Hybrid FDMA/CDMA wireless ATM and subband image coding.

by Yeung Chi Kit.Thesis (M.Phil.)--Chinese University of Hong Kong, 1996.Includes bibliographical references (leaves 89-91).Chapter I --- Hybrid FDMA/CDMA Wireless ATM --- p.1Chapter 1 --- Introduction --- p.2Chapter 1.1 --- Motivation --- p.2Chapter 1.2 --- Thesis Organization (PART I) --- p.5Chapter 2 --- Fundamentals --- p.6Chapter 2.1 --- Spread Spectrum --- p.6Chapter 2.1.1 --- Direct Sequence (DS) CDMA --- p.6Chapter 2.1.2 --- Frequency Hopping (FH) CDMA --- p.8Chapter 2.1.3 --- Time Hopping (TH) CDMA --- p.8Chapter 2.1.4 --- MC-CDMA (Multicarrier-CDMA) --- p.9Chapter 2.2 --- Asynchronous Transfer Mode (ATM) --- p.10Chapter 3 --- System Model --- p.12Chapter 4 --- System Capacity --- p.16Chapter 4.0.1 --- One Homogeneous User Population --- p.16Chapter 4.0.2 --- Two Homogeneous User Populations --- p.18Chapter 5 --- Conclusion --- p.24Chapter II --- Subband Image Coding --- p.28Chapter 6 --- Introduction --- p.29Chapter 6.1 --- Motivation --- p.29Chapter 6.2 --- Thesis Organization (PART II) --- p.31Chapter 7 --- Fundamentals --- p.33Chapter 7.1 --- Image Fidelity Criteria --- p.33Chapter 7.1.1 --- Numerical (Quantitative) Measures --- p.34Chapter 7.1.2 --- Perceptual (Subjective) Measure --- p.34Chapter 8 --- Wavelet Transform --- p.36Chapter 8.1 --- Wavelet Theory --- p.37Chapter 8.2 --- Multiresolution Analysis --- p.39Chapter 8.3 --- Quality Criteria for Wavelets --- p.42Chapter 8.4 --- Criteria for filters...................´ب --- p.43Chapter 8.5 --- Orthogonal Discrete Wavelet Transform --- p.45Chapter 8.6 --- Biorthogonal Discrete Wavelet Transform --- p.47Chapter 8.7 --- Wavelet Packets Transform --- p.48Chapter 8.8 --- Appendix --- p.50Chapter 8.8.1 --- QMF & CQF --- p.50Chapter 8.8.2 --- Examples of Orthogonal Filters --- p.53Chapter 8.8.3 --- Examples of Biorthogonal Filters --- p.53Chapter 9 --- Transform Coding and Compression --- p.55Chapter 9.1 --- Transformation Techniques --- p.56Chapter 9.2 --- Quantization --- p.57Chapter 9.2.1 --- Scalar Quantization --- p.57Chapter 9.2.2 --- Llyod-Max Quantization --- p.59Chapter 9.2.3 --- Vector Quantization --- p.59Chapter 9.2.4 --- Successive Approximation Entropy-Coded Quantization --- p.60Chapter 9.3 --- Entropy Coding --- p.61Chapter 9.3.1 --- Huffman Coding --- p.61Chapter 9.3.2 --- Arithmetic Coding --- p.62Chapter 9.3.3 --- Dictionary Based Coding --- p.64Chapter 9.3.4 --- Run Length Coding --- p.65Chapter 9.3.5 --- Example --- p.65Chapter 10 --- Embedded Zerotree Algorithm --- p.69Chapter 10.1 --- Significance Map Encoding --- p.70Chapter 10.2 --- Successive Approximation Entropy Coded Quantization --- p.72Chapter 10.3 --- Example --- p.74Chapter 10.4 --- Comments on EZW --- p.77Chapter 11 --- Residue Coding Using Embedded Zerotree Algorithm --- p.79Chapter 11.1 --- Residue Coding --- p.80Chapter 11.2 --- Results --- p.81Chapter 12 --- Conclusion --- p.8

An efficient rate control algorithm for a wavelet video codec

Rate control plays an essential role in video coding and transmission to provide the best video quality at the receiver's end given the constraint of certain network conditions. In this paper, a rate control algorithm using the Quality Factor (QF) optimization method is proposed for the wavelet-based video codec and implemented on an open source Dirac video encoder. A mathematical model which we call Rate-QF (R - QF) model is derived to generate the optimum QF for the current coding frame according to the target bitrate. The proposed algorithm is a complete one pass process and does not require complex mathematical calculation. The process of calculating the QF is quite simple and further calculation is not required for each coded frame. The experimental results show that the proposed algorithm can control the bitrate precisely (within 1% of target bitrate in average). Moreover, the variation of bitrate over each Group of Pictures (GOPs) is lower than that of H.264. This is an advantage in preventing the buffer overflow and underflow for real-time multimedia data streaming

Performance Evaluation of Hybrid Coding of Images Using Wavelet Transform and Predictive Coding

Image compression techniques are necessary for the storage of huge amounts of digital images using reasonable amounts of space, and for their transmission with limited bandwidth. Several techniques such as predictive coding, transform coding, subband coding, wavelet coding, and vector quantization have been used in image coding. While each technique has some advantages, most practical systems use hybrid techniques which incorporate more than one scheme. They combine the advantages of the individual schemes and enhance the coding effectiveness. This paper proposes and evaluates a hybrid coding scheme for images using wavelet transforms and predictive coding. The performance evaluation is done using a variety of different parameters such as kinds of wavelets, decomposition levels, types of quantizers, predictor coefficients, and quantization levels. The results of evaluation are presented

Wavelet encoding and variable resolution progressive transmission

Progressive transmission is a method of transmitting and displaying imagery in stages of successively improving quality. The subsampled lowpass image representations generated by a wavelet transformation suit this purpose well, but for best results the order of presentation is critical. Candidate data for transmission are best selected using dynamic prioritization criteria generated from image contents and viewer guidance. We show that wavelets are not only suitable but superior when used to encode data for progressive transmission at non-uniform resolutions. This application does not preclude additional compression using quantization of highpass coefficients, which to the contrary results in superior image approximations at low data rates

Embed[d]ed Zerotree Codec

This thesis discusses the findings of the final year project involving the VHDL (V= Very High Speed Integrated Circuit, Hardware Description Language) design and simulation of an EZT (Embedded Zero Tree) codec. The basis of image compression and the various image compression techniques that are available today have been explored. This provided a clear understanding of image compression as a whole. An in depth understanding of wavelet transform theory was vital to the understanding of the edge that this transform provides over other transforms for image compression. Both the mathematics of it and how it is implemented using sets of high pass and low pass filters have been studied and presented. At the heart of the EZT codec is the EZW (Embedded Zerotree Wavelet) algorithm, as this is the algorithm that has been implemented in the codec. This required a thorough study and understanding of the algorithm and the various terms used in it. A generic single processor codec capable of handling any size of zerotree coefficients of images was designed. Once the coding and decoding strategy of this single processor had been figured out, it was easily extended to a codec with three parallel processors. This parallel architecture uses the same coding and decoding methods as in the single processor except that each processor in the parallel processing now handles only a third of the coefficients, thus promising a much speedier codec as compared to the first one. Both designs were then translated into VHDL behavioral level codes. The codes were then simulated and the results were verified. Once the simulations were completed the next aim for the project, namely synthesizing the design, was embarked upon. Of the two logical parts of the encoder, only the significance map generator has been synthesized

Suboptimality of the Karhunen-Loève transform for transform coding

We examine the performance of the Karhunen-Loeve transform (KLT) for transform coding applications. The KLT has long been viewed as the best available block transform for a system that orthogonally transforms a vector source, scalar quantizes the components of the transformed vector using optimal bit allocation, and then inverse transforms the vector. This paper treats fixed-rate and variable-rate transform codes of non-Gaussian sources. The fixed-rate approach uses an optimal fixed-rate scalar quantizer to describe the transform coefficients; the variable-rate approach uses a uniform scalar quantizer followed by an optimal entropy code, and each quantized component is encoded separately. Earlier work shows that for the variable-rate case there exist sources on which the KLT is not unique and the optimal quantization and coding stage matched to a "worst" KLT yields performance as much as 1.5 dB worse than the optimal quantization and coding stage matched to a "best" KLT. In this paper, we strengthen that result to show that in both the fixed-rate and the variable-rate coding frameworks there exist sources for which the performance penalty for using a "worst" KLT can be made arbitrarily large. Further, we demonstrate in both frameworks that there exist sources for which even a best KLT gives suboptimal performance. Finally, we show that even for vector sources where the KLT yields independent coefficients, the KLT can be suboptimal for fixed-rate coding