Handbook of Image and Video Processing / Edition 1

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Overview

The Handbook of Image and Video Processing contains a comprehensive and highly accessible presentation of all essential mathematics, techniques, and algorithms for every type of image and video processing used by scientists and engineers. The timely volume will provide both the novice and the seasoned practitioner with the necessary information and skills to be able to develop algorithms and applications for multimedia, digital imaging, digital video, telecommunications, and World Wide Web industries.
Handbook of Image and Video Processing will also serve as a textbook for courses such as digital image processing, digital image analysis, digital video, video communications, multimedia, and biomedical image processing in the departments of electrical and computer engineering and computer science.

KEY FEATURES: * No other resource contains the same breadth of up-to-date coverage
* Contains over 100 example algorithm illustrations
* Contains a series of extremely accessible tutorial chapters
* Indispensable for researchers in telecommunications, Internet applications, multimedia, and nearly every branch of science

Al Bovik is one of the best known image processing experts in the world. He was the host of the first IEEE International Conference on Image Processing in 1994 and he is the current editor-in-chief of IEEE Transactions on Image Processing. He is affiliated with the University of Texas, Austin.

Audience: Electrical engineers, computer engineers, materials scientists, optical engineers, microscopists, computer scientists, information scientists, and financial institutions.

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Product Details

  • ISBN-13: 9780121197902
  • Publisher: Elsevier Science & Technology Books
  • Publication date: 6/28/2000
  • Series: Communications, Networking, and Multimedia Series
  • Edition description: Older Edition
  • Edition number: 1
  • Pages: 891
  • Product dimensions: 8.74 (w) x 11.27 (h) x 2.07 (d)

Meet the Author

Al Bovik is the General Dynamics Endowed Fellow and Professor in the Department of Electrical and Computer Engineering at the University of Texas at Austin, where he is the Associate Director of the Center for Vision and Image Sciences. He has published nearly 300 techincal articles in the general area of image and video processing and holds two U.S. patents.

Dr. Bovik is a recipient of the IEEE Signal Processing Society Meritorious Service Award (1998), and is a two-time Honorable Mention winner of the international Pattern Recognition Society Award. He is a fellow of the IEEE, is the Editor-in-Chief of the IEEE Transactions on Image Processing, serves on many other boards and panels, and was the Founding General Chairman of the IEEE International Conference on Image Processing, which was first held in Austin, Texas in 1994.

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Read an Excerpt

1.0 Introduction

Objectives of this Handbook

The goals of this Handbook are ambitious, since it is intended to reach a broad audience that is interested in a wide variety of image and video processing applications. Moreover, it is intended to be accessible to readers that have a diverse background, and that represent a wide spectrum of levels of preparation and engineering or computer education. However, a Handbook format is ideally suited for this multiuser purpose, since it allows for a presentation that adapts to the reader's needs. In the early part of the Handbook we present very basic material that is easily accessible even for novices to the image processing field. These chapters are also useful for review, for basic reference, and as support for later chapters. In every major section of the Handbook, basic introductory material is presented, as well as more advanced chapters that take the reader deeper into the subject.

Unlike textbooks on image processing, the Handbook is therefore not geared toward a specified level of presentation, nor does it uniformly assume a specific educational background. There is material that is available for the beginning image processing user, as well as for the expert. The Handbook is also unlike a textbook in that it is not limited to a specific point of view given by a single author. Instead, leaders from image and video processing education, industry, and research have been called upon to explain the topical material from their own daily experience. By calling upon most of the leading experts in the field, we have been able to provide a complete coverage of the image and video processing area without sacrificing any level of understanding of any particular area.

Because of its broad spectrum of coverage, we expect that the Handbook of Image and Video Processingwill serve as an excellent textbook as well as reference. It has been our objective to keep the student's needs in mind, and we believe that the material contained herein is appropriate to be used for classroom pre- sentations ranging from the introductory undergraduate level, to the upper-division undergraduate, to the graduate level. Al- though the Handbook does not include "problems in the back," this is not a drawback since the many examples provided in every chapter are sufficient to give the student a deep understanding of the function of the various image and video processing algorithms. This field is very much a visual science, and the principles underlying it are best taught with visual examples. Of course, we also foresee the Handbook as providing easy reference, background, and guidance for image and video processing professionals working in industry and research.

Our specific objectives are to

  • provide the practicing engineer and the student with a highly accessible resource for learning and using image/video processing algorithms and theory
  • provide the essential understanding of the various image and video processing standards that exist or are emerging, and that are driving today's explosive industry
  • provide an understanding of what images are, how they are modeled, and give an introduction to how they are perceived
  • provide the necessary practical background to allow the engineer student to acquire and process his or her own digital image or video data
  • provide a diverse set of example applications, as separate complete chapters, that are explained in sufficient depth to serve as extensible models to the reader's own potential applications

The Handbook succeeds in achieving these goals, primarily because of the many years of broad educational and practical experience that the many contributing authors bring to bear in explaining the topics contained herein.

Organization of the Handbook

Since this Handbook is emphatically about processing images and video, the next section is immediately devoted to basic algorithms for image processing, instead of surveying methods and devices for image acquisition at the outset, as many textbooks do. Section 2 is divided into three chapters, which respectively introduce the reader to the most fundamental two-dimensional image processing techniques. Chapter 2.1 lays out basic methods for gray-level image processing, which includes point operations, the image histogram, and simple image algebra. The methods described there stand alone as algorithms that can be applied to most images, but they also set the stage and the notation for the more involved methods discussed in later chapters. Chapter 2.2 describes basic methods for image binarization and for binary image processing, with emphasis on morphological binary image processing. The algorithms described there are among the most widely used in applications, especially in the biomedical area. Chapter 2.3 explains the basics of the Fourier transform and frequency-domain analysis, including discretization of the Fourier transform and discrete convolution. Special emphasis is placed on explaining frequency-domain concepts through visual examples. Fourier image analysis provides a unique opportunity for visualizing the meaning of frequencies as components of signals. This approach reveals insights that are difficult to capture in one-dimensional, graphical discussions.

Section 3 of the Handbook deals with methods for correcting distortions or uncertainties in images and for improving image information by combining images taken from multiple views. Quite frequently the visual data that are acquired have been in some way corrupted. Acknowledging this and developing algorithms for dealing with it is especially critical since the human capacity for detecting errors, degradations, and delays in digitally delivered visual data is quite high. Image and video signals are derived from imperfect sensors, and the processes of digitally converting and transmitting these signals are subject to errors. There are many types of errors that can occur in image or video data, including, for example, blur from motion or defocus; noise that is added as part of a sensing or transmission process; bit, pixel, or frame loss as the data are copied or read; or artifacts that are introduced by an image or video compression algorithm. As such, it is important to be able to model these errors, so that numerical algorithms can be developed to ameliorate them in such a way as to improve the data for visual consumption. Section 3 contains three broad categories of topics. The first is image/video enhancement, in which the goal is to remove noise from an image while retaining the perceptual fidelity of the visual information; these are seen to be conflicting goals. Chapters are included that describe very basic linear methods; highly efficient nonlinear methods; and recently developed and very powerful wavelet methods; and also extensions to video enhancement. The second broad category is image/video restoration, in which it is assumed that the visual information has been degraded by a distortion function, such as defocus, motion blur, or atmospheric distortion, and more than likely, by noise as well. The goal is to remove the distortion and attenuate the noise, while again preserving the perceptual fidelity of the information contained within. And again, it is found that a balanced attack on conflicting requirements is required in solving these difficult, ill-posed problems. The treatment again begins with a basic, introductory chapter; ensuing chapters build on this basis and discuss methods for restoring multichannel images (such as color images); multiframe images (i.e., using information from multiple images taken of the same scene); iterative methods for restoration; and extensions to video restoration. Related topics that are considered are motion detection and estimation, which is essential for handling many problems in video processing, and a general framework for regularizing ill-posed restoration problems. Finally, the third category involves the extraction of enriched information about the environment by combining images taken from multiple views of the same scene. This includes chapters on methods for computed stereopsis and for image stabilization and mosaicking.

Section 4 of the Handbook deals with methods for image and video analysis. Not all images or videos are intended for direct human visual consumption. Instead, in many situations it is of interest to automate the process of repetitively interpreting the content of multiple images or video data through the use of an image or video analysis algorithm...

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Table of Contents

Sect. I Introduction
1.1 Introduction to digital image and video processing 3
Sect. II Basic image processing techniques
2.1 Basic gray-level image processing 21
2.2 Basic binary image processing 39
2.3 Basic tools for image Fourier analysis 57
2.4 Image processing education 73
Sect. III Image and video processing
3.1 Basic linear filtering with application to image enhancement 99
3.2 Nonlinear filtering for image analysis and enhancement 109
3.3 Morphological filtering for image enhancement and feature detection 135
3.4 Wavelet denoising for image enhancement 157
3.5 Basic methods for image restoration and identification 167
3.6 Regularization in image restoration and reconstruction 183
3.7 Multichannel image recovery 203
3.8 Multi-frame image restoration 219
3.9 Iterative image restoration 235
3.10 Motion detection and estimation 253
3.11 Video enhancement and restoration 275
3.12 Local and global stereo methods 297
3.13 Image sequence stabilization, mosaicking, and superresolution 309
Sect. IV Image and video analysis
4.1 Computational models of early human vision 325
4.2 Multiscale image decompositions and wavelets 347
4.3 Random field models 361
4.4 AM-FM image models : fundamental techniques and emerging trends 377
4.5 Image noise models 397
4.6 Color and multispectral image representation and display 411
4.7 Statistical modeling of photographic images 431
4.8 Statistical methods for image segmentation 443
4.9 Multiband techniques, texture classification, and segmentation 455
4.10 Video segmentation 471
4.11 2D and 3D motion tracking in digital video 491
4.12 Adaptive and neural methods for image segmentation 519
4.13 Gradient and Laplacian edge detection 535
4.14 Diffusion partial differential equations for edge detection 555
4.15 Shape smoothing and PDEs 573
4.16 PDEs for morphological scale spaces and eikonal applications 587
4.17 Geometric active contours for image segmentation 613
4.18 Software for image and video processing 629
Sect. V Image compression
5.1 Lossless coding 643
5.2 Block truncation coding 661
5.3 Fundamentals of vector quantization 673
5.4 Wavelet image compression 689
5.5 Lossy image compression : the JPEG and JPEG2000 standards 709
5.6 The JPEG lossless image compression standards 733
5.7 Multispectral image coding 747
5.8 Recover methods for post processing for compressed images 761
Sect. VI Video compression
6.1 Basic concepts and techniques of video coding and the H.261 standard 777
6.2 Interframe subband/wavelet scalable video coding 799
6.3 Digital video transcoding 819
6.4 MPEG-1 and MPEG-2 video standards 833
6.5 MPEG-4, H.264/AVC, and MPEG-7; new standards for the digital video industry 849
6.6 Embedded video codecs 877
Sect. VII Image and video acquisition
7.1 Image scanning, sampling, and interpolation 895
7.2 Video sampling and interpolation 911
Sect. VIII Image and video rendering and assessment
8.1 Image quantization, halftoning, and printing 925
8.2 Perceptual criteria for image quality evaluation 939
8.3 Structural approaches to image quality assessment 961
8.4 Information theoretic approaches to image quality assessment 975
Sect. IX Image and video storage, retrieval, and communication
9.1 Image and video indexing and retrieval 993
9.2 A unified framework for video summerization browsing, and retrieval 1013
9.3 Video communication networks 1031
9.4 Wireless video 1065
9.5 Watermarking techniques for image authentication and copyright protection 1083
9.6 Visual cryptography : the combinatorial and halftoning frameworks 1111
Sect. X Applications of image processing
10.1 Synthetic aperture radar algorithms 1131
10.2 Computed tomography 1155
10.3 Cardiac image processing 1175
10.4 Computer-aided detection and diagnosis in mammography 1195
10.5 Fingerprint classification and matching 1219
10.6 Face recognition from still images and videos 1235
10.7 How iris recognition works 1251
10.8 Exploiting visual information in automatic speech processing 1263
10.9 Confocal microscopy 1291
10.10 Computer-assisted microscopy 1311
10.11 Statistical models for Bayesian object recognition 1341
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  • Anonymous

    Posted May 11, 2001

    Image processing encyclopedia for the strong of heart

    This is an encyclopedia of image processing topics. It contains some introductory material to help people understand what images are and how to process them. The majority of the text, however, is for experienced people wanting to look up topics. This book is big. It is about 8'x11' by 900 pages. It contains material from 100 different professionals on 50 different topics. The style is academic. The editor is the editor of the IEEE Transactions on Image Processing. The page style is similar to what you would see in an IEEE Transaction. There is plenty of math. The text explains the mathematics, but not to the depth I would like to see. The authors illustrate the techniques with many images. If there are no 'before and after' images in an image processing book, reject it. Well, this book has plenty of images. That is a strong point. A week point is there is no source code illustrating the techniques and algorithms. I find this a major weakness, but one that is not unique to this book. The authors leave much to the reader. This is not a read from cover to cover book. The reader must go slow, take notes, study, and read again to understand the material. All in all, this is a good source of knowledge on image processing. If you work with images and write software to process images, you should have this book on your desk.

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