Textbook in PDF format

The aim of this book is to concentrate on the fundamental principles and techniques of image processing. A conscious attempt has been made to give an in-depth presentation of selected topics, rather than a comprehensive survey of the entire field. Implementation of the various image processing algorithms is an important step in learning the subject. The author has come to realise that using a package like MatLAB (which has an image processing toolbox) quickens the learning process. While programming in a language like C has certain advantages, it is a time consuming process. The beginner is likely to be mired in syntax errors and the complexities of the programming language. This leaves the student less time to understand the algorithm being used. Two separate chapters have been devoted to the MatLAB programming environment and the image processing toolbox. Implementation of image processing algorithms using MatLAB is also emphasised in other chapters wherever it is considered appropriate. Students are encouraged to run the programs discussed in this book and also to write their own code. Your appreciation of image processing will be enhanced if you write your own programs. This book can be easily covered in a single semester. It is hoped that this book will be useful for beginners and those who want to brush up the basics of this subject. Every chapter is accompanied by a collection of exercises and programming assignments. Working through these exercises will help the student to sharpen his/her understanding of the subject. Hints and answers to these exercises are provided at the back to help the student whenever he gets stuck in a particular problem. However, he/she has to use these as a last resort!
This second edition includes important updates to the first edition, as well as two entirely new chapters, making the book ideal for advanced students in physics and engineering.
Preface.
Acknowledgements.
Author biography.
Introduction.
Image enhancement in the spatial domain.
Filtering in the Fourier domain.
Image compression.
Image analysis and object recognition.
Image restoration.
Wavelets.
Color image processing.
Introduction to MatLAB.
The image processing toolbox.
Video processing.
Applications of machine learning.
Error correcting codes and cryptography.
Solutions to selected exercises