Geometric Partial Differential Equations and Image Analysis
This book provides an introduction to the use of geometric partial differential equations in image processing and computer vision. This research area brings a number of new concepts into the field, providing a very fundamental and formal approach to image processing. State-of-the-art practical results in a large number of real problems are achieved with the techniques described in this book. Applications covered include image segmentation, shape analysis, image enhancement, and tracking. This book will be a useful resource for researchers and practitioners. It is intended to provide information for people investigating new solutions to image processing problems as well as for people searching for existent advanced solutions.
- Covers both theory and applications, with a good coverage of the state-of-the-art literature
- First to cover many aspects of the topic, not just the numerical or filtering component
- Useful resource both for experts and newcomers into the field
Reviews & endorsements
"...enjoyable to read...an excellent introduction for someone interested in pursuing research in this area, with ample references to current work sprinkled throughout." SIAM Review
"I think that every person interested in image analysis by partial differential equations or related fields, such as differential geometry and curve evolution, should read this book." Mathematics of Computation
Product details
February 2006Paperback
9780521685078
412 pages
229 × 154 × 21 mm
0.55kg
Available
Table of Contents
- 1. Basic mathematical background
- 2. Geometric curve and surface evolution
- 3. Geodesic curves and minimal surfaces
- 4. Geometric diffusion of scalar images
- 5. Geometric diffusion of vector valued images
- 6. Diffusion on non-flat manifolds
- 7. Contrast enhancement
- 8. Additional theories and applications.