Image Processing Fundamentals

Contents

1. Introduction
2. Digital Image Definitions
1. Common Values
2. Characteristics of Image Operations

Types of operations

Types of neighborhoods

3. Video Parameters
2. Tools
1. Convolution
2. Properties of Convolution
3. Fourier Transforms
4. Properties of Fourier Transforms

Importance of phase and magnitude

Circularly symmetric signals

Examples of 2D signals and transforms

5. Statistics

Probability distribution function of the brightnesses

Probability density function of the brightnesses

Average

Standard deviation

Coefficient-of-variation

Percentiles

Mode

SignaltoNoise ratio

6. Contour Representations

Chain code

Chain code properties

Crack code

Run codes

4. Perception
1. Brightness Sensitivity

Wavelength sensitivity

Stimulus sensitivity

2. Spatial Frequency Sensitivity
3. Color Sensitivity

Standard observer

CIE chromaticity coordinates

4. Optical Illusions
4. Image Sampling
1. Sampling Density for Image Processing

Sampling aperture

2. Sampling Density for Image Analysis

Sampling for area measurements

Sampling for length measurements

Conclusions on sampling

6. Noise
1. Photon Noise
2. Thermal Noise
3. On-chip Electronic Noise
4. KTC Noise
5. Amplifier Noise
6. Quantization Noise
7. Cameras
1. Linearity
2. Sensitivity

Absolute sensitivity

Relative sensitivity

3. SNR

Thermal noise (Dark current)

Photon noise

4. Shading
5. Pixel Form

Square pixels

Fill factor

6. Spectral Sensitivity
7. Shutter Speeds (Integration Time)

Video cameras

Scientific cameras

8. Readout Rate
7. Displays
1. Refresh Rate
2. Interlacing
3. Resolution
8. Algorithms
1. Histogram-based Operations

Contrast stretching

Equalization

Other histogram-based operations

2. Mathematics-based Operations

Binary operations

Arithmetic-based operations

3. Convolution-based Operations

Background

Convolution in the spatial domain

Convolution in the frequency domain

4. Smoothing Operations

Linear Filters

Non-Linear Filters

Summary of Smoothing Algorithms

5. Derivative-based Operations

First Derivatives

Second Derivatives

Other Filters

6. Morphology-based Operations

Fundamental definitions

Dilation and Erosion

Boolean Convolution

Opening and Closing

itandMiss operation

Summary of the basic operations

Skeleton

Propagation

Summary of skeleton and propagation

Gray-value morphological processing

Morphological smoothing

Morphological gradient

Morphological Laplacian

Summary of morphological filters

10. Techniques
1. Shading Correction

Model of shading

Estimate of shading

2. Basic Enhancement and Restoration Techniques

Unsharp masking

Noise suppression

Distortion suppression

3. Segmentation

Thresholding

Edge finding

Binary mathematical morphology

Gray-value mathematical morphology

Acknowledgments

References

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