Table Of ContentBemdJahne
Digital
Image Processing
Concepts, Algorithms,
and Scientific Applications
Second Edition
with 168 Figures and 16 Color Plates
Springer-Verlag
Berlin Heidelberg GmbH
Dr. Bernd Jăhne
Scripps Institution of Oceanography
University of California, San Diego
La Jolla, CA 92093-0230, USA
E-mail: bjaehne @ucsd.edu
ISBN 978-3-540-56941-1 ISBN 978-3-662-21817-4 (eBook)
DOI 10.1007/978-3-662-21817-4
Library of Congress Cataloging-in-Publication Data
Jăhne, Bernd
Digital image processing: concepts, algorithms, and scientific applications 1
Bernd Jăhne. --2nd ed.
Includes bibliographical references and index.
1. lmage processing --Digital techniques. I. Title.
TA 1637.134 1993
621.36'7 --dc20
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© Springer-Verlag Berlin Heidelberg 1991 and 1993
Originally published by Springer-Verlag Berlin Heidelberg New York in 1993
Softcover reprint of the hardcover 2nd edition 1993
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Preface to the Second Edition
Digital image processing is a fascinating subject in several aspects. Human beings
perceive most of the information about their environment through their visual sense.
While for a long time images could only be captured by photography, we are now at
the edge of another technological revolution which allows image data to be captured,
manipulated, and evaluated electronically with computers.
With breathtaking pace, computers are becoming more powerful and at the same
time less expensive, so that widespread applications for digital image processing emerge.
In this way, image processing is becoming a tremendous tool to analyze image data in
all areas of natural science. For more and more scientists digital image processing will
be the key to study complex scientific problems they could not have dreamed to tackle
only a few years ago. A door is opening for new interdisciplinary cooperations merging
computer science with the corresponding research areas.
Many students, engineers, and researchers in all natural sciences are faced with the
problem of needing to know more about digital image processing. This book is written
to meet this need. The author-himself educated in physics- describes digital image
processing as a new tool for scientific research. The book starts with the essentials
of image processing and leads - in selected areas - to the state-of-the art. This
approach gives an insight as to how image processing really works. The selection of the
material is guided by the needs of a researcher who wants to apply image processing
techniques in his or her field. In this sense, this book tries to offer an integral view of
image processing from image acquisition to the extraction of the data of interest. Many
concepts and mathematical tools which find widespread application in natural sciences
are also applied in digital image processing. Such analogies are pointed out, since they
provide an easy access to many complex problems in digital image processing for readers
with a general background in natural sciences. The discussion of the general concepts is
supplemented with examples from applications on PC-based image processing systems
and ready-to-use implementations of important algorithms. Part of these examples
are demonstrated with BioScan OPTIMAS, a high-quality image processing software
package for PC-based image processing systems (BioScan, Inc., Edmonds, WA). A
special feature of this book is the extensive treatment of three-dimensional images
and image sequences. The synthetic images used for illustration were designed and
computed with Caligari Broadcast (Octree Software, N.Y.) on a Commodore Amiga by
AEON Verlag, Hanau, FRG.
VI
After studying this book, the reader should be able to apply even quite complex
digital image processing techniques in his or her research area. This book is based on
courses given by the author since 1986 in the Physics Department and the Interdisci
plinary Center for Scientific Computing at the University of Heidelberg. It is assumed
that the reader is familiar with elementary matrix algebra as well as the Fourier trans
form. Wherever possible, mathematical topics are described intuitively making use of
the fact that image processing is an ideal subject to illustrate even complex mathemat
ical relations.
I am deeply indebted to the many individuals who helped me to write this book. I do
this by tracing its history. In the early 1980s, when I worked on the physics of small-scale
air-sea interaction at the Institute of Environmental Physics at Heidelberg University,
it became obvious that these complex phenomena could not be adequately treated with
point measuring probes. Consequently, a number of area extended measuring techniques
were developed. Then I searched for techniques to extract the physically relevant data
from the images and sought for colleagues with experience in digital image processing.
The first contacts were established with the Institute for Applied Physics at Heidelberg
University and the German Cancer Research Center in Heidelberg. I would like to thank
Prof. Dr. J. Bille, Dr. J. Dengler and Dr. M. Schmidt cordially for many eye-opening
conversations and their cooperation.
Then I contacted the faculty for computer science at Karlsruhe University and the
Fraunhofer Institute for Information and Data Processing in Karlsruhe. I learnt a
great deal from the course of Prof. Dr. H.-H. Nagel and Dr. R. Kories on "Algorithmic
Interpretation of Image Sequences" that I attended in the summer term 1986.
In April 1989, a German edition of this book was published by Springer-Verlag.
This is not a straightforward translation, but a completely revised edition with many
augmentations, notably with many more practical examples, listings of important al
gorithms, a new chapter on shape, updated information on the latest image processing
hardware, a new set of color tables, and countless small improvements.
I would like to express my sincere thanks to Dr. Klaus Riemer. He drafted several
chapters of the lecture notes for my courses at Heidelberg University. He also designed
a number of drawings for this book. Many individuals have reviewed various drafts of
the manuscript. I would like to thank Robert I. Birenbaum, Thomas Fendrich, Karl
Heinz Grosser, Jochen Klinke, Dr. Dietmar Wierzimok and many others for valuable
comments and suggestions on different parts of the manuscript. I am mostly grateful
for the help of my friends at AEON Verlag. They sacrificed many night hours for
proofreading, designing computer graphics, and providing general editorial assistance.
Many researchers and companies provided me with material from their research.
The following list shows the many applications of digital image processing:
• Dr. K. S. Baker, Scripps Institution of Oceanography, La Jolla, California; R. C.
Smith, University of California at Santa Barbara, California; 0. B. Brown, Rosenstiel
School of Marine and Atmospheric Science, University of Miami, Florida
• Dr. J.P. Burt, David Sarnoff Research Center, Princeton, New Jersey
• Dr. P. de Loor and Drs. D. van Halsema, Physics and Electronics Laboratory, TNO,
Den Haag
• Dr. J. Dengler, Department of Medical and Biological Computer Science, German
VII
Cancer Research Center, Heidelberg, and Dr. M. Schmidt, Alfred Wegener Institute,
Bremerh aven
• Dr. W. Enkelmann, Fraunhofer-Institute for Information and Data Processing, Karls-
ruhe
• Prof. Dr. G. Granlund, Computer Vision Laboratory, University of Linkoping
• Dr. R. Kories, Fraunhofer-lnstitute for Information and Data Processing, Karlsruhe
• Prof. Dr. E. C. Hildreth, Center for Biological Information Processing, Massachusetts
Institute of Technology, Cambridge, Massachusetts
• Prof. Dr. A. C. Kak, School of Electrical Engineering, Prudue University, West
Lafayette, Indiana
• Dr. K. Riemer and Dr. D. Wierzimok, Institute for Environmental Physics, University
of Heidelberg
• Dr. B. Schmitt and Prof. Dr. D. Komitowski, Department for Histodiagnostics and
Pathomorphological Documentation, German Cancer Research Center, Heidelberg
• J. Steurer, Institute for Communications Technology, Technical University of Munich
• Prof. Dr. J. Wolfrum and Dr. H. Becker, Institute for Physical Chemistry, University
of Heidelberg
• Imaging Technology Inc., Woburn, Massachusetts, and Stemmer PC-Systeme GmbH,
Munich
• Matrox Electronic Systems Limited, Dorval, Quebec, and Rauscher GmbH, Munich
• Techex Computer + Grafik Vertriebs GmbH, Munich
I would also like to thank Prof. Dr. K. 0. Miinnich, director of the Institute for
Environmental Physics. From the beginning, he was open-minded about new ideas to
apply digital image processing techniques in environmental physics. It is due to his
farsightedness and substantial support that the research group "Digital Image Process
ing in Environmental Physics" could develop so fruitfully at his institute. Many of
the examples shown in this book are taken from my research at Heidelberg Univer
sity and the Scripps Institution of Oceanography. I gratefully acknowledge financial
support for this research from the German Science Foundation, the European Commu
nity, the National Science Foundation (OCE8911224), and the Office of Naval Research
(N00014-89-J-3222). Most of this book has been written while I was guest professor
at the Interdisciplinary Research Center for Scientific Computing at Heidelberg Uni
versity. I would like to thank Prof. Dr. Jiiger for his hospitality. I would also like to
express my sincere thanks to the staff of Springer-Verlag for their constant interest in
this book and their professional advice.
For the second edition, the proven and well-received concept of the first edition has
been maintained. Obvious errors have been corrected and some enhancements have been
added. Appendix B (PC-Based Image Processing Systems) has been accommodated
to progress in hardware. Again, I would like to thank all readers in advance for their
comments on further improvements or additions. I am also grateful for hints on errors,
omissions or typing errors which, despite all the care taken, may still have slipped
attention.
La Jolla, California and Heidelberg, spring 1993 Bernd Jiihne
Contents
Contents
1 Introduction 1
1.1 Digital Image Processing- A New Research Tool 1
1.2 Components of an Image Processing System 0 0 0 0 0 2
1.2ol Image Sensors 0 0 0 0 0 0 2
.....
1.2.2 Image Storage 6
1.2.3 Image Processing Speed 8
1.3 Human and Computer Vision 8
1.4 Examples of Scientific Applications 12
1.5 Hierarchy of Image Processing Operations 15
1.6 Image Processing and Computer Graphics 18
2 Image Formation and Digitization 19
2.1 Interaction between Light and Matter 19
201.1 Introduction 19
0 0 ••
201.2 Opaque Surfaces . 0 20
2.1.3 Volumes 0 0 0 . 0 0 21
2.1.4 Light Sources . . 0 22
2.1.5 Reflection .. 0 .. 22
2.2 Image formation 22
0 0. 0 0
202.1 World and Camera Coordinates . 23
202.2 Pinhole Camera Model: Perspective Projection 24
2.2.3 Homogeneous Coordinates . 26
•• 0 0 0 0
2.2.4 Geometric Distortion 0 . . . 28
2.2.5 Depth of Focus 0 0 . 0 . . . 29
2.2.6 3-D Point Spread Function 31
2.2.7 Optical Transfer Function 33
202.8 Cross Sectional Imaging 37
2.2.9 Stereoscopy . o . . . 38
202.10 Tomography 39
......0.. .0..
2.3 Digitization 40
2.3.1 Image matrix 0 0 . 0 40
2.302 Moire-Effect and Aliasing 43
2.3.3 The Sampling Theorem 45
2.3.4 Reconstruction from Samples 50
2o3.5 Standard Sampling 0 . . . 0 . 52
Contents IX
3 Space and Wave Number Domain 53
......
3.1 Introduction . . . . . . . . . . . . . 53
3.2 The Discrete Fourier transform (DFT) 54
3.2.1 The one-dimensional DFT . 54
0 0. 0 0 0
3.2.2 The Two-Dimensional DFT 56
3.2.3 Periodicity . . . . . . . . . 57
3.2.4 Symmetry ......... . 57
3.2.5 Dynamical Range of the DFT . 60
3.2.6 Phase and Amplitude 61
3.3 Discrete Unitary Transforms . . . . . . 63
3.3.1 General Properties ...... . 63
3.3.2 Further Examples for Unitary Transforms .. 65
3.4 Fast Algorithms for Unitary Transforms . 67
3.4.1 Importance of Fast Algorithms .. 67
3.4.2 The 1-D Radix-2 FFT Algorithms 68
3.4.3 Other 1-D FFT Algorithms .... 72
3.4.4 Multidimensional FFT Algorithms 75
4 Pixels 77
4.1 Introduction . 77
4.2 Random Variables 77
4.2.1 Basics ... 77
4.2.2 Quantization . 81
4.2.3 Histograms . . . . 83
4.3 Point Operations . . . . . 86
4.3.1 Homogeneous Point Operations . 86
4.3.2 Look-Up Tables ......... . 86
4.3.3 Inhomogeneous Point Operations . 91
4.4 Dyadic L UT Operations . 94
4.5 Correlations and Spectra . . . . . . . 95
4.5.1 Random Fields ....... . 95
4.5.2 Correlations and Covariances 95
4.5.3 Spectra and Coherence . 97
5 Neighborhoods 100
5.1 Combining Pixels . . . . . . . . . . . . ....... . . 100
5.1.1 Linear Filtering ................ . . 101
5.1.2 Recursive Filters and Linear Systems . . 103
5.1.3 Rank Value Filtering . . 106
5.2 Linear Shift-Invariant Filters . 107
5.2.1 Linearity ...... . . 108
5.2.2 Shift Invariance . . . . . 109
5.2.3 Impulse Response, Transfer Function, and Eigenfunctions . 109
5.2.4 Symmetry . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
5.2.5 General Properties of Linear Shift-Invariant Operators .. . 114
X Contents
6 Mean and Edges 117
6.1 Smoothing . . ...... . . 117
6.1.1 Box Filters ... . . 117
6.1.2 Binomial Filters . . 122
6.1.3 Recursive Smoothing Filters . . 128
6.1.4 Median Filter ........ . . 131
6.2 Edge Detection . . . . . . . . . . . . . 134
6.2.1 First-Order Derivative Operators . 135
6.2.2 Laplace Filter . . 138
6.3 Filter Design ........ . . 140
6.3.1 Filter Nets ..... . . 142
6.3.2 Filter Decomposition . . 146
6.3.3 Smoothing Operators . 147
6.3.4 Bandpass Filters; DoG and LoG Filter . . 153
6.3.5 Derivative Operators . . . . . . ..... . 155
7 Local Orientation 157
7.1 Introduction ...................... . . 157
7.1.1 Vectorial Representation of Local Orientation . 159
7.1.2 Color Coding of Vectorial Image Features . 159
7.2 The Quadrature Filter Set Method .... . 160
7.2.1 Directional Quadrature Filters .. . 160
7.2.2 Vectorial Filter Response Addition . 162
7.3 The Tensor Method ........... . . 164
7.3.1 Analogy: The Inertia Tensor .. . . 166
7.3.2 Eigenvalue Analysis of the 2-D Inertia Tensor . 167
7.3.3 Computing the Inertia Tensor in the Space Domain . 168
7.3.4 Examples and Applications . . . . . . . . . . . . . . . 170
8 Scales 173
8.1 Multigrid Data Structures . 173
8.2 Gauss and Laplace Pyramids . 174
8.2.1 Introduction ..... . 174
8.2.2 Algorithms for Pyramidal Decomposition . . 177
8.2.3 Filters for Pyramid Formation . 180
8.2.4 Interpolation . . . . . . . . . . . . . . . . . . 180
9 Texture 185
9.1 Introduction . . 185
9.2 Rotation and Scale Invariant Texture Features . 188
9.2.1 Local Variance . . . . . . . . . .... . 188
9.3 Rotation and Scale Variant Texture Features . 190
9.3.1 Local Orientation . . . . . . . 190
9.3.2 Local Wave Number . . . . . 190
9.3.3 Pyramidal Texture Analysis . 190
9.4 Fractal Description of Texture . . . . 192
