Digital Signal & Image Processing Tutorial Skip Navigation Links.
Collapse Ch1 - Signals, Systems, and Fourier TransformCh1 - Signals, Systems, and Fourier Transform
1.0 Introduction
Collapse 1.1 Signals1.1 Signals
1.1.1 Examples of Sequences
1.1.2 Digital Images
Collapse 1.2 Systems1.2 Systems
1.2.1 Linear Systems and Shift-Invariant Systems
1.2.2 Convolution
1.2.3 Stable Systems and Special Support Systems
Collapse 1.3 The Fourier Transform1.3 The Fourier Transform
1.3.1 The Fourier Transform Pair
Expand 1.3.2 Properties1.3.2 Properties
Collapse 1.4 Additional Properties Of The Fourier Transform1.4 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
Collapse Ch2 - Image Processing BasicsCh2 - Image Processing Basics
2.0 Introduction
Collapse 2.1 Light2.1 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
Collapse 2.2 The Human Visual System2.2 The Human Visual System
2.2.1 The Eye
2.2.2 Model for Peripheral Level of Visual System
Collapse 2.3 Visual Phenomena2.3 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
Collapse 2.4 Image Processing Systems2.4 Image Processing Systems
2.4.1 Overview of an Image Processing System
2.4.2 The Digitizer
2.4.3 Display
Collapse Ch3 – Image EnhancementCh3 – Image Enhancement
3,0 Introduction
Collapse 3.1. Contrast And Dynamic Range Modification3.1. 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
Collapse 3.2. Noise Smoothing3.2. Noise Smoothing
3.2.1.Lowpass Filtering
3.2.2. Median Filtering
3.2.3. Out-Range Pixel Smoothing
Collapse 3.3. Edge Detection3.3. 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
Collapse 3.4. Image Interpolation and Motion Estimation3.4. 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