Digital Image Processing

- About the Author - Foreword - Preface - Acknowledgements - Notation - Alphabetical - Greek - Operators - Glossary - Mathematical and Statistical - Computer Science - Organizational and Standards - Introduction - Imaging Science - Signals and Images - Image Formation - Image Information - Image Analysis - Digital Image Processing - Fundamental Problems - About this Book - Summary of Important Results - Part I: Mathematical and Computational Background - Chapter 1: Vector Fields - 1.1 Scalar Fields - 1.2 Vector Fields - 1.3 The Divergence Theorem - 1.4 Summary of Important Results - Chapter 2: 2D Fourier Theory - 2.1 The 2D Complex Fourier Series - 2.2 The 2D Delta Function - 2.3 The 2D Fourier Transform - 2.4 Physical Representation - 2.5 The Spectrum - 2.6 Definitions and Notation - 2.7 Some Important Results - 2.8 Some Important Theorems - 2.9 Convolution and Correlation - 2.10 Convolution and Correlation Theorems - 2.11 Other Integral Transforms - 2.12 Discussion - 2.13 Summary of Important Results - Chapter 3: The 2D DFT, FFT and FIR Filter - 3.1 The Discrete Fourier Transform - 3.2 The Sampling Theorem - 3.3 The Discrete Spectrum of a Digital Image - 3.4 The Fast Fourier Transform - 3.5 The Imaging Equation and Convolution in 2D - 3.6 The Finite Impulse Response Filter - 3.7 Origin of the Imaging Equation - 3.8 Summary of Important Results - Chapter 4: Field and Wave Equations - 4.1 The Langevin Equation - 4.2 Maxwell's Equations - 4.3 General Solution to Maxwell's (Microscopic) Equations - 4.4 The Macroscopic Maxwell's Equations - 4.5 EM Waves in a Homogeneous Medium - 4.6 EM Waves in an Inhomogeneous Medium - 4.7 Elastic Field Equations - 4.8 Inhomogeneous Elastic Wave Equation - 4.9 Acoustic Field Equations - 4.10 Discussion - 4.11 Summary of Important Results - Chapter 5: Green Functions - 5.1 Overview - 5.2 Introduction to the Green Function - 5.3 The Time Independent Wave Operator - 5.4 Wavefields Generated by Sources - 5.5 Time Dependent Green Function - 5.6 Time Dependent Sources - 5.7 Green Function Solution to Maxwell's Equation - 5.8 The Diffusion Equation - 5.9 Green Function Solution to the Diffusion Equation - 5.10 The Laplace and Poisson Equations - 5.11 Discussion - 5.12 Summary of Important Results - Problems: Part I - Part II: Imaging Systems Modelling - Chapter 6: Scattering Theory - 6.1 The Schrödinger and Helmholtz Equations - 6.2 Solution to the Helmholtz Equation - 6.3 Examples of Born Scattering - 6.4 Other Approximation Methods - 6.5 The Born Series - 6.6 Inverse Scattering - 6.7 Surface Scattering Theory - 6.8 Summary of Important Results - Chapter 7: Imaging of Layered Media - 7.1 Pulse-Echo Imaging - 7.2 EM Imaging of a Layered Dielectric - 7.3 Acoustic Imaging of a Layered Material - 7.4 Side-band Systems and Demodulation - 7.5 Some Applications - 7.6 Case Study: Imaging the Ionosphere - 7.7 Case Study: Radar Plasma Screening - 7.8 Summary of Important Results - Chapter 8: Projection Tomography - 8.1 Basic Principles - 8.2 Projection Tomography and Scattering Theory - 8.3 The Radon Transform - 8.4 Back-Projection PSF - 8.5 The Central Slice Theorem - 8.6 Numerical Methods - 8.7 The Hough Transform - 8.8 Non-separable Image Processing - 8.9 Summary of Important Results - Chapter 9: Diffraction Tomography - 9.1 Diffraction Tomography using CW Fields - 9.2 Pulse Mode Diffraction Tomography - 9.3 The Diffraction Slice Theorem - 9.4 Quantitative Diffraction Tomography - 9.5 EM Diffraction Tomography - 9.6 Case Study: Simulation of an Ultrasonic B-Scan - 9.7 Summary of Important Results - Chapter 10: Synthetic Aperture Imaging - 10.1 Synthetic Aperture Radar - 10.2 Principles of SAR - 10.3 Electromagnetic Scattering Model for SAR - 10.4 Case Study: The 'Sea Spikes' Problem - 10.5 Quantitative Imaging with SAR - 10.6 Synthetic Aperture Sonar - 10.