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One of the amazing properties of human vision is its ability to feel the depth of the scenes being viewed. This is made possible by a process named stereopsis, which is the ability of our brain to fuse together the stereo image pair seen by two eyes. As a stereo image pair is a direct result of the same scene being viewed by a slightly different perspective they open up a new paradigm where spatial redundancy could be exploited for efficient transmission and storage of stereo image data. This thesis introduces three novel algorithms for stereo image compression. The first algorithm improves compression by exploiting the redundancies present in the so-called disparity field of a stereo image pair. The second algorithm uses a pioneering block coding strategy to simultaneously exploit the inter-frame and intra-frame redundancy of a stereo image pair, eliminating the need of coding the disparity field. The basic idea behind the development of the third algorithm is the efficient exploitation of redundancy in smoothly textured areas that are present in both frames, but are relatively displaced from each other due to binocular parallax. Extra compression gains of up to 20% have been achieved by the use of these techniques. The thesis also includes research work related to the improvement of the MPEG-4 video coding standard, which is the first audiovisual representation standard that understands a scene as a composition of audio-visual objects. A linear extrapolation based padding technique that makes use of the trend of pixel value variation often present near object boundaries, in padding the exterior pixels of the reference video object has been proposed. Coding gains of up to 7% have been achieved for coding boundary blocks of video objects. Finally a contour analysis based approach has been proposed for MPEG-4 video object extraction.

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This thesis aims to understand how information coding and the protocol that it supports can affect the characteristics of electronic circuits. More specifically, it investigates an on-line test methodology called IFIS (If it Fails It Stops) and its impact on the design, implementation and subsequent characteristics of circuits intended for application specific lC (ASIC) technology. The first study investigates the influences of information coding and protocol on the characteristics of IFIS systems. The second study investigates methods of circuit design applicable to IFIS cells and identifies the technique possessing the characteristics most suitable for on-line testing. The third study investigates the characteristics of a 'real-life' commercial UART re-engineered using the techniques resulting from the previous two studies. The final study investigates the effects of the halting properties endowed by the protocol on failure diagnosis within IFIS systems. The outcome of this work is an identification and characterisation of the factors that influence behaviour, implementation costs and the ability to test and diagnose IFIS designs.

by Lo Kwok-tung. / Thesis (Ph.D.)--Chinese University of Hong Kong, 1992. / Includes bibliographical references. / ABSTRACT --- p.i / ACKNOWLEDGEMENTS --- p.iii / LIST OF PRINCIPLE SYMBOLS AND ABBREVIATIONS --- p.iv / LIST OF FIGURES --- p.vii / LIST OF TABLES --- p.ix / TABLE OF CONTENTS --- p.x / Chapter CHAPTER 1 --- Introduction / Chapter 1.1 --- Background - The Need for Image Compression --- p.1-1 / Chapter 1.2 --- Image Compression - An Overview --- p.1-2 / Chapter 1.2.1 --- Predictive Coding - DPCM --- p.1-3 / Chapter 1.2.2 --- Sub-band Coding --- p.1-5 / Chapter 1.2.3 --- Transform Coding --- p.1-6 / Chapter 1.2.4 --- Vector Quantization --- p.1-8 / Chapter 1.2.5 --- Block Truncation Coding --- p.1-10 / Chapter 1.3 --- Block Based Image Coding Techniques --- p.1-11 / Chapter 1.4 --- Goal of the Work --- p.1-13 / Chapter 1.5 --- Organization of the Thesis --- p.1-14 / Chapter CHAPTER 2 --- Block-Based Image Coding Techniques / Chapter 2.1 --- Statistical Model of Image --- p.2-1 / Chapter 2.1.1 --- One-Dimensional Model --- p.2-1 / Chapter 2.1.2 --- Two-Dimensional Model --- p.2-2 / Chapter 2.2 --- Image Fidelity Criteria --- p.2-3 / Chapter 2.2.1 --- Objective Fidelity --- p.2-3 / Chapter 2.2.2 --- Subjective Fidelity --- p.2-5 / Chapter 2.3 --- Transform Coding Theroy --- p.2-6 / Chapter 2.3.1 --- Transformation --- p.2-6 / Chapter 2.3.2 --- Quantization --- p.2-10 / Chapter 2.3.3 --- Coding --- p.2-12 / Chapter 2.3.4 --- JPEG International Standard --- p.2-14 / Chapter 2.4 --- Vector Quantization Theory --- p.2-18 / Chapter 2.4.1 --- Codebook Design and the LBG Clustering Algorithm --- p.2-20 / Chapter 2.5 --- Block Truncation Coding Theory --- p.2-22 / Chapter 2.5.1 --- Optimal MSE Block Truncation Coding --- p.2-24 / Chapter CHAPTER 3 --- Development of New Orthogonal Transforms / Chapter 3.1 --- Introduction --- p.3-1 / Chapter 3.2 --- Weighted Cosine Transform --- p.3-4 / Chapter 3.2.1 --- Development of the WCT --- p.3-6 / Chapter 3.2.2 --- Determination of a and β --- p.3-9 / Chapter 3.3 --- Simplified Cosine Transform --- p.3-10 / Chapter 3.3.1 --- Development of the SCT --- p.3-11 / Chapter 3.4 --- Fast Computational Algorithms --- p.3-14 / Chapter 3.4.1 --- Weighted Cosine Transform --- p.3-14 / Chapter 3.4.2 --- Simplified Cosine Transform --- p.3-18 / Chapter 3.4.3 --- Computational Requirement --- p.3-19 / Chapter 3.5 --- Performance Evaluation --- p.3-21 / Chapter 3.5.1 --- Evaluation using Statistical Model --- p.3-21 / Chapter 3.5.2 --- Evaluation using Real Images --- p.3-28 / Chapter 3.6 --- Concluding Remarks --- p.3-31 / Chapter 3.7 --- Note on Publications --- p.3-32 / Chapter CHAPTER 4 --- Pruning in Transform Coding of Images / Chapter 4.1 --- Introduction --- p.4-1 / Chapter 4.2 --- "Direct Fast Algorithms for DCT, WCT and SCT" --- p.4-3 / Chapter 4.2.1 --- Discrete Cosine Transform --- p.4-3 / Chapter 4.2.2 --- Weighted Cosine Transform --- p.4-7 / Chapter 4.2.3 --- Simplified Cosine Transform --- p.4-9 / Chapter 4.3 --- Pruning in Direct Fast Algorithms --- p.4-10 / Chapter 4.3.1 --- Discrete Cosine Transform --- p.4-10 / Chapter 4.3.2 --- Weighted Cosine Transform --- p.4-13 / Chapter 4.3.3 --- Simplified Cosine Transform --- p.4-15 / Chapter 4.4 --- Operations Saved by Using Pruning --- p.4-17 / Chapter 4.4.1 --- Discrete Cosine Transform --- p.4-17 / Chapter 4.4.2 --- Weighted Cosine Transform --- p.4-21 / Chapter 4.4.3 --- Simplified Cosine Transform --- p.4-23 / Chapter 4.4.4 --- Generalization Pruning Algorithm for DCT --- p.4-25 / Chapter 4.5 --- Concluding Remarks --- p.4-26 / Chapter 4.6 --- Note on Publications --- p.4-27 / Chapter CHAPTER 5 --- Efficient Encoding of DC Coefficient in Transform Coding Systems / Chapter 5.1 --- Introduction --- p.5-1 / Chapter 5.2 --- Minimum Edge Difference (MED) Predictor --- p.5-3 / Chapter 5.3 --- Performance Evaluation --- p.5-6 / Chapter 5.4 --- Simulation Results --- p.5-9 / Chapter 5.5 --- Concluding Remarks --- p.5-14 / Chapter 5.6 --- Note on Publications --- p.5-14 / Chapter CHAPTER 6 --- Efficient Encoding Algorithms for Vector Quantization of Images / Chapter 6.1 --- Introduction --- p.6-1 / Chapter 6.2 --- Sub-Codebook Searching Algorithm (SCS) --- p.6-4 / Chapter 6.2.1 --- Formation of the Sub-codebook --- p.6-6 / Chapter 6.2.2 --- Premature Exit Conditions in the Searching Process --- p.6-8 / Chapter 6.2.3 --- Sub-Codebook Searching Algorithm --- p.6-11 / Chapter 6.3 --- Predictive Sub-Codebook Searching Algorithm (PSCS) --- p.6-13 / Chapter 6.4 --- Simulation Results --- p.6-17 / Chapter 6.5 --- Concluding Remarks --- p.5-20 / Chapter 6.6 --- Note on Publications --- p.6-21 / Chapter CHAPTER 7 --- Predictive Classified Address Vector Quantization of Images / Chapter 7.1 --- Introduction --- p.7-1 / Chapter 7.2 --- Optimal Three-Level Block Truncation Coding --- p.7-3 / Chapter 7.3 --- Predictive Classified Address Vector Quantization --- p.7-5 / Chapter 7.3.1 --- Classification of Images using Three-level BTC --- p.7-6 / Chapter 7.3.2 --- Predictive Mean Removal Technique --- p.7-8 / Chapter 7.3.3 --- Simplified Address VQ Technique --- p.7-9 / Chapter 7.3.4 --- Encoding Process of PCAVQ --- p.7-13 / Chapter 7.4 --- Simulation Results --- p.7-14 / Chapter 7.5 --- Concluding Remarks --- p.7-18 / Chapter 7.6 --- Note on Publications --- p.7-18 / Chapter CHAPTER 8 --- Recapitulation and Topics for Future Investigation / Chapter 8.1 --- Recapitulation --- p.8-1 / Chapter 8.2 --- Topics for Future Investigation --- p.8-3 / REFERENCES --- p.R-1 / APPENDICES / Chapter A. --- Statistics of Monochrome Test Images --- p.A-l / Chapter B. --- Statistics of Color Test Images --- p.A-2 / Chapter C. --- Fortran Program Listing for the Pruned Fast DCT Algorithm --- p.A-3 / Chapter D. --- Training Set Images for Building the Codebook of Standard VQ Scheme --- p.A-5 / Chapter E. --- List of Publications --- p.A-7

by Cheng Siu Lung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 81-86). / Abstracts in English and Chinese. / ABBREVIATION --- p.3 / INTRODUCTION --- p.9 / Chapter 1.1 --- Wireless ATM for multimedia application --- p.9 / Chapter 1.2 --- Challenges in Wireless ATM --- p.11 / Chapter 1.3 --- Outline of thesis --- p.14 / PREDICTIVE QUEUING MULTIPLE ACCESS --- p.17 / Chapter 2.1 --- Introduction --- p.17 / Chapter 2.2 --- Protocol for Mobile to Base --- p.20 / Chapter 2.3 --- Scheduling Protocol at the Base Station --- p.23 / Chapter 2.4 --- Rate Compatible Punctured Turbo code --- p.27 / Chapter 2.5 --- FEC and ARQ methodologies --- p.30 / Chapter 2.6 --- Experimental Results --- p.32 / Chapter 2.7 --- Conclusion --- p.34 / FUNDAMENTALS OF THE WIRELESS COMMUNICATION MEDIUM --- p.36 / Chapter 3.1 --- Introduction --- p.36 / Chapter 3.2 --- Error control and channel capacity --- p.38 / Chapter 3.3 --- Capacity of fading channel --- p.39 / ITERATIVE CHANNEL ESTIMATION FOR TURBO CODE FOR FREQUENCY HOPPED MULTIPLE ACCESSING --- p.45 / Chapter 4.1 --- Introduction --- p.45 / Chapter 4.2. --- Turbo code structures --- p.47 / Chapter 4.3 --- System Model --- p.49 / Chapter 4.4 --- Iterative Channel Estimator --- p.53 / Chapter 4.5 --- Turbo decoding with iterative channel estimation --- p.56 / Chapter 4.6 --- Simulation Results --- p.58 / Chapter 4.7 --- Conclusion --- p.63 / DUMMY BITS INSERTED TURBO CODE --- p.64 / Chapter 5.1 --- Introduction --- p.64 / Chapter 5.2 --- Weight Distribution of turbo codes --- p.66 / Chapter 5.3 --- Encoding with dummy bit insertion --- p.69 / Chapter 5.3.1 --- Dummy bit insertion methodology --- p.69 / Chapter 5.3.2 --- Hybrid Periodic Random Interleaver --- p.70 / Chapter 5.3.3 --- Dummy bit removal before transmission --- p.71 / Chapter 5.4 --- Decoding with dummy signal enhancement --- p.73 / Chapter 5.5 --- Weight distribution of dummy bit inserted turbo coding --- p.76 / Chapter 5.6 --- Simulation results --- p.77 / Chapter 5.7 --- Summary --- p.79 / REFERENCES --- p.81

by Jian Zhang. / Thesis (Ph.D.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (p. 134-[144]). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web.

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As a subtopic in this thesis, we also investigate how to deal with uncertainty in the context of the traditional Straightforward Network Coding (SNC) scheme. With the proposed scheme, Soft Network Coding, only simple symbol-level network coding operation at the physical layer of the relay node can achieve even better performance than the traditional SNC scheme, which needs the complicated channel decoding and re-encoding operation. / Network coding is a promising upper layer technique first proposed in the context of wired networks. In this thesis, we investigate the application of network coding at the physical layer of wireless networks to take into account the unique properties of wireless networks. Specifically, we propose a new network coding scheme referred to as Physical layer Network Coding (PNC). PNC effects network-coding operation directly at the physical layer by proper interpretation of EM (Electromagnetic) signal received simultaneously from multiple sources. From the network point of view, this scheme can approach the min-cut throughput for both bi-direction and uni-direction linear relay networks; from the information theory point of view, this scheme can approach the capacity of two-way relay channel in the low and high SNR regions. When channel coding is considered, we could classify PNC into two classes, end-to-end coded PNC and link-by-link coded PNC. For end-to-end coded PNC, we further classify it into subclasses: PNC over infinite field (PNCI) and PNC over finite field (PNCF). For each subclass, we propose and analyze new PNC mapping schemes. For link-by-link coded PNC, we focus on the transformation from the received packet Y3 to the network coded form of unchannel-coded packet S1⊕S2, referred to as the Channel-decoding-Network-Coding process (CNC). Among three CNC designs, a matched CNC, CNC3, is of great interest due to its superior performance. Therefore, we design a new decoding algorithm at the relay node to make CNC3 feasible. Simulation result shows that the matched CNC with our new decoding algorithm outperforms the two straightforward CNC designs significantly in terms of BER without added complexity. Overall, this thesis lays down the fundamentals and foundation of PNC. And through theoretical analysis and implementation constructions, we provide insights on how good performance in wireless networks can be achieved with PNC. / Zhang, Shengli. / Adviser: Soung Chang Lieu. / Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3709. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 178-183). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.