Introduction to Digital Image Processing  book cover
1st Edition

Introduction to Digital Image Processing

ISBN 9781482216691
Published September 13, 2013 by CRC Press
756 Pages - 371 B/W Illustrations

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Book Description

The subject of digital image processing has migrated from a graduate to a junior or senior level course as students become more proficient in mathematical background earlier in their college education. With that in mind, Introduction to Digital Image Processing is simpler in terms of mathematical derivations and eliminates derivations of advanced subjects. Most importantly, the textbook contains an extensive set of programming exercises for students.

The textbook examines the basic technologies needed to support image processing applications, including the characterization of continuous images, image sampling and quantization techniques, and two-dimensional signal processing techniques. It then covers the two principle areas of image processing: image enhancement and restoration techniques and extraction of information from an image. It concludes with discussions of image and video compression.

  • Covers the mathematical representation of continuous images and discrete images
  • Discusses the psychophysical properties of human vision
  • Analyzes and compares linear processing techniques implemented by direct convolution and Fourier domain filtering
  • Details restoration models, point and spatial restoration and geometrical image modification
  • Includes morphological image processing, edge detection, image feature extraction, image segmentation, object shape analysis, and object detection
  • Describes coding technique applicable to still image and video coding based upon point and spatial processing
  • Outlines the widely adopted JPEG and MPEG still image and video coding standards

The author’s accessible style provides historical background on the development of image processing techniques as well as a theoretical exposition. The inclusion of numerous exercises fully prepares students for further study.

Table of Contents

Continuous Image Mathematical Characterization
Image Representation
Two-Dimensional Systems
Two-Dimensional Fourier Transform
Image Stochastic Characterization

Psychophysical Vision Properties
Light Perception
Eye Physiology
Visual Phenomena
Monochrome Vision Model
Color Vision Model

Photometry and Colorimetry
Color Matching
Colorimetry Concepts
Color Spaces

Image Sampling and Reconstruction
Image Sampling and Reconstruction Concepts
Monochrome Image Sampling Systems
Monochrome Image Reconstruction Systems
Color Image Sampling Systems

Image Quantization
Scalar Quantization
Processing Quantized Variables
Monochrome and Color Image Quantization

Discrete Image Mathematical Characterization
Vector-Space Image Representation
Generalized Two-Dimensional Linear Operator
Image Statistical Characterization
Image Probability Density Models
Linear Operator Statistical Representation

Superposition and Convolution
Finite-Area Superposition and Convolution
Sampled Image Superposition and Convolution
Circulant Superposition and Convolution
Superposition and Convolution Operator Relationships

Unitary and Wavelet Transforms
General Unitary Transforms
Fourier Transform,
Cosine, Sine, and Hartley Transforms
Hadamard, Haar, and Daubechies Transforms
Karhunen–Loeve Transform
Wavelet Transforms

Linear Processing Techniques
Transform Domain
Transform Domain Superposition
Fast Fourier Transform Convolution
Fourier Transform Filtering

Image Enhancement
Contrast Manipulation
Histogram Modification
Noise Cleaning
Edge Crispening
Color Image Enhancement
Multispectral Image Enhancement

Image Restoration
Image Restoration Models
Sensor and Display Point Nonlinearity Correction
Continuous Image Spatial Filtering Restoration
Pseudoinverse Spatial Image Restoration
Statistical Estimation Spatial Image Restoration
Multi-Plane Image Restoration

Geometrical Image Modification
Basic Geometrical Methods
Spatial Warping
Geometrical Image Resampling

Morphological Image Processing
Binary Image Connectivity
Binary Image Hit or Miss Transformations
Binary Image Shrinking, Thinning, Skeletonizing, and Thickening
Binary Image Generalized Dilation and Erosion
Binary Image Close and Open Operations
Gray Scale Image Morphological Operations

Edge Detection
Edge, Line, and Spot Models
First-Order Derivative Edge Detection
Second-Order Derivative Edge Detection
Edge-Fitting Edge Detection
Luminance Edge Detector Performance
Color Edge Detection
Line and Spot Detection

Image Feature Extraction
Image Features Evaluation
Amplitude Features
Transform Coefficient Features
Texture Characterization
Texture Features
Scale-Invariant Features

Image Segmentation
Amplitude Segmentation
Clustering Segmentation
Region Segmentation
Boundary Segmentation
Texture Segmentation
Segment Labeling

Shape Analysis
Topological Attributes
Distance, Perimeter, and Area Measurements
Spatial Moments
Shape Orientation Descriptors
Fourier Descriptors
Thinning and Skeletonizing

Image Detection and Registration
Template Matching
Matched Filtering of Continuous Images
Image Registration

Point Processing Image Compression
Pulse Code Modulation Coding of Monochrome Images
Statistical Coding of Monochrome Images
Predictive Coding of Monochrome Images
Point Processing Color Image Coding
JPEG Lossless Image Coding

Spatial Processing Image Compression
Run Coding of Monochrome Images
Interpolation Coding of Monochrome Images
Unitary Transform Coding of Monochrome Images
Wavelet Coding of Monochrome Images
Spatial Processing Color Image Coding
JPEG Baseline Image Coding Standard
JPEG2000 Image Coding Standard

Video Compression
Spatial Video Coding Techniques
Spatial/Temporal Video Coding Techniques
MPEG - 1 Video Coding Standard
MPEG - 2 Video Coding Standard
MPEG - 4 Video Coding Standards





Exercises appear at the end of each chapter.

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