Optimization techniques for adaptive. quantization of image and video under delay. constraints. Antonio Ortega. Submitted in partial fulællment of the

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Optimization techniques for adaptive quantization of image and video under delay constraints Antonio Ortega Submitted in partial fulællment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences Columbia University 1994

cæ 1994 Antonio Ortega All Rights Reserved

ABSTRACT Optimization techniques for adaptive quantization of image and video under delay constraints Antonio Ortega Traditionally, rate-distortion èr-dè theory has been concerned with providing bounds on the optimal performance for various classes of coding algorithms and sources. In this thesis we depart from that approach intwoways. First, our objective are operational R-D results, i.e. we study algorithms that can ænd the optimal solution for a given coder conæguration and known inputs, without relying on modeling either the encoder or the source. Second, we seek to explore explicitly other parameters that determine the achievable R-D performance, namely, the encoding delay and complexity, and the memory at the encoder. We compute the optimal solution even if it requires too much complexity, memory or delay to be considered in a practical setting. Optimal schemes serve as a benchmark and can also be the basis for heuristic methods which provide slightly suboptimal but more eæcient performance. More speciæcally we study the following topics: èiè Optimal buæer constrained quantization. We ænd optimal solutions for the buæer control problem in a deterministic framework by assuming a long encoding delay. Our solution, based on dynamic programming, also leads us to short delay, lower complexity heuristics. èiiè Rate control and policing constraints for video transmission over ATM networks. We study the problem of optimizing the source quality as in èiè, while taking into account network considerations. èiiiè Optimization of dependent quantization environments. Optimal bit alloca-

tion results are presented for dependent quantization schemes èe.g. DPCM, predictive motion compensated video coding, MPEGè. èivè Rate-delay trade-oæs in a multiresolution image database system. We study how the bit allocation in a multiresolution coding system can be chosen so as to minimize the end-to-end query delay inbrowsing through a set of images. èvè Adaptive quantization without side information. We propose a backward adaptive quantization algorithm where the input distribution is ëlearned" from past quantized samples. This allows adaptation to sources with unknown or time-varying input distribution.

List of Abbreviations ATM B CBR DCT DP DPCM GAP HDTV HVS I JPEG KLT LB MPEG MR MSE P PSNR R-D SBC SMG, Asynchronous Transfer Mode, Bidirectionally interpolated mode èin MPEGè, Constant Bit Rate, Discrete Cosine Transform, Dynamic Programming, Diæerential Pulse Coded Modulation, Generalized Assignment Problem, High Deænition Television, Human Visual System, Intraframe mode èin MPEGè, Joint Photographic Experts Group, Karhunen Loçeve Transform, Leaky Bucket, Moving Pictures Experts Group, Multiresolution, Mean Squared Error, Prediction mode èin MPEGè, Peak Signal to Noise Ratio, RateíDistortion, Subband Coding, Statistical Multiplexing Gain xv

SNR SR TCM TCQ VBR VA VLSI VQ, Signal to Noise Ratio, Single resolution, Trellis Coded Modulation, Trellis Coded Quantization, Variable Bit Rate, Viterbi Algorithm, Very Large Scale Integration, Vector Quantization xvi

Acknowledgements Iwould like to ærst acknowledge the continuous help and support from my thesis advisor and friend Professor Martin Vetterli. With his insights and suggestions Martin made this research both interesting and fun, never hesitating to share his many ideas and his endless supply of energy and enthusiasm. Iwould also like to thank all my friends at the Image Lab and at CTR, especially Cormac Herley, Jonathan Hong, Thao Nguyen, and Kannan Ramchandran, for making it a pleasant work environment. In particular, I thank Alexandros Eleftheriadis, who has unselæshly contributed so much of his own time to keeping the Image Lab running. I thank my family for their total support during my tenure at Columbia. I also thank my friends in New York for dragging me south of 110th St., or even across the river, every once in a while. I thank my friends in Madrid and elsewhere for their numerous stays at what was quickly nicknamed ëpensiçon Ortega". I had the pleasure to work with a number of people during my years at Columbia. Iwould like to thank Drs. Mark Garrett of Bellcore and Zhensheng Zhang of CTR foravery enjoyable collaboration. A special thanks goes to Kannan Ramchandran. I beneæted greatly from the many hours spent working with Kannan on every stage of several projects, as well as from many discussions throughout my stay at Columbia. Our collaboration not only led to several joint publications but was also most enjoyable. Some of the research presented here was initiated at the Universidad Politçecnica de Madrid in Spain. I would like to thank Professors Narciso Garcça and Guillermo Cisneros for advising my initial work at U.P.M. I also thank Josçe Ignacio Ronda for a fruitful collaboration that was continued after my departure, demonstrating the xvii

usefulness of the Internet. Professors Anastassiou, Chang, Kender and Silvotti I thank for serving on my defense committee. Last, but certainly not least, I gratefully acknowledge the generous support of the Fulbright Commission and the Ministry of Education and Science of Spain, which made possible this research by granting me a scholarship for the duration of my stay at Columbia. xviii

A mis padres xix