Digital Signal & Image Processing Tutorial
Ch1 - Signals, Systems, and Fourier Transform
1.0 Introduction
1.1 Signals
1.1.1 Examples of Sequences
1.1.2 Digital Images
1.2 Systems
1.2.1 Linear Systems and Shift-Invariant Systems
1.2.2 Convolution
1.2.3 Stable Systems and Special Support Systems
1.3 The Fourier Transform
1.3.1 The Fourier Transform Pair
1.3.2 Properties
Examples
1.4 Additional Properties Of The Fourier Transform
1.4.1 Signal Synthesis and Reconstruction from Phase or Magnitude
1.4.2 The Fourier Transform of Typical Images
1.4.3 The Projection-Slice Theorem
1.5 Digital Processing of Analog Signals
Ch2 - Image Processing Basics
2.0 Introduction
2.1 Light
2.1.1 Light as an Electromagnetic Wave
2.1.2 Brightness, Hue, and Saturation
2.1.3 Additive and Subtractive Color Systems
2.1.4 Representation of Monochrome and Color Images
2.2 The Human Visual System
2.2.1 The Eye
2.2.2 Model for Peripheral Level of Visual System
2.3 Visual Phenomena
2.3.1 Intensity Sensitivity
2.3.2 Adaptation
2.3.3 Mach Band Effect and Spatial Frequency Response
2.3.4 Spatial Masking
2.3.5 Other Visual Phenomena
2.4 Image Processing Systems
2.4.1 Overview of an Image Processing System
2.4.2 The Digitizer
2.4.3 Display
Ch3 – Image Enhancement
3,0 Introduction
3.1. Contrast And Dynamic Range Modification
3.1.1. Gray Scale Modification
3.1.2. Highpass Filtering and Unsharp Masking
3.1.3. Homomorphic Processing
3.1.4. Adaptive Modification of Local Contrast and Local Luminance Mean
3.2. Noise Smoothing
3.2.1.Lowpass Filtering
3.2.2. Median Filtering
3.2.3. Out-Range Pixel Smoothing
3.3. Edge Detection
3.3.1. Gradient-Based Methods
3.3.2. Laplacian-Based Methods
3.3.3. Edge Detection by Marr and Hildreth’s Method
3.3.4. Edge Detection Based on Signal Modeling
3.4. Image Interpolation and Motion Estimation
3.4.1. Spatial Interpolation
3.4.2. Motion Estimation
3.4.3. Motion-Compensated Temporal Interpolation
3.4.4. Application of Motion Estimation Methods to Spatial Interpolation
3.5. False Color and Pseudocolor
