Digital Image Processing: An Algorithmic Approach with MATLAB

by Qidwai; Uvais

• ISBN13: 9781420079500
• ISBN10: 1420079506
• Format: Hardcover
• Copyright: 2009-10-15
• Publisher: Chapman & Hall/

Summary

This text focuses on theory algorithms and MATLAB® implementation. Each chapter presents theoretical background with extensive mathematical treatment as well as algorithmic structures and data manipulation that emphasize matrix and linear algebra-based architecture and system design. The chapters also include MATLAB exercises and sample programs to help readers who lack a sound background in engineering and mathematics. The authors also provide actual classroom-based summaries that are designed to be used as lecture notes. The accompanying CD-ROM and supplementary website features MATLAB programs, PowerPoint presentations, and lecture material for instructors.

Table of Contents

Preface	p. xv
About the Authors	p. xix
Introduction to Image Processing and the Matlab“ Environment
Introduction	p. 1
What Is an Image?	p. 2
Digital Image Definitions: Theoretical Account	p. 2
Image Properties	p. 5
Signal-to-Noise Ratio	p. 5
Image Bit Resolution	p. 5
Matlab	p. 7
Why Matlab for Image Processing	p. 9
The Image Processing Toolbox in Matlab	p. 10
Algorithmic Account	p. 11
Sampling	p. 11
Noisy Image	p. 11
Bit Resolution	p. 12
Matlab Code	p. 13
Basic Steps	p. 13
Sampling	p. 14
Noisy Image	p. 14
Bit Resolution	p. 14
Summary	p. 15
Exericises	p. 16
Image Acquisition, Types, and File I/O	p. 19
Image Acquisition	p. 19
Cameras	p. 20
Image Types and File I/O	p. 23
Bitmap Format	p. 24
JPEG Format	p. 24
GIF Format	p. 24
TIFF Format	p. 25
Basics of Color Imges	p. 25
Other Color Spaces	p. 27
YIQ Color Space	p. 27
YCbCr Color Space	p. 28
HSV Color Space	p. 28
Algorithmic Account	p. 29
Image Conversions	p. 32
Matlab Code	p. 32
Summary of Image Types and Numeric	p. 36
Exercises	p. 38
Image Arithmetic	p. 39
Introduction	p. 39
Operator Basics	p. 39
Theoretical Treatment	p. 40
Pixel Addition	p. 40
Pixel Subtraction	p. 41
Pixel Multiplication and Scaling	p. 42
Pixel Division	p. 43
Blending	p. 43
Algorithmic Treatment	p. 44
Image Addition	p. 44
Image Subtraction/Multiplication/Division	p. 44
Image Blending and Linear Combinations	p. 46
Coding Examples	p. 48
Image Addition	p. 48
Image Subtraction	p. 50
Multiplying Images	p. 51
Dividing Images	p. 53
Image Blending and Linear Combinations	p. 54
Summary	p. 56
Exericises	p. 56
Affine and Logical Operations, Distortions, and Noise in Images	p. 59
Introduction	p. 59
Affine Operations	p. 59
Logical Operators	p. 62
Noise in Images	p. 65
Photon Noise	p. 66
Thermal Noise	p. 66
On-Chip Electronic Noise	p. 67
KTC Noise	p. 67
Amplifier Noise	p. 67
Quantization Noise	p. 67
Distortions in Images	p. 68
Linear Motion Blur	p. 68
Uniform Out-of-Focus Blur	p. 69
Atmospheric Turbulence Blur	p. 70
Scatter Blur	p. 70
Algorithmic Account	p. 70
Affine Operations	p. 70
Logical Operators	p. 72
Distortions and Noise	p. 74
Matlab Code	p. 75
Affine and Logical Operators	p. 76
Noise in Images	p. 77
Blur in Images	p. 78
Summary	p. 80
Exercises	p. 81
Image Transforms	p. 83
Introduction	p. 83
Discrete Fourier Transform (DFT) in 2D	p. 84
Wavelet Transforms	p. 85
Hough Transform	p. 91
Algorithmic Account	p. 94
Fourier Transform	p. 94
Wavelet Transform	p. 94
Hough Transform	p. 94
Matlab“ Code	p. 95
Fourier Transform	p. 95
Wavelet Transform	p. 98
Hough Transform	p. 99
Summary	p. 99
Exerices	p. 100
Spatial and Frequency Domain Filter Design	p. 103
Introduction	p. 103
Spatial Domain Filter Design	p. 103
Convolution Operation	p. 104
Averaging/Mean Filter	p. 104
Median Filter	p. 105
Gaussian Smoothing	p. 108
Conservative Smoothing	p. 108
Frequency-Based Filter Design	p. 109
Algorithmic Account	p. 112
Spatial Filtering (Convolution Based)	p. 112
Spatial Filtering (Case Based)	p. 115
Frequency Filtering	p. 116
Matlab“ Code	p. 116
Summary	p. 120
Exercises	p. 120
Image Restoration and Blind Deconvolution	p. 123
Introduction	p. 123
Image Representation	p. 124
Deconvolution	p. 127
Algorthmic Account	p. 131
Lucy-Richardson Method	p. 132
Wiener Method	p. 132
Blind Deconvolution	p. 133
Matlab Code	p. 135
Summary	p. 136
Exercises	p. 137
Image Compression	p. 139
Introduction	p. 139
Image Compression-Decompression Steps	p. 140
Error Metrics	p. 141
Classifying Image Data	p. 142
Discrete Cosine Transform	p. 142
Bit Allocation	p. 143
Quantization	p. 145
Entropy Coding	p. 149
JPEG Compression	p. 149
JPEG's Algorithm	p. 150
Algorithmic Account	p. 151
Matlab“ Code	p. 152
Summary	p. 153
Exercises	p. 154
Edge Detection	p. 155
Introduction	p. 155
The Sobel Operator	p. 156
The Prewitt Operator	p. 158
The Canny Operator	p. 160
The Compass Operator (Edge Template Matching)	p. 161
The Zero-Crossing Detector	p. 163
Line Detection	p. 166
The Unsharp Filter	p. 167
Algorithmic Account	p. 168
Matlab Code	p. 170
Summary	p. 172
Exercises	p. 173
Binary Image Processing	p. 175
Introduction	p. 175
Dilation	p. 177
Erosion	p. 179
Opening	p. 179
Closing	p. 180
Thinning	p. 182
Thickening	p. 183
Skeletonization/Medial Axis Transform	p. 184
Algorithmic Account	p. 186
Matlab“ Code	p. 186
Summary	p. 190
Exerises	p. 190
Image Encryption and Watermarking	p. 193
Introduction	p. 193
Watermarking Methodology	p. 194
Basic Principle of Watermarking	p. 196
Problems Associated With Watermarking	p. 197
Attacks on Watermarks	p. 199
What Can Be Done?	p. 200
Algorithmic Account	p. 201
Matlab“ Code	p. 201
Summary	p. 203
Exericises	p. 204
Image Classification and Segmentation	p. 205
Introduction	p. 205
Supervised Classification	p. 206
Unsupervised Classification	p. 206
General Idea of Classification	p. 207
Common Intensity-Connected Pixel: Naïve Classifier	p. 208
Nearest Neighbor Classifier	p. 209
Mechanism of Operation	p. 211
Unsupervised Classification	p. 212
Algorithmic Account	p. 213
Matlab“ Code	p. 214
Summary	p. 218
Exrecises	p. 219
Image-Based Object Tracking	p. 221
Introduction	p. 221
Methodologies	p. 221
Background Subtraction	p. 223
Artifacts	p. 225
Temporal Difference Between Frames	p. 226
Gradient Difference	p. 226
Correlation-Bases Tracking	p. 227
Color-Based Tracking	p. 229
Algorithmic Account	p. 231
Matlab Code	p. 231
Summary	p. 239
Exericises	p. 40
Face Recognition	p. 241
Introduction	p. 241
Face Recognition Approaches	p. 241
Vector Representation	p. 242
Linear (Subspace) Analysis	p. 243
Principal Components Analysis	p. 244
Databases and Performance Evaluation	p. 244
Process Details	p. 46
Algorithmic Account	p. 249
Matlab“ Code	p. 250
Summary	p. 251
Exercises	p. 252
Soft Computing in Image Processing	p. 253
Introduction	p. 253
Fuzzy Logic in Image Processing	p. 255
Why Fuzzy Image Processing?	p. 256
Fuzzy Classifier	p. 258
Fuzzy Denoising	p. 261
Algorithmic Account	p. 263
Matlab Code	p. 263
Summary	p. 266
Excrises	p. 266
Bibliography	p. 269
Gossary	p. 275
Index	p. 283
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