Digital image processing: PIKS Scientific inside

807 Pages·2007·13.426 MB·English

by  William K. Pratt

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DIGITAL IMAGE
PROCESSING
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DIGITAL IMAGE
PROCESSING
PIKS Scientific Inside
Fourth Edition
WILLIAM K. PRATT
PixelSoft, Inc.
Los Altos, California
WILEY-INTERSCIENCE
A John Wiley & Sons, Inc., Publication
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About the cover:
The first image on the left is the peppers_gamma original color image.
The second image is the edge map of the luma component of the first image produced by a derivative of
Gaussian edge detector.
The third image is the cat original color image.
The fourth image is the spatial gain image of the luma component of the cat image produced by a Wallis
statistical differencing operator.
The fifth image is the result of Wallis processing on the luma component and amplitude stretching of the
chrominance components of the cat image.
The lower right image is a sharpened version of the original image obtained by subtracting an amplitude
weighted version of the blurred image from a weighted version of the original image. The processing
technique is called unsharp masking.
Copyright © 2007 by John Wiley & Sons, Inc., All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.
Published simutaneously in Canada.
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Library of Congress Cataloging-in-Publication Data:
Pratt, William K.
Digital image processing : PIKS Scientific inside / William K. Pratt.—, 4th ed.
p. cm.
“A Wiley-Interscience publication.”
Includes bibliographical references and index.
ISBN: 978-0-471-76777-0
1. Image processing—Digital techniques. I. Title.
TA1632.P7 2007
621.36'7—dc22 2006046397
Printed in the United States of America.
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To my wife, Shelly,
whose image needs no enhancement
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CONTENTS
Preface xiii
Acknowledgments xvii
PART 1 CONTINUOUS IMAGE CHARACTERIZATION 1
1 Continuous Image Mathematical Characterization 3
1.1 Image Representation, 3
1.2 Two-Dimensional Systems, 5
1.3 Two-Dimensional Fourier Transform, 10
1.4 Image Stochastic Characterization, 14
2 Psychophysical Vision Properties 23
2.1 Light Perception, 23
2.2 Eye Physiology, 26
2.3 Visual Phenomena, 29
2.4 Monochrome Vision Model, 33
2.5 Color Vision Model, 39
3 Photometry and Colorimetry 45
3.1 Photometry, 45
3.2 Color Matching, 49
vii
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viii CONTENTS
3.3 Colorimetry Concepts, 54
3.4 Tristimulus Value Transformation, 61
3.5 Color Spaces, 63
PART 2 DIGITAL IMAGE CHARACTERIZATION 89
4 Image Sampling and Reconstruction 91
4.1 Image Sampling and Reconstruction Concepts, 91
4.2 Monochrome Image Sampling Systems, 99
4.3 Monochrome Image Reconstruction Systems, 110
4.4 Color Image Sampling Systems, 119
5 Image Quantization 127
5.1 Scalar Quantization, 127
5.2 Processing Quantized Variables, 133
5.3 Monochrome and Color Image Quantization, 136
PART 3 DISCRETE TWO-DIMENSIONAL PROCESSING 145
6 Discrete Image Mathematical Characterization 147
6.1 Vector-Space Image Representation, 147
6.2 Generalized Two-Dimensional Linear Operator, 149
6.3 Image Statistical Characterization, 153
6.4 Image Probability Density Models, 158
6.5 Linear Operator Statistical Representation, 162
7 Superposition and Convolution 165
7.1 Finite-Area Superposition and Convolution, 165
7.2 Sampled Image Superposition and Convolution, 174
7.3 Circulant Superposition and Convolution, 181
7.4 Superposition and Convolution Operator Relationships, 184
8 Unitary Transforms 189
8.1 General Unitary Transforms, 189
8.2 Fourier Transform, 193
8.3 Cosine, Sine and Hartley Transforms, 199
8.4 Hadamard, Haar and Daubechies Transforms, 204
8.5 Karhunen–Loeve Transform, 211
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CONTENTS ix
9 Linear Processing Techniques 217
9.1 Transform Domain Processing, 217
9.2 Transform Domain Superposition, 220
9.3 Fast Fourier Transform Convolution, 225
9.4 Fourier Transform Filtering, 233
9.5 Small Generating Kernel Convolution, 241
PART 4 IMAGE IMPROVEMENT 245
10 Image Enhancement 247
10.1 Contrast Manipulation, 248
10.2 Histogram Modification, 259
10.3 Noise Cleaning, 267
10.4 Edge Crispening, 284
10.5 Color Image Enhancement, 291
10.6 Multispectral Image Enhancement, 298
11 Image Restoration Models 307
11.1 General Image Restoration Models, 307
11.2 Optical Systems Models, 310
11.3 Photographic Process Models, 314
11.4 Discrete Image Restoration Models, 322
12 Image Restoration Techniques 329
12.1 Sensor and Display Point Nonlinearity Correction, 329
12.2 Continuous Image Spatial Filtering Restoration, 335
12.3 Pseudoinverse Spatial Image Restoration, 345
12.4 SVD Pseudoinverse Spatial Image Restoration, 359
12.5 Statistical Estimation Spatial Image Restoration, 364
12.6 Constrained Image Restoration, 369
12.7 Blind Image Restoration, 373
12.8 Multi-Plane Image Restoration, 379
13 Geometrical Image Modification 387
13.1 Basic Geometrical Methods, 387
13.2 Spatial Warping, 400
13.3 Perspective Transformation, 404
13.4 Camera Imaging Model, 407
13.5 Geometrical Image Resampling, 410