visual computation methods

visual computation methods
作 者: 谢剑斌
出版社: 科学出版社
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作者简介

暂缺《visual computation methods》作者简介

内容简介

本书是电子、计算机与自动化学科方向的专著,为使读者全面了解视频分析算法的背景、思想、原理、仿真及特点,本书详尽地介绍了多种算子、描述子、滤波、变换、方法等的基本原理,深入地阐述了视频分析算法的实验仿真,系统地总结了其优点和缺点,并提供配套的实验仿真源代码。

图书目录

CONTENTS

PREFACE

Chapter 1 Video Image Enhancement 1

1.1 Recursive Median Filter 1

References 2

1.2 Least Squares Filter 2

1.3 Homomorphic Filter 7

References 10

1.4 Bilateral Filter 10

References 14

1.5 Guided Filter 14

References 16

1.6 Lateral Inhibition Network 16

References 22

1.7 Mathematical Morphology 22

References 30

Chapter 2 Video Image Segmentation 31

2.1 Double-Peak Histogram 31

References 34

2.2 Watershed 34

References 36

2.3 Regional Split-and-Merge 37

References 38

2.4 OTSU 38

References 40

2.5 Maximum 2D Entropy 41

References 47

2.6 2D Cross-Entropy 48

References 55

Chapter 3 Key Point Detection 56

3.1 Moravec 56

References 58

3.2 Forstner 58

References 60

3.3 Harris 60

References 64

3.4 SUSAN 64

References 69

3.5 CSS 69

References 74

3.6 FAST 74

References 77

3.7 DoG 77

References 80

3.8 LoG 80

References 83

Chapter 4 Visual Feature Descriptors 84

4.1 Hu Moment 84

References 86

4.2 Legendre Moments 87

4.3 Fourier Descriptors 89

References 91

4.4 Haar 91

References 96

4.5 HOG 96

References 98

4.6 LBP 99

References 103

4.7 SIFT 103

References 112

4.8 SURF 112

References 116

Chapter 5 Transform and Dimension Reduction 117

5.1 K-L Transform 117

References 119

5.2 DCT Transform 120

References 126

5.3 Gabor Transform 126

References 129

5.4 Wavelet Transform 129

References 135

5.5 Haar Transform 136

References 140

5.6 Hough Transform 140

References 146

5.7 LPT Transform 146

References 150

5.8 PCA 150

References 154

5.9 LDA 154

References 157

Chapter 6 Clustering and Classification 158

6.1 Measure Methods of Similarity 158

6.2 K-Means Clustering 162

References 165

6.3 Bayesian Methods 165

References 168

6.4 Adaptive Boosting 168

References 174

6.5 SVM 174

References 181

Chapter 7 Motion Detection and Target Tracking 182

7.1 Background Subtraction 182

References 189

7.2 Temporal Difference 189

References 194

7.3 Optical Flow 194

References 202

7.4 Kalman Filtering 202

References 207

7.5 Mean Shift 207

References 211

7.6 CamShift Method 211

References 213