2-D and 3-D Image Registration for Medical, Remote Sensing, and Industrial Applications
Buy Rights Online Buy Rights

Rights Contact Login For More Details

More About This Title 2-D and 3-D Image Registration for Medical, Remote Sensing, and Industrial Applications

English

To master the fundamentals of image registration, there is no more comprehensive source than 2-D and 3-D Image Registration. In addition to delving into the relevant theories of image registration, the author presents their underlying algorithms. You'll also discover cutting-edge techniques to use in remote sensing, industrial, and medical applications. Examples of image registration are presented throughout, and the companion Web site contains all the images used in the book and provides links to software and algorithms discussed in the text, allowing you to reproduce the results in the text and develop images for your own research needs. 2-D and 3-D Image Registration serves as an excellent textbook for classes in image registration as well as an invaluable working resource.

English

A. ARDESHIR GOSHTASBY, PHD, is a professor in the department of computer science and engineering at Wright State University. Dr. Goshtasby has been developing solutions to image registration problems since 1983 and has numerous publications to his credit.

English

Preface xi

Acknowledgments xiii

Acronyms xv

1 Introduction 1

1.1 Terminologies 3

1.2 Steps in Image Registration 4

1.3 Summary of the Chapters to Follow 5

1.4 Bibliographical Remarks 5

2 Preprocessing 7

2.1 Image Enhancement 7

2.1.1 Image smoothing 7

2.1.2 Deblurring 11

2.2 Image Segmentation 15

2.2.1 Intensity thresholding 15

2.2.2 Boundary detection 17

2.3 Summary 39

2.4 Bibliographical Remarks 40

3 Feature Selection 43

3.1 Points 43

3.2 Lines 51

3.2.1 Line detection using the Hough transform 52

3.2.2 Least-squares line fitting 53

3.2.3 Line detection using image gradients 56

3.3 Regions 58

3.4 Templates 59

3.5 Summary 60

3.6 Bibliographical Remarks 60

4 Feature Correspondence 63

4.1 Point Pattern Matching 63

4.1.1 Matching using scene coherence 64

4.1.2 Matching using clustering 67

4.1.3 Matching using invariance 70

4.2 Line Matching 74

4.3 Region Matching 77

4.3.1 Shape matching 78

4.3.2 Region matching by relaxation labeling 82

4.4 Chamfer Matching 86

4.4.1 Distance transform 87

4.5 Template Matching 92

4.5.1 Similarity measures 92

4.5.2 Gaussian-weighted templates 99

4.5.3 Template size 100

4.5.4 Coarse-to-fine methods 101

4.6 Summary 103

4.7 Bibliographical Remarks 103

5 Transformation Functions 107

5.1 Similarity Transformation 112

5.2 Projective and Affine Transformations 115

5.3 Thin-Plate Spline 116

5.4 Multiquadric 120

5.5 Weighted Mean Methods 123

5.6 Piecewise Linear 129

5.7 Weighted Linear 131

5.8 Computational Complexity 134

5.9 Properties of the Transformation Functions 136

5.10 Summary 139

5.11 Bibliographical Remarks 140

6 Resampling 143

6.1 Nearest Neighbor 144

6.2 Bilinear Interpolation 145

6.3 Cubic Convolution 147

6.4 Cubic Spline 149

6.5 Radially Symmetric Kernels 150

6.6 Summary 153

6.7 Bibliographical Remarks 154

7 Performance Evaluation 155

7.1 Feature Selection Performance 156

7.2 Feature Correspondence Performance 160

7.3 Transformation Function Performance 161

7.4 Registration Performance 163

7.5 Summary 164

7.6 Bibliographical Remarks 164

8 Image Fusion 167

8.1 Fusing Multi-Exposure Images 168

8.1.1 Image blending 168

8.1.2 Examples 172

8.2 Fusing Multi-Focus Images 175

8.3 Summary 177

8.4 Bibliographical Remarks 177

9 Image Mosaicking 181

9.1 Problem Description 182

9.2 Determining the Global Transformation 182

9.3 Blending Image Intensities 185

9.4 Examples 186

9.5 Mosaicking Range Images 189

9.6 Evaluation 192

9.7 Summary 193

9.8 Bibliographical Remarks 194

10 Stereo Depth Perception 197

10.1 Stereo Camera Geometry 198

10.2 Camera Calibration 202

10.3 Image Rectification 204

10.4 The Correspondence Process 207

10.4.1 Constraints in stereo 207

10.4.2 Correspondence algorithms 210

10.5 Interpolation 217

10.6 Summary 219

10.7 Bibliographical Remarks 220

Glossary 223

References 229

Index 255

English

"...is a valuable contribution, useful also to researchers in computational geometric modeling, and reverse engineering." (Computing Reviews.com, September 22, 2005)
loading