A Concise Introduction to Image Processing using C++

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ISBN: 9781584888970 | 1584888970
Cover: Hardcover
Copyright: 11/20/2008

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A Concise Intro to Image Processing using C++ presents state-of-the-art image processing methodology, including current industrial practices for image compression, image de-noising methods based on partial differential equations, and new image compression methods such as fractal image compression and wavelet compression. It includes elementary concepts of image processing and related fundamental tools with coding examples as well as exercises. With a particular emphasis on illustrating fractal and wavelet compression algorithms, the text covers image segmentation, object recognition, and morphology. An accompanying CD-ROM contains code for all algorithms.

Preface	p. xv
Basic Concepts of Images	p. 1
Analogue Signals	p. 1
Digital Signals	p. 3
Sampling	p. 4
Quantisation	p. 5
Grey-Scale Images	p. 6
Resolution	p. 6
Grey Levels	p. 6
Colour Images	p. 7
The RGB Colour Model	p. 9
The YIQ Colour Model	p. 10
The YUV Model	p. 11
The HSI Model	p. 12
Conversion from the RGB Model to the HSI Model	p. 14
Conversion from the HSI Model to the RGB Model	p. 14
The CMY Model	p. 16
Image Storage Formats	p. 17
The BMP Format	p. 17
The RAW Format	p. 18
The JPEG format	p. 18
The GIF Format	p. 19
Video	p. 19
Exercises	p. 20
References	p. 20
Partial Code Examples	p. 21
Convert an 8-bit grey-scale image to a binary image	p. 21
Convert a 24-bit colour image to its red channel image	p. 22
Convert an 8-bit colour image to a grey-scale image	p. 25
Basic Image Processing Tools	p. 29
Correlation Operation and Convolution Operation	p. 30
Correlation Operations	p. 30
Convolution Operations	p. 32
Fourier Transform	p. 37
Continuous Fourier Transform	p. 37
One-Dimensional Continuous Fourier Transform	p. 37
Two-Dimensional Continuous Fourier Transform	p. 38
The Discrete Fourier Transform	p. 38
Properties of the Discrete Fourier Transform	p. 39
The Fast Fourier Transform	p. 41
The Discrete Cosine Transform	p. 42
The Gabor Transform	p. 43
The Wavelet Transform	p. 44
The Continuous Wavelet Transform	p. 44
The Discrete Wavelet Transform	p. 45
Further Reading: Orthogonality and Completeness	p. 46
Orthogonality	p. 47
Completeness	p. 47
Exercises	p. 48
References	p. 49
Partial Code Examples	p. 49
Fourier Transformation	p. 49
DCT Transformation	p. 58
Wavelet Transformation and the inverse wavelet transformation	p. 60
Preprocessing Techniques for Images	p. 65
Pixel Brightness (Grey-Level) Transformations	p. 66
Image Enhancement Based on Histogram	p. 66
Histogram	p. 66
Histogram Equalisation	p. 66
Contrast Stretching	p. 69
Linear Transform	p. 70
The Limiting Linear Transform	p. 70
Concepts and Models of Image Preprocessing	p. 71
Image Smoothing	p. 73
Spatial-Domain Methods	p. 73
Neighbourhood-Averaging Methods	p. 73
Threshold-Averaging Methods	p. 75
Gaussian Filtering	p. 75
Median Filtering	p. 76
Weighted Median Filtering	p. 77
Frequency-Domain Methods	p. 78
Ideal Low-Pass Filtering	p. 78
Trapezoidal Low-Pass Filtering	p. 79
Butterworth Low-Pass Filtering	p. 79
Image Enhancement	p. 80
Gradient	p. 80
Gradient Image	p. 81
Gradient Operators	p. 81
Roberts Operator	p. 83
Prewitt Operator	p. 83
Sobel Operator	p. 83
Laplacian Operator	p. 84
High-Pass Filtering	p. 85
Ideal High-Pass Filtering	p. 85
Trapezoidal High-Pass Filtering	p. 87
Butterworth High-Pass Filtering	p. 87
Image Restoration	p. 87
Image Degradation Model	p. 87
Image Restoration Based on the Degradation Model	p. 89
Unconstrained Conditional Restoration	p. 89
Constrained Conditional Restoration	p. 90
Inverse Filtering	p. 91
Wiener Filtering	p. 92
Geometric Rectification	p. 93
Spatial Geometric Transforms	p. 94
Confirmation of Pixel Intensities	p. 96
Processing Methods Using Partial Differential Equations	p. 97
Diffusion-Based Models	p. 98
The Heat Conduction Model	p. 98
The Anisotropic Diffusion Model	p. 98
TV-Based Models	p. 102
Discrete Formats of PDE Models	p. 103
Further Reading	p. 104
Exercises	p. 105
References	p. 106
Partial Code Examples	p. 108
Show the Grey-Scale Histogram of an 8-Bit Grey-Scale Image	p. 108
Median Filtering	p. 112
Gradient Image Obtained by Using Sobel Operator	p. 118
Image Restoration Using the Second- and Fourth-Order Partial Differential Equations	p. 124
Image Segmentation	p. 135
Thresholding	p. 136
Semi-Thresholding and Band-Thresholding	p. 136
Semi-Thresholding	p. 136
Band-Thresholding	p. 137
Histogram-Based Thresholding	p. 137
The Mode Method	p. 138
Adaptive (Local) Method	p. 138
Optimal (Iterative) Thresholding	p. 138
Edge-Based Segmentation	p. 140
Edge Image Thresholding	p. 140
Edge Relaxation	p. 143
Border Tracing	p. 148
The Hough Transform	p. 150
Region-Based Segmentation	p. 152
The Region-Growing Method	p. 152
The Region-Merging Method	p. 153
The Region Split-and-Merge Method	p. 154
Further Reading	p. 154
Exercises	p. 155
References	p. 157
Partial Code Examples	p. 158
Optimal Thresholding Segmentation	p. 158
The Border-Tracing Method	p. 161
Mathematical Morphology	p. 167
Some Basic Concepts of Set Theory	p. 168
Sets and Elements	p. 168
Relationships between Two Sets	p. 168
Operations Involving Sets	p. 168
Morphology for Binary Images	p. 169
Binary Morphological Operation	p. 171
Dilation Operation	p. 171
Erosion Operation	p. 173
Opening and Closing Operations	p. 175
Hit-or-Miss Transformation	p. 175
Applications of Binary Morphological Operations	p. 176
Thinning and Thickening	p. 176
Skeleton Method	p. 177
Morphology for Grey-Scale Images	p. 178
Basic Grey-Scale Morphological Operations	p. 178
Dilation Operation	p. 178
Erosion Operation	p. 182
Applications of Grey-Scale Morphological Operations	p. 183
Further Reading	p. 184
Exercises	p. 185
References	p. 185
Partial Code Examples	p. 186
Binary Erosion	p. 186
Binary Skeleton	p. 195
Image Compression	p. 199
Image Fidelity Metrics	p. 200
Lossless Compression	p. 201
Huffman Encoding	p. 201
Runlength Encoding	p. 206
Lossy Compression	p. 207
Predictive Compression Methods	p. 207
Vector Quantisation	p. 208
Wavelet Compression	p. 212
Fractal Compression	p. 217
Image Compression Standards: JPEG and MPEG	p. 220
The JPEG Standard	p. 221
DCT-Based Method	p. 221
Predictive Method	p. 221
The MPEG Standard	p. 222
Further Reading	p. 223
Exercises	p. 224
References	p. 225
Partial Code Examples	p. 226
Huffman Encoding	p. 226
Fractal Image Compression	p. 236
Index	p. 243
Table of Contents provided by Ingram. All Rights Reserved.

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A Concise Introduction to Image Processing using C++

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A Concise Introduction to Image Processing using C++

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