A Computational Introduction to Digital Image Processing: 2nd Edition (Hardback) book cover

A Computational Introduction to Digital Image Processing

2nd Edition

By Alasdair McAndrew

Chapman and Hall/CRC

535 pages | 16 Color Illus. | 388 B/W Illus.

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pub: 2015-11-05
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Description

Highly Regarded, Accessible Approach to Image Processing Using Open-Source and Commercial Software

A Computational Introduction to Digital Image Processing, Second Edition explores the nature and use of digital images and shows how they can be obtained, stored, and displayed. Taking a strictly elementary perspective, the book only covers topics that involve simple mathematics yet offer a very broad and deep introduction to the discipline.

New to the Second Edition

This second edition provides users with three different computing options. Along with MATLAB®, this edition now includes GNU Octave and Python. Users can choose the best software to fit their needs or migrate from one system to another. Programs are written as modular as possible, allowing for greater flexibility, code reuse, and conciseness. This edition also contains new images, redrawn diagrams, and new discussions of edge-preserving blurring filters, ISODATA thresholding, Radon transform, corner detection, retinex algorithm, LZW compression, and other topics.

Principles, Practices, and Programming

Based on the author’s successful image processing courses, this bestseller is suitable for classroom use or self-study. In a straightforward way, the text illustrates how to implement imaging techniques in MATLAB, GNU Octave, and Python. It includes numerous examples and exercises to give students hands-on practice with the material.

Reviews

"This textbook does an excellent job covering the basics of image processing. I highly recommend it."

—Reza Malek-Madani, Professor of Mathematics, US Naval Academy

"This book is the most concise and readable introductory text on digital image processing I have ever encountered. It provides a gentle introduction to the field with little mathematics and plenty of examples. Each topic is clearly explained and can be practiced using ready-made computer programs written in three programming languages (MATLAB, Octave, and Python)."

—Mahamed G.H. Omran, PhD, Gulf University for Science & Technology (GUST), Kuwait

Table of Contents

Introduction

Images and Pictures

What Is Image Processing?

Image Acquisition and Sampling

Images and Digital Images

Some Applications

Image Processing Operations

An Image Processing Task

Types of Digital Images

Image File Sizes

Image Perception

Images Files and File Types

Opening and Viewing Grayscale Images

RGB Images

Indexed Color Images

Numeric Types and Conversions

Image Files and Formats

Programs

Image Display

Introduction

The imshow Function

Bit Planes

Spatial Resolution

Quantization and Dithering

Programs

Point Processing

Introduction

Arithmetic Operations

Histograms

Lookup Tables

Neighborhood Processing

Introduction

Notation

Filtering in MATLAB and Octave

Filtering in Python

Frequencies; Low and High Pass Filters

Gaussian Filters

Edge Sharpening

Non-Linear Filters

Edge-Preserving Blurring Filters

Region of Interest Processing

Programs

Image Geometry

Interpolation of Data

Image Interpolation

General Interpolation

Enlargement by Spatial Filtering

Scaling Smaller

Rotation

Correcting Image Distortion

The Fourier Transform

Introduction

Background

The One-Dimensional Discrete Fourier Transform

Properties of the One-Dimensional DFT

The Two-Dimensional DFT

Experimenting with Fourier Transforms

Fourier Transforms of Synthetic Images

Filtering in the Frequency Domain

Homomorphic Filtering

Programs

Image Restoration

Introduction

Noise

Cleaning Salt and Pepper Noise

Cleaning Gaussian Noise

Removal of Periodic Noise

Inverse

Wiener Filtering

Image Segmentation

Introduction

Thresholding

Applications of Thresholding

Choosing an Appropriate Threshold Value

Adaptive Thresholding

Edge Detection

Derivatives and Edges

Second Derivatives

The Canny Edge Detector

Corner Detection

The Hough and Radon Transforms

Mathematical Morphology

Introduction

Basic Ideas

Dilation and Erosion

Opening and Closing

The Hit-or-Miss Transform

Some Morphological Algorithms

A Note on the bwmorph Function in MATLAB and Octave

Grayscale Morphology

Applications of Grayscale Morphology

Programs

Image Topology

Introduction

Neighbors and Adjacency

Paths and Components

Equivalence Relations

Component Labeling

Lookup Tables

Distances and Metrics

Skeletonization

Programs

Shapes and Boundaries

Introduction

Chain Codes and Shape Numbers

Fourier Descriptors

Color Processing

What Is Color?

Color Models

Manipulating Color Images

Pseudocoloring

Processing of Color Images

Programs

Image Coding and Compression

Lossless and Lossy Compression

Huffman Coding

Run Length Encoding

Dictionary Coding: LZW Compression

The JPEG Algorithm

Programs

Wavelets

Waves and Wavelets

A Simple Wavelet: The Haar Wavelet

Wavelets and Images

The Daubechies Wavelets

Image Compression Using Wavelets

High Pass Filtering Using Wavelets

Denoising Using Wavelets

Special Effects

Polar Coordinates

Ripple Effects

General Distortion Effects

Pixel Effects

Color Images

Appendix A: Introduction to MATLAB and Octave

Appendix B: Introduction to Python

Appendix C: The Fast Fourier Transform

Bibliography

Index

Exercises appear at the end of each chapter.

About the Author

Alasdair McAndrew is a senior lecturer and discipline leader in mathematics and physics at Victoria University in Melbourne, Australia. His teaching and research interests include image processing, cryptography, mathematics, and mathematics education. An avid technophile, he is the author of the CRC Press book Introduction to Cryptography with Open-Source Software. He holds a PhD from Monash University.

Subject Categories

BISAC Subject Codes/Headings:
COM012000
COMPUTERS / Computer Graphics
MAT013000
MATHEMATICS / Graphic Methods
TEC015000
TECHNOLOGY & ENGINEERING / Imaging Systems