Thanki / Kothari Digital Image Processing using SCILAB

1. Auflage 2018
ISBN: 978-3-319-89533-8
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 168 Seiten

This book provides basic theories and implementations using SCILAB open-source software for digital images. The book simplifies image processing theories and well as implementation of image processing algorithms, making it accessible to those with basic knowledge of image processing. This book includes many SCILAB programs at the end of each theory, which help in understanding concepts. The book includes more than sixty SCILAB programs of the image processing theory. In the appendix, readers will find a deeper glimpse into the research areas in the image processing.

Dr. Rohit Thanki obtained his Ph.D. in Multibiometric System Security using CS Theory and Watermarking from C. U. Shah University, Wadhwan city, Gujarat, India in 2017. His area of research interest is Digital Watermarking, Biometrics System, Security, Compressive Sensing, Pattern Recognition and Image Processing. He has published 3 books, 4 book chapters and 28 research papers to his credit in refereed & indexed journals, and conference at international and national level. His international recognition includes his professional memberships & services in refereed organizations, programme committees and reviewer for journals published by IEEE, Elsevier, Taylor & Francis, Springer, IGI-Global etc. Dr. Ashish Kothari obtained his Ph.D. in Digital Video Watermarking from JJT University, Rajasthan, India in 2013. He is working as an Associate professor and Head of Electronics and Communication Engineering, Atmiya Institute of Technology and Science, Rajkot, Gujarat, India. He is also recognized Ph.D. supervisor at Gujarat Technological University, Ahmedabad, Gujarat, India. His area of research interest is Image Processing, Video Processing, Digital Watermarking and Signal Processing. He has published 1 book, 1 book chapters and more than 25 research papers to his credit in refereed & indexed journals, and conferences at international and national level. His international recognition includes his professional memberships & services in refereed organizations, programme committees and reviewer for journals.

Autoren/Hrsg.

Thanki, Rohit M.

Kothari, Ashish M.

Inhaltsverzeichnis

1;Preface;5
2;Acknowledgments;7
3;Contents;8
4;List of Figures;12
5;Chapter 1: Introduction;18
5.1;1.1 Introduction;18
5.2;1.2 Types of Signals;19
5.2.1;1.2.1 One-Dimensional Signals;19
5.2.2;1.2.2 Two-Dimensional Signals;20
5.2.3;1.2.3 Three-Dimensional Signals;20
5.2.4;1.2.4 Multi-Dimensional Signals;20
5.3;1.3 A Digital Image and Its Processing;21
5.4;1.4 Information of Scilab Software;26
5.4.1;1.4.1 How to Obtain and Install Scilab;27
5.4.2;1.4.2 How to Install the Image Processing Toolbox in Scilab;27
5.5;1.5 Areas of Image Processing Covered in the Book;34
5.6;Bibliography;35
6;Chapter 2: Image Enhancement in the Spatial Domain;36
6.1;2.1 Introduction;36
6.2;2.2 Image Enhancement by Point Processing;36
6.2.1;2.2.1 Identity Transformation;37
6.2.2;2.2.2 Image Negative;38
6.2.3;2.2.3 Contrast Stretching;39
6.2.4;2.2.4 Contrast Thresholding;41
6.2.5;2.2.5 Gray Level Slicing;42
6.2.5.1;2.2.5.1 Gray Level Slicing Without Background;43
6.2.5.2;2.2.5.2 Gray Level Slicing with Background;44
6.2.6;2.2.6 Bit Plane Slicing;45
6.2.7;2.2.7 Log Transformation;46
6.2.8;2.2.8 Power Low Transformation;48
6.3;2.3 Histogram;49
6.3.1;2.3.1 Histogram Processing;52
6.3.1.1;2.3.1.1 Histogram Stretching;52
6.3.1.1.1;Example of Histogram Stretching;53
6.3.1.1.2;Solution;53
6.3.1.2;2.3.1.2 Histogram Equalization;54
6.3.1.2.1;Example of Histogram Equalization;55
6.3.1.2.2;Solution for Histogram Equalization;55
6.3.1.3;2.3.1.3 Histogram Matching (Specification);57
6.4;2.4 Image Enhancement by Neighborhood Processing: Spatial Domain Filters;58
6.4.1;2.4.1 Concept of Frequency in Images;59
6.4.2;2.4.2 Low-Pass Average Filter;60
6.4.3;2.4.3 Low-Pass Median Filter (Order Statistic Filter);61
6.4.4;2.4.4 High-Pass Filter;63
6.4.5;2.4.5 High-Boost Filter;64
6.5;2.5 Image Enhancement Using Arithmetic/Logical Operations;65
6.6;Bibliography;67
7;Chapter 3: Image Enhancement in the Frequency Domain;68
7.1;3.1 Introduction;68
7.2;3.2 Fourier Transform;69
7.2.1;3.2.1 Important Properties of Discrete Fourier Transform (DFT);71
7.3;3.3 Low-Pass Frequency Domain Filter;73
7.3.1;3.3.1 Ideal Low-Pass Filter (LPF);73
7.3.2;3.3.2 Butterworth LPF;75
7.3.3;3.3.3 Gaussian LPF;77
7.4;3.4 High-Pass Frequency Domain Filter;78
7.4.1;3.4.1 Ideal High-Pass Filter (HPF);79
7.4.2;3.4.2 Butterworth HPF;79
7.4.3;3.4.3 Gaussian HPF;81
7.5;3.5 Unsharp Masking;83
7.5.1;3.5.1 Homomorphic Filtering;84
7.6;Bibliography;86
8;Chapter 4: Image Restoration;87
8.1;4.1 Introduction;87
8.2;4.2 Image Degradation and Restoration Process;88
8.3;4.3 Noise Models;89
8.3.1;4.3.1 Gaussian Noise;89
8.3.2;4.3.2 Rayleigh Noise;91
8.3.3;4.3.3 Erlang/Gamma Noise;91
8.3.4;4.3.4 Exponential Noise;93
8.3.5;4.3.5 Uniform Noise;95
8.3.6;4.3.6 Salt and Pepper Noise;95
8.4;4.4 Periodic Noise and Estimation of Noise Parameters;96
8.5;4.5 Image Restoration: Spatial Filtering;98
8.5.1;4.5.1 Mean Filters;98
8.5.1.1;4.5.1.1 Arithmetic Mean Filter;99
8.5.1.2;4.5.1.2 Geometric Mean Filter;100
8.5.1.3;4.5.1.3 Harmonic Mean Filter;100
8.5.1.4;4.5.1.4 Contra Harmonic Mean Filter;102
8.5.2;4.5.2 Order Statistics Filters;104
8.5.2.1;4.5.2.1 Median Filter;104
8.5.2.2;4.5.2.2 Min Filter;105
8.5.2.3;4.5.2.3 Max Filter;106
8.5.2.4;4.5.2.4 Mid-Point Filter;108
8.5.2.5;4.5.2.5 Alpha Trimmed Mean Filter;109
8.5.3;4.5.3 Adaptive Filters;110
8.6;4.6 Wiener Filtering;112
8.7;Bibliography;114
9;Chapter 5: Morphological Image Processing;115
9.1;5.1 Introduction;115
9.1.1;5.1.1 Structuring Elements: Hits and Fits;115
9.2;5.2 Fundamental Morphology Operations;116
9.2.1;5.2.1 Erosion;116
9.2.2;5.2.2 Dilation;118
9.3;5.3 Compound Morphology Operations;119
9.3.1;5.3.1 Opening;119
9.3.2;5.3.2 Closing;122
9.4;5.4 Hit or Miss Transform;123
9.5;5.5 Some Morphological Algorithms;125
9.5.1;5.5.1 Boundary Extraction;126
9.5.2;5.5.2 Thinning;127
9.5.3;5.5.3 Thickening;128
9.6;Bibliography;129
10;Chapter 6: Image Segmentation;130
10.1;6.1 Introduction;130
10.2;6.2 Point Detection;130
10.3;6.3 Line Detection;131
10.4;6.4 Edge Detection;134
10.4.1;6.4.1 Sobel Edge Detector;134
10.4.2;6.4.2 Prewitt Edge Detector;136
10.4.3;6.4.3 Roberts Edge Detector;138
10.4.4;6.4.4 Laplacian of a Gaussian (LOG) Edge Detector;140
10.4.5;6.4.5 Canny Edge Detector;142
10.5;6.5 Thresholding;143
10.6;Bibliography;144
11;Chapter 7: Color Image Processing;145
11.1;7.1 Color Image Representation in SCILAB;145
11.2;7.2 Conversion of an RGB (Red, Green, Blue) Image into Other Spaces;146
11.2.1;7.2.1 NTSC Color Space;146
11.2.2;7.2.2 YCbCr Color Space;148
11.2.3;7.2.3 HSV (Hue, Saturation, Value) Color Space;148
11.2.4;7.2.4 CMY (Cyan, Magenta, Yellow) Color Space;149
11.3;7.3 Basic Operations for a Color Image;151
11.3.1;7.3.1 Histogram of a Color Image;151
11.3.2;7.3.2 Color Image Smoothing;152
11.3.3;7.3.3 Color Image Sharping;153
11.3.4;7.3.4 Color Edge Detection;155
11.4;Bibliography;156
12;Chapter 8: Applications of Digital Image Processing;157
12.1;8.1 Introduction;157
12.2;8.2 Copyright Protection;157
12.3;8.3 Image Compression;160
12.4;8.4 Fog Removal;160
12.5;8.5 Template Matching;160
12.6;8.6 Image Mosaicing;162
12.7;Bibliography;163
13;Index;165