Two-Dimensional Wavelets and their Relatives
Two-dimensional wavelets offer a number of advantages over discrete wavelet transforms when processing rapidly varying functions and signals. In particular, they offer benefits for real-time applications such as medical imaging, fluid dynamics, shape recognition, image enhancement and target tracking. This book introduces the reader to 2-D wavelets via 1-D continuous wavelet transforms, and includes a long list of useful applications. The authors then describe in detail the underlying mathematics before moving on to more advanced topics such as matrix geometry of wavelet analysis, three-dimensional wavelets and wavelets on a sphere. Throughout the book, practical applications and illustrative examples are used extensively, ensuring the book's value to engineers, physicists and mathematicians alike.
- The first of its kind in print dealing with the two - and higher - dimensional continuous wavelet transforms, with extensive examples of applications
- Gradual introduction of the underlying mathematical tools, with very few prerequisites, yet leading the reader to the research frontier
- Covers both the continuous and the discrete wavelet transforms
Reviews & endorsements
Review of the hardback: 'This book is of great interest to anyone working in 2-d CWT and their applications.' Zentralblatt MATH
Product details
June 2008Paperback
9780521065191
480 pages
246 × 187 × 29 mm
0.87kg
134 b/w illus. 3 tables
Available
Table of Contents
- Prologue
- 1. Warm-up: the 1-D continuous wavelet transform
- 2. The 2-D continuous wavelet transform
- 3. Some 2-D wavelets and their performances
- 4. Applications of the 2-D CWT I. Image processing
- 5. Applications of the 2-D CWT II. Physical applications
- 6. Matrix geometry of wavelet analysis I
- 7. Matrix geometry of wavelet analysis II
- 8. Minimal uncertainty and Wigner transformations
- 9. Higher-dimensional wavelets
- 10. Spatio-temporal wavelets and motion estimation
- 11. Beyond wavelets
- Epilogue
- Appendix 1
- Bibliography
- Index.