Digital Image Processimg

Image Processing Fundamentals - Contents

Introduction

Digital Image Definitions

Common Values

Characteristics of Image Operations

Types of operations

Types of neighborhoods

Video Parameters

Tools

Convolution

Properties of Convolution

Fourier Transforms

Properties of Fourier Transforms

Importance of phase and magnitude

Circularly symmetric signals

Examples of 2D signals and transforms

Statistics

Probability distribution function of the brightnesses

Probability density function of the brightnesses

Average

Standard deviation

Coefficient-of-variation

Percentiles

Mode

SignaltoNoise ratio

Contour Representations

Chain code

Chain code properties

Crack code

Run codes

Perception

Brightness Sensitivity

Wavelength sensitivity

Stimulus sensitivity

Spatial Frequency Sensitivity

Color Sensitivity

Standard observer

CIE chromaticity coordinates

Optical Illusions

Image Sampling

Sampling Density for Image Processing

Sampling aperture

Sampling Density for Image Analysis

Sampling for area measurements

Sampling for length measurements

Conclusions on sampling

Noise

Photon Noise

Thermal Noise

On-chip Electronic Noise

KTC Noise

Amplifier Noise

Quantization Noise

Cameras

Linearity

Sensitivity

Absolute sensitivity

Relative sensitivity

SNR

Thermal noise (Dark current)

Photon noise

Shading

Pixel Form

Square pixels

Fill factor

Spectral Sensitivity

Shutter Speeds (Integration Time)

Video cameras

Scientific cameras

Readout Rate

Displays

Refresh Rate

Interlacing

Resolution

Algorithms

Histogram-based Operations

Contrast

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