VLSI implementations for image communications

405 Pages·1993·28.496 MB·English

by  P Pirsch

ADVANCES IN IMAGE COMMUNICATION
Series Editor: J. Biemond, Delft University of Technology, The Netherlands
Volume 1 Three-Dimensional Object Recognition Systems (edited by A.K. Jain and
P.J. Flynn)
Volume 2 VLSI Implementations for Image Communications (edited by P. Pirsch)
ADVANCES IN IMAGE COMMUNICATION 2
VLSI Implementations
for Image Communications
Edited by
P. Pirsch
Institut fur Theoretische Nachrichtentechnik
und Informationsverarbeitung
University of Hannover
Hannover
Germany
ELSEVIER
Amsterdam - London - New York - Tokyo 1993
ELSEVIER SCIENCE PUBLISHERS B.V.
Sara Burgerhartstraat 25
P.O. Box 211,1000 AE Amsterdam, The Netherlands
Library of Congress Cataloging-1n-PublicatIon Data
VLSI implementations for image communications / edited by P. Pirsch.
p. cm. — (Advances in image communication ; 2)
Includes bibliographical references and index.
ISBN 0-444-88790-3 (a Ik. paper)
1. Image processing. 2. Integrated circuits—Very large scale
integration. I. Pirsch, P. (Peter) II. Series.
TA1637.V67 1993
006.6—dc20 93-30175
CIP
ISBN: 0 444 88790 3
© 1993 Elsevier Science Publishers B.V. All rights reserved.
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V
INTRODUCTION TO THE SERIES
"Advances In Image Communication"
Image Communication is a rapidly evolving multidisciplinary field focussing on the evaluation
and development of efficient means for acquisition, storage, transmission, representation and
understanding of visual information. Until a few years ago, image communication research
was still confined to universities and research laboratories of telecommunication or
broadcasting companies. Nowadays, however, this field is also witnessing the strong interest
of a large number of industrial companies due to the advent of narrowband and broadband
ISDN, digital satellite channels, digital over-the-air transmission and digital storage media.
Moreover, personal computers and workstations have become important platforms for
multimedia interactive applications that advantageously use a close integration of digital video
compression techniques (MPEG), Very Large Scale Integration (VLSI) technology, highly
sophisticated network facilities and digital storage media. At the same time, the scope of
research of the academic environment on Image Communication has further increased to
include model- and knowledge-based image understanding techniques, artificial intelligence,
motion analysis, and advanced image and video processing techniques and lead to a diverse
area of applications such as: access to image data bases, interactive visual communication, TV
and HDTV broadcasting and recording, 3D-TV, graphic arts and communication, image
manipulation, etc. The variety of topics on Image communication is so large that no-one can
be a specialist in all the topics, and the whole area is beyond the scope of a single volume,
while the requirement of up-to-date information is ever increasing.
In 1988, the European Association for Signal Processing EURASIP together with Joel
Claypool & Ir. Hans van der Nat, at that time Publishing Editors at Elsevier Science
Publishers, conceived several projects to meet this need for information. First of all a new
EURASIP journal, "Signal Processing: Image Communication", was launched in June 1989
under the inspired Editorship of Dr. Leonardo Chiariglione. So far, the journal has been a
major success not in the least due to the many special issues devoted to timely aspects in
Image Communication, such as low/medium/high bit rate video coding, all digital HDTV, 3D-
TV, etc. It was further decided to publish a book series in the field, an idea enthusiastically
supported by Dr. Chiariglione. Mr. van der Nat approached the undersigned to edit this series.
VI
It was agreed that the book series should be aimed to serve as a comprehensive reference
work for those already active in the area of Image Communication. Each volume author or
editor was asked to write or compile a state-of-the-art book in his area of expertise, and
containing information until now scattered in many journals and proceedings. The book series
therefore should help Image Communication specialists to get a better understanding of the
important issues in neighbouring areas by reading particular volumes. At the same time, it
should give newcomers to the field a foothold for doing research in the Image Communication
area. In order to produce a quality book series, it was necessary to ask authorities well known
in their respective fields to serve as volume editors, who would in turn attract outstanding
contributors. It was a great pleasure to me that ultimately we were able to attract such an
excellent team of editors and authors.
The Series Editor wishes to thank all of the volume editors and authors for the time and effort
they put into the book series. He is also grateful to Ir. Hans van der Nat and Drs. Mark Eligh
of Elsevier Science Publishers for their continuing effort to bring the book series from the
initial planning stage to final publication.
Jan Biemond
Delft University of Technology
Delft, The Netherlands
1993
Future titles planned for the series "Advances in Image Communication":
- Wavelets in Image Communication M. Barlaud, Editor
- Subband Coding of Images T.A. Ramstad, S.O. Aase
- Motion Estimation for Coding Applications G. Tziritas, C. Labit
- HDTV Signal Processing R. Schafer, G. Schamel
- Magnetic Recording M. Breeuwer, P.H.N. de With
- Image Deblurring; Motion Compensated Filtering A.K. Katsaggelos, N. Galatsanos
- Colour Image Processing P.E. Trahanias, A.N. Ventsanopoulos
- Transmission of the Digital Television and J.-P. Leduc
High-Definition Television on ATM Networks
VI
It was agreed that the book series should be aimed to serve as a comprehensive reference
work for those already active in the area of Image Communication. Each volume author or
editor was asked to write or compile a state-of-the-art book in his area of expertise, and
containing information until now scattered in many journals and proceedings. The book series
therefore should help Image Communication specialists to get a better understanding of the
important issues in neighbouring areas by reading particular volumes. At the same time, it
should give newcomers to the field a foothold for doing research in the Image Communication
area. In order to produce a quality book series, it was necessary to ask authorities well known
in their respective fields to serve as volume editors, who would in turn attract outstanding
contributors. It was a great pleasure to me that ultimately we were able to attract such an
excellent team of editors and authors.
The Series Editor wishes to thank all of the volume editors and authors for the time and effort
they put into the book series. He is also grateful to Ir. Hans van der Nat and Drs. Mark Eligh
of Elsevier Science Publishers for their continuing effort to bring the book series from the
initial planning stage to final publication.
Jan Biemond
Delft University of Technology
Delft, The Netherlands
1993
Future titles planned for the series "Advances in Image Communication":
- Wavelets in Image Communication M. Barlaud, Editor
- Subband Coding of Images T.A. Ramstad, S.O. Aase
- Motion Estimation for Coding Applications G. Tziritas, C. Labit
- HDTV Signal Processing R. Schafer, G. Schamel
- Magnetic Recording M. Breeuwer, P.H.N. de With
- Image Deblurring; Motion Compensated Filtering A.K. Katsaggelos, N. Galatsanos
- Colour Image Processing P.E. Trahanias, A.N. Ventsanopoulos
- Transmission of the Digital Television and J.-P. Leduc
High-Definition Television on ATM Networks
vii
Preface
Over the past few years there has been an explosive progress on image processing and image
communications technologies. Because of this progress image and video communications are
becoming reality. New video services and multimedia applications are under discussion or will
be introduced in the near future. Essential for all these applications are image and video compres-
sion techniques. Video compression is needed for transmission cost reduction for video phones
and video conferencing systems, to reduce the bandwidth required for broadcasting TV by
terresterial and satellite distribution, and to provide compact interactive video for training and
entertainment from a CD.
International standardization committees have been working on the specification of several
compression algorithms. The Joint Photograhic Experts Group (JPEG) of the International Stan-
dards Organization (ISO) have specified an algorithm for compression of still images. The
CCITT (The International Telegraph and Telephone Consultative Committee) proposed the
H.261 standard for video telephony. The Motion Picture Experts Group (MPEG) of ISO proposed
a standard for storage of video sequences with reduced resolution. New standards for transmis-
sion and storage of video sequences with TV or even HDTV resolution are now under develop-
ment.
Important for enabling the discussed applications of video signal processing is VLSI (very
large scale integration). The real-time processing of video signals requires a tremendous com-
putational capability that can only be achieved cost effectively by using VLSI's. The usefulness
of a video algorithm strongly depends on the feasibility and effectiveness of its VLSI imple-
mentation. The subject of efficient VLSI implementation for video signal processing spans a
broad range of disciplines involving algorithms, architectures, circuits, and systems. Recent
progress in VLSI architectures and implementations has resulted in order of magnitude reduction
in cost and size of video signal processing equipment and has made video applications practical.
The purpose of this book is to report on recent advances in VLSI architectures and implementa-
tion for video signal processing applications with emphasis on video coding for bit rate reduction.
VLSI implementation of video signal processing applications is cross-disciplinary, involving
interactions between algorithms, VLSI architectures, circuit techniques, semiconductor technol-
ogies and CAD for microelectronics. In line with the knowledge of interactions, this book puts
together several selected contributions addressing themes on:
Algorithms for Image Communications
Transfer of Algorithms to Architectures
VLSI Implementations and Image Processing Systems with Programmable Multiprocessors
VLSI Architectures and Implementations of Dedicated Image Processing Functions
Chapter 1 presents a brief overview of basic video coding techniques which are common to
most video compression systems. Besides basic coding techniques three video compression
systems are illustrated. The following two chapters deal with the transfer of algorithms to VLSI
viii
architectures. The chapter 2 discusses the need of special processor architectures with extensive
parallel processing and pipelining as a result of the high performance requirements of video
coding schemes. Methods of mapping algorithms onto processor arrays and the application to the
example of a hybrid codec are given in chapter 3.
The next two chapters describe programmable multiprocessor systems for video signal pro-
cessing. Chapter 4 presents two basic approaches for implementation of video codecs, the func-
tional approach and the distributed approach. Also the application to a single board implementa-
tion of a video telephone is included. Parallel processing approaches by using overlap-save and
overlap-add techniques for image segment processing are illustrated in chapter 5. Multiprocessor
arrangements have been developed which perform real-time evaluation of hybrid coding
schemes up to HDTV rate.
In the last part several chapters are directed to architectures dedicated to special image proces-
sing functions. Architectural strategies and circuits concepts of high throughput digital filters are
introduced in chapter 6. Besides well established implementation approaches new parallelization
concepts are explained. Then architectures for orthogonal transforms follow in chapter 7. Em-
phasis is herby on the discrete cosine transform (DCT). Alternative architectures are compared
concerning hardware expense, throughput rate, accuracy of number representation etc. Architec-
tures for motion estimation, in particular for displacement estimation algorithms, are presented
in chapter 8. After an overview of algorithms the chapter focuses on implementations for block
matching algorithms and pel recursive algorithms. One-dimensional and two-dimensional array
architectures for real-time video applications are investigated. Several architectural strategies
for the implementation of vector quantization are reviewed in chapter 9. Full search and tree
search algorithms are included. The processor complexity is analyzed as a function of system
parameters. Architectures for the realization of differential pulse-code modulation (DPCM) are
presented in chapter 10. An important topic is here the relaxation of time constraints for the
recursive loop by modifications of the original DPCM structure or parallel DPCM processors.
Implementation examples are included. High throughput architectures for decoding of variable-
length codes are discussed in chapter 11. An entropy codec for HDTV applications is used as an
example to illustrate the special design issues. Several approaches to achieve concurrency in
decoding of variable-length codes are presented in chapter 12. Techniques to break the sequential
computation bottleneck of these decoders by pipelining and parallel processing are visualized.
This book is an outgrowth of the IEEE workshops "VLSI Architectures and Implementations
for Digital Video and Visual Communications" and "Signal Processing and VLSI Implementa-
tion for High-Definition Video" held during the ISCAS conferences in New Orleans, May 1990
and Singapore, June 1991.
I wish to express my sincere appreciation to Prof. Jan Biemond and the ELSEVIER publisher
for inviting me to edit this volume as part of the series Advances in Image Communication. A
special thank deserve all authors who contributed to the book.
Peter Pirsch
VLSI Implementations for Image Communications
P. Pirsch (Editor)
© 1993 Elsevier Science Publishers B.V. All rights reserved.
1. Video Coding Techniques: An Overview
Kou-Hu Tzou
Image Processing Department, COMSAT Laboratories,
Clarksburg, Maryland 20871, US A
Abstract
In this chapter, we present a brief overview of basic video coding techniques, which are
common to most video compression systems. The coding techniques reviewed include
quantization, predictive coding, entropy coding, orthogonal transform, motion
estimation/compensation, and subband processing. After the brief overview of these
techniques, we present three sample video compression systems to illustrate how these
techniques can be tailored for specific applications.
1. INTRODUCTION
Digital video has advantages of flexible processing, immunity to small transmission
noises, and convenience for switching and networking. Nevertheless, there are also a few
disadvantages of digital video such as large storage requirement and very high data rate for
transmission. For example, in a conventional NTSC television system, the signal is
transmitted in an analog format requiring a baseband bandwidth about 6 MHz. The typical
recording time on a video disk is about two hours so that a full movie can be recorded on a
disk. However, when the video signal is represented in a digital format, the bandwidth is
expanded substantially. For example, if the TV signal is sampled at 14.32 MHz (4 times the
NTSC subcarrier frequency) with an 8-bit resolution, this results in a bit rate of 114 Mbps. At
a 4-bits/Hz modulation efficiency, this digital bit stream needs more than 28 MHz bandwidth,
which represent a bandwidth expansion more than 4 times. On the other hand, a typical digital
optical disk has about 2 GBytes storage space, which can only hold less than 2.5 minutes of
digital video. Compared with the analog approach, the storage capacity is far less.
During the last decade, the VLSI technology has advanced rapidly, which can pack more
logic gates on a single chip and can operate at a much higher speed. The high speed processing
capability of VLSI has helped digital video become more practical. In order to alleviate the
bandwidth expansion problem while taking the advantages of digital video, many video coding
techniques have been developed during the last two decades. Along with the development of
high-speed dedicated as well as general purpose video processors, video coding algorithms
also become much more sophisticated. Today, VCR-quality video can be achieved at 1.5
Mbps [1] and personal videophone can be achieved at 64 kbps [2]. However, back in the early
80's, even the advanced teleconference codec required 1.5-6.3 Mbps to achieve satisfactory
quality [84,85]. Besides the hardware and software development, some international video
coding standard activities have also helped to expedite the realization of digital video services.
Among various coding systems, there are a few common techniques and basic structures.
An exhaustive treatment of various coding techniques is, by no means, the intent of this
chapter. Rather its purpose is to provide hardware designers with the basic knowledge of these
commonly used video coding techniques. This knowledge may help them understand the
technical challenges and requirements in various video coding systems. For those who like
exploit the details, there are a few books [3-6] fully dedicated to this subject and can be used as
references. In this chapter, we will briefly overview various coding techniques including
2
quantization, predictive coding, entropy coding, orthogonal transform, motion estimation, and
subband analysis/synthesis. In a real system, depending on the specified quality, available bit
rate, affordable complexity, and desired features, proper techniques can be combined to meet
the requirement. Three coding systems are illustrated in Section 8 as examples.
2. QUANTIZATION
To represent an analog waveform digitally, first the signal has to be sampled at a minimum
rate twice the cutoff bandwidth of the signal. This minimum rate is called Nyquist sampling
rate, which allows a perfect reconstruction of the analog waveform from the sampled data. The
sampled data, however, may have continuous amplitude by nature. In order to obtain an
efficient digital representation, the continuous amplitude has to be properly mapped to a limited
number of discrete values. This mapping is called amplitude quantization. The simplest form
of sampling and quantization process is the well-known Analog-to-Digital (A/D) conversion.
In the digital environment, the data is already in a digital form. However, the data may be in a
very fine resolution. In order to reduce the amount of data, the high precision data are often
quantized to a smaller number of allowed representative levels.
Quantization often introduces distortion to the underlying signal. In nature, quantization is
a lossy process where the reconstructed signal may not be exactly the same as the original .In
many coding applications, this is the only lossy process of the system. Therefore, the quality
of quantization often determines the quality of the processed signal. Quantizer design has been
an issue heavily studied over the last several decades. There are several popularly used
performance criteria for quantizer design such as the minimum mean square error and the
minimum absolute error. The task involved in the quantizer design is to choose the optimal
reconstruction levels and quantization thresholds which minimize the distortion. The
performance of the resulting quantizer is measured by the distortion at a prescribed number of
quantization levels. The number of quantization levels can be directly translated to a bit rate if
no statistical coding is applied subsequently. The performance bound of a quantizer is
governed by the well-known rate-distortion theory [7]. According to the theory, the minimum
coding rate for a source with a prescribed distortion has to be greater than the rate-distortion
bound.
2.1 Uniform Quantization
The uniform quantizer is characterized by the same step size over the whole data region.
However, for unbounded signals, the step sizes are the same except for the two corresponding
to the end intervals. A quantizer can be fully specified by its corresponding characteristic
function. For a signal with a symmetric distribution centered at zero, an M-level uniform
quantizer is shown in Fig. 2.1(a) for even M and 2.1(b) for odd M. The type of quantizer is
called midtreador midrise depending on whether zero is one of the quantization output or not.
The midtread quantizer maps an input zero to an output zero, which is a desired feature in many
applications. If the signal has a peaked probability density function at zero, then zero outputs
are likely to occur in cluster, which are suitable for run-length coding (to be discussed in
Section 4). In order to compress the quantizer outputs using run-length coding, the midtread-
type quantizer is preferred.
The mean-squared quantization error (MSQE) of an M-level quantizer is
M
* =IJv' (x-x )2p(x)dx, (2.1)
i
i=l yi~'
where v*-i and ?i are the two thresholds corresponding to the reconstructed level, */. For an
uniformly distributed random variable x with probability density function p(x) = \/a,