Mathematics of Digital Images
Mathematics of Digital Images
$105.00
USDCompression, restoration and recognition are three of the key components of digital imaging. The mathematics needed to understand and carry out all these components are explained here in a style that is at once rigorous and practical with many worked examples, exercises with solutions, pseudocode, and sample calculations on images. The introduction lists fast tracks to special topics such as Principal Component Analysis, and ways into and through the book, which abounds with illustrations. The first part describes plane geometry and pattern-generating symmetries, along with some on 3D rotation and reflection matrices. Subsequent chapters cover vectors, matrices and probability. These are applied to simulation, Bayesian methods, Shannon's information theory, compression, filtering and tomography. The book will be suited for advanced courses or for self-study. It will appeal to all those working in biomedical imaging and diagnosis, computer graphics, machine vision, remote sensing, image processing and information theory and its applications.
- Written to be understood not only by engineers but by all concerned with digital image issues
- Builds up the required probability and information theory from scratch
- Draws on material from author's successful earlier book
Reviews & endorsements
"Recognition explains the mathematics needed to carry out various aspects of digital imaging through examples, exercises with solutions, pseudocode and sample calculations on images. Suitable for a course or tutorial."
Spectra
"This book explains the mathematics needed to understand and carry out these components in a style at once rigorous and practical, with many worked examples, exercises and solutions, pseudocode, and sample calculations on images."
Bookshelf
"The writing style, editing and figures and overall presentation are excellent. I found it a pleasure to read and will keep it handy as a reference book. This is a book that I would have found extremely useful at the start of my PhD, and I would recommend it particularly for graduate students who need a robust reference on mathematical foundations."
Jason Dowling
IAPR Newsletter
"...offers both theory and practical applications and exercises. College-level courses will want to consider this as a classroom text on the subject, but specialty libraries will also find it a popular pick for advanced self-study."
California Bookwatch
Diane C. Donovan, Midwest Book Review
"The strength of this book is the substantial background material that is required to understand modern image processing techniques. ...I found this book to be a useful reference tool for those wanting to understand basic image processing techniques. It is clearly written and easy to follow."
David Chop
Northwestern University
"...Recommended as a textbook for courses or for self-study."
Agnieszka Lisowska
Product details
December 2007Adobe eBook Reader
9780511345579
0 pages
0kg
30 b/w illus. 20 tables 125 exercises
This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
- Introduction
- 1. Isometries
- 2. How isometries combine
- 3. The braid patterns
- 4. Plane patterns and symmetries
- 5. The 17 plane patterns
- 6. More plane truth
- 7. Vectors and matrices
- 8. Matrix algebra
- 9. Probability
- 10. Random vectors
- 11. Sampling and inference
- 12. Entropy and coding
- 13. Information and error-correction
- 14. The Fourier transform
- 15. Transforming images
- 16. Scaling
- 17. B-spline wavelets
- 18. Further methods
- References
- Symbols
- Selected answers
- Index.
