Geometric Partial Differential Equations and Image Analysis
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- Author: Guillermo Sapiro, University of Minnesota
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This book provides an introduction to the use of geometric partial differential equations in image processing and computer vision. It 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. Applications covered include image segmentation, shape analysis, image enhancement, and tracking. The volume provides information for people investigating new solutions to image processing problems as well as for people searching for existent advanced solutions.Read more
- 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 ReviewSee more reviews
"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
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- Date Published: February 2011
- format: Adobe eBook Reader
- isbn: 9780511836770
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
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.
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