Principles of Digital Image Processing: Core Algorithms (Google eBook)

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Springer Science & Business Media, Jul 8, 2010 - Computers - 341 pages
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This easy-to-follow textbook is the second of 3 volumes which provide a modern, algorithmic introduction to digital image processing, designed to be used both by learners desiring a firm foundation on which to build, and practitioners in search of critical analysis and modern implementations of the most important techniques. It extends the introductory material presented in the first volume (Fundamental Techniques) with additional techniques that form part of the standard image processing toolbox. The textbook presents a critical selection of algorithms, illustrated explanations and concise mathematical derivations, for readers to gain a deeper understanding of the topic. It also encourages the reader to actively construct and experiment with the algorithms to develop their understanding for how to use these methods in the real world. This reader-friendly text will equip undergraduates with a deeper understanding of the topic as well as being valuable for further developing knowledge for self-study.
  

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Contents

Introduction
1
11 Programming with Images
2
12 Image Analysis
3
Regions in Binary Images
5
21 Finding Image Regions
6
22 Region Contours
17
23 Representing Image Regions
26
24 Properties of Binary Regions
32
73 The Discrete Fourier Transform DFT
144
74 Implementing the DFT
154
75 Exercises
156
The Discrete Fourier Transform in 2D
157
82 Visualizing the 2D Fourier Transform
162
83 Frequencies and Orientation in 2D
164
84 2D Fourier Transform Examples
171
85 Applications of the DFT
175

25 Exercises
46
Detecting Simple Curves
49
32 Hough Transform
50
33 Implementing the Hough Transform
55
34 Hough Transform for Circles and Ellipses
63
35 Exercises
67
Corner Detection
69
42 Harris Corner Detector
70
43 Implementation
72
44 Exercises
84
Color Quantization
85
51 Scalar Color Quantization
86
52 Vector Quantization
88
53 Exercises
95
Colorimetric Color Spaces
96
61 CIE Color Spaces
98
62 CIE Lab
104
63 sRGB
106
64 Adobe RGB
111
66 Colorimetric Support in Java
114
67 Exercises
124
Introduction to Spectral Techniques
125
71 The Fourier Transform
126
72 Working with Discrete Signals
137
86 Exercises
180
The Discrete Cosine Transform DCT
183
92 TwoDimensional DCT
187
93 Other Spectral Transforms
188
94 Exercises
190
Geometric Operations
191
101 2D Mapping Function
193
102 Resampling the Image
209
103 Interpolation
210
104 Java Implementation
238
105 Exercises
253
Comparing Images
255
111 Template Matching in Intensity Images
257
112 Matching Binary Images
269
113 Exercises
278
Mathematical Notation
279
A2 Set Operators
281
A3 Complex Numbers
282
Source Code
283
B2 Harris Corner Detector
294
B3 MedianCut Color Quantization
301
Bibliography
313
Index
320
Copyright

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