Efficient Algorithms for MPEG Video Compression / Edition 1

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Video compression is the enabling technology behind many cutting-edge business and Internet applications, including video-conferencing, video-on-demand, and digital cable TV. Coauthored by internationally recognized authorities on the subject, this book takes a close look at the essential tools of video compression, exploring some of the most promising algorithms for converting raw data to a compressed form.
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Editorial Reviews

From the Publisher
"...for some every page will be worth the cost..." (Visual Systems Journals, July/August 2002)

"...presents a new framework for allocating bits to the compression of pictures in an MPEG video sequence." (SciTech Book News, Vol. 26, No. 2, June 2002)

From The Critics
In continuous media, such as MPEG movie files, temporal dimensions become extremely important. For example, although each frame in a movie may have different rates of compressability over time, the ability to maintain a constant image quality is damaged by compressing every frame as much as possible. In this monograph, Hoang (an algorithm development manager with iCompression) and Vitter (computer science, Duke U.) focus on the rate control of compressed video. Specifically, they present a new framework for allocating bits to the compression of pictures in an MPEG video sequence. They cast rate control as a resource allocation problem with continuous variables, nonlinear constraints, and a novel lexicographic optimality criterion that is motivated for uniform video quality. Analyzing the above framework, they construct polynomial-time algorithms for optimal bit rate control. They describe the implementation and results of the algorithms and discuss further modifications. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

Meet the Author

DZUNG TIEN HOANG is a video algorithm development manager at iCompression, a subsidiary of Globespan. With a PhD from Brown University, he has also held positions at Digital Video Systems and Sony Electronics.
JEFFREY SCOTT VITTER is the Gilbert, Louis, and Edward Lehrman Professor of Computer Science at Duke University. With a PhD from Stanford University, he is a National Science Foundation Presidential Young Investigator, a Fulbright Scholar, a Guggenheim Fellow, an IBM Faculty Development Awardee, and a Fellow of both the ACM and IEEE. He also holds several patents in the fields of external sorting, prediction, and approximate data structures.
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Table of Contents





Lexicographic Bit Allocation Framework.

Optimal Bit Allocation under CBR Constraints.

Optimal Bit Allocation under VBR Constraints.

Implementation of Lexicographic Bit Allocation.

A More Efficient Dynamic Programming Algorithm.

Real-Time VBR Rate Control.

Extensions of the Lexicographic Framework.


About the Authors.


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