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基本説明
An ideal teaching resource for both undergraduate and postgraduate students. New material includes image processing and colour, sine and cosine transforms, Independent Component Analysis (ICA), phase congruency and the monogenic signal and several other new topics. These updates are combined with coverage of classic topics in image processing, such as orthogonal transforms and image enhancement, making this a truly comprehensive text on the subject.
Full Description
Following the success of the first edition, this thoroughly updated second edition of Image Processing: The Fundamentals will ensure that it remains the ideal text for anyone seeking an introduction to the essential concepts of image processing. New material includes image processing and colour, sine and cosine transforms, Independent Component Analysis (ICA), phase congruency and the monogenic signal and several other new topics. These updates are combined with coverage of classic topics in image processing, such as orthogonal transforms and image enhancement, making this a truly comprehensive text on the subject.
Key features:
Presents material at two levels of difficulty: the main text addresses the fundamental concepts and presents a broad view of image processing, whilst more advanced material is interleaved in boxes throughout the text, providing further reference for those who wish to examine each technique in depth.
Contains a large number of fully worked out examples.
Focuses on an understanding of how image processing methods work in practice.
Illustrates complex algorithms on a step-by-step basis, and lists not only the good practices but also identifies the pitfalls in each case.
Uses a clear question and answer structure.
Includes a CD containing the MATLAB® code of the various examples and algorithms presented in the book. There is also an accompanying website with slides available for download for instructors as a teaching resource.
Image Processing: The Fundamentals, Second Edition is an ideal teaching resource for both undergraduate and postgraduate students. It will also be of value to researchers of various disciplines from medicine to mathematics with a professional interest in image processing
Contents
Preface xxiii
1 Introduction 1
2 Image Transformations 47
2.1 Singular value decomposition 51
2.2 Haar, Walsh and Hadamard transforms 74
2.3 Discrete Fourier transform 94
2.4 The even symmetric discrete cosine transform (EDCT) 138
2.5 The odd symmetric discrete cosine transform (ODCT) 149
2.6 The even antisymmetric discrete sine transform (EDST) 157
2.7 The odd antisymmetric discrete sine transform (ODST) 167
3 Statistical Description of Images 177
3.1 Random fields 178
3.2 Karhunen-Loeve transform 201
3.3 Independent component analysis 234
4 Image Enhancement 293
4.1 Elements of linear filter theory 294
4.2 Reducing high frequency noise 311
4.3 Reducing low frequency interference 351
4.4 Histogram manipulation 367
4.5 Generic deblurring algorithms 383
5 Image Restoration 395
5.1 Homogeneous linear image restoration: inverse filtering 396
5.2 Homogeneous linear image restoration: Wiener filtering 419
5.3 Homogeneous linear image restoration: Constrained matrix inversion 436
5.4 Inhomogeneous linear image restoration: the whirl transform 468
5.5 Nonlinear image restoration: MAP estimation 490
5.6 Geometric image restoration 513
6 Image Segmentation and Edge Detection 527
6.1 Image segmentation 528
6.2 Edge detection 591
6.3 Phase congruency and the monogenic signal 625
7 Image Processing for Multispectral Images 669
7.1 Image preprocessing for multispectral images 671
7.2 The physics and psychophysics of colour vision 700
7.3 Colour image processing in practice 742
Bibliographical notes 775
References 777
Index 781
