By partitioning the wavelet transform coefficients of the motion-compensated residual frame into groups and independently processing each group using arithmetic and Forward Error Correction (FEC) coding, Dirac could achieves the robustness to transmission errors by giving the video quality which is gracefully decreasing over a range of packet loss rates up to 30% when compared with conventional FEC only methods. Simulation results also show that the proposed scheme using multiple partitions can achieve up to 10 dB PSNR gain over its existing un-partitioned format. This paper also investigates the error-resilient performance of the proposed scheme in comparison with H.264 over packet-erasure channel

Design techniques for graph-based error-correcting codes and their applications

In ShannonÂs seminal paper, ÂA Mathematical Theory of CommunicationÂ, he defined ÂChannel Capacity which predicted the ultimate performance that transmission systems can achieve and suggested that capacity is achievable by error-correcting (channel) coding. The main idea of error-correcting codes is to add redundancy to the information to be transmitted so that the receiver can explore the correlation between transmitted information and redundancy and correct or detect errors caused by channels afterward. The discovery of turbo codes and rediscovery of Low Density Parity Check codes (LDPC) have revived the research in channel coding with novel ideas and techniques on code concatenation, iterative decoding, graph-based construction and design based on density evolution. This dissertation focuses on the design aspect of graph-based channel codes such as LDPC and Irregular Repeat Accumulate (IRA) codes via density evolution, and use the technique (density evolution) to design IRA codes for scalable image/video communication and LDPC codes for distributed source coding, which can be considered as a channel coding problem. The first part of the dissertation includes design and analysis of rate-compatible IRA codes for scalable image transmission systems. This part presents the analysis with density evolution the effect of puncturing applied to IRA codes and the asymptotic analysis of the performance of the systems. In the second part of the dissertation, we consider designing source-optimized IRA codes. The idea is to take advantage of the capability of Unequal Error Protection (UEP) of IRA codes against errors because of their irregularities. In video and image transmission systems, the performance is measured by Peak Signal to Noise Ratio (PSNR). We propose an approach to design IRA codes optimized for such a criterion. In the third part of the dissertation, we investigate Slepian-Wolf coding problem using LDPC codes. The problems to be addressed include coding problem involving multiple sources and non-binary sources, and coding using multi-level codes and nonbinary codes

Techniques for unequal error protection.

Ho Man-Shing.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.Includes bibliographical references (leaves 65-66).Abstracts in English and Chinese.Acknowledgement --- p.iAbstract --- p.iiList of Abbreviation --- p.iiiChapter 1. --- Introduction --- p.1Chapter 1.1 --- Digital Communication System --- p.3Chapter 1.2 --- Thesis Organization --- p.4Chapter 2. --- Error-Correcting Codes --- p.6Chapter 2.1 --- Convolutional Codes --- p.7Chapter 2.1.1 --- Generator Polynomials --- p.8Chapter 2.1.2 --- Generator Matrix --- p.9Chapter 2.1.3 --- Circuit Diagram --- p.10Chapter 2.1.4 --- State-transition Diagram --- p.11Chapter 2.1.4 --- Trellis Diagram --- p.12Chapter 2.1.5 --- Distance property --- p.13Chapter 2.2 --- Rate-Compatible Punctured Convolutional Codes --- p.14Chapter 2.3 --- Trellis-Coded Modulation --- p.17Chapter 2.3.1 --- General Model of TCM --- p.18Chapter 2.3.2 --- Trellis Representation --- p.20Chapter 2.3.3 --- Set Partitioning --- p.21Chapter 2.3.4 --- Code Modulation --- p.23Chapter 2.4 --- Decoding Algorithm --- p.25Chapter 2.4.1 --- Viterbi Algorithm --- p.27Chapter 2.4.2 --- List Viterbi Algorithm --- p.30Chapter 3. --- Unequal-Error-Protection for Embedded Image Coder --- p.33Chapter 3.1 --- SPIHT Coder --- p.35Chapter 3.1.1 --- Progressive Image Transmission --- p.36Chapter 3.1.2 --- Set Partitioning Sorting Algorithm --- p.37Chapter 3.1.3 --- Spatial Orientation Trees --- p.38Chapter 3.2 --- System Description --- p.39Chapter 3.3 --- Code Allocation --- p.41Chapter 3.4 --- System Complexity --- p.42Chapter 3.5 --- Simulation Result --- p.43Chapter 4. --- Unequal-Error-Protection Provided by Trellis-Coded Modulation --- p.51Chapter 4.1 --- System Description --- p.52Chapter 4.2 --- Unequal Constellation --- p.53Chapter 4.3 --- Free Distance --- p.55Chapter 4.4 --- Simulation Results --- p.59Chapter 5. --- Conclusion --- p.63Bibliography --- p.6

Towards practical distributed video coding

Multimedia is increasingly becoming a utility rather than mere entertainment. The range of video applications has increased, some of which are becoming indispensable in modem lifestyle. Video surveillance is one area that has attracted significant amount of focus and also benefited from considerable research effort for development. However, it is noted that there is still a notable technological gap between an ideal video surveillance platform and the available solutions, mainly in the form of the encoder and decoder complexity balance and the associated design costs. In this thesis, we tocus on an emerging technology, Distributed Video Coding (DVC), which is ideally suited for the video surveillance scenario, and fits many other potential applications too.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Enabling error-resilient internet broadcasting using motion compensated spatial partitioning and packet FEC for the dirac video codec

Video transmission over the wireless or wired network require protection from channel errors since compressed video bitstreams are very sensitive to transmission errors because of the use of predictive coding and variable length coding. In this paper, a simple, low complexity and patent free error-resilient coding is proposed. It is based upon the idea of using spatial partitioning on the motion compensated residual frame without employing the transform coefficient coding. The proposed scheme is intended for open source Dirac video codec in order to enable the codec to be used for Internet broadcasting. By partitioning the wavelet transform coefficients of the motion compensated residual frame into groups and independently processing each group using arithmetic coding and Forward Error Correction (FEC), robustness to transmission errors over the packet erasure wired network could be achieved. Using the Rate Compatibles Punctured Code (RCPC) and Turbo Code (TC) as the FEC, the proposed technique provides gracefully decreasing perceptual quality over packet loss rates up to 30%. The PSNR performance is much better when compared with the conventional data partitioning only methods. Simulation results show that the use of multiple partitioning of wavelet coefficient in Dirac can achieve up to 8 dB PSNR gain over its existing un-partitioned method