Yu, H. and Chua, C.-s., 2004. Image Anisotropic Diffusion Based on Gradient Vector Flow Fields. In: Computer Vision - ECCV 2004. Berlin / Heidelberg: Springer, pp. 288-301.
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Official URL: http://www.springerlink.com/content/f5ph3vwarardaa...
DOI: 10.1007/b97871
Abstract
In this paper, the gradient vector flow fields are introduced in the image anisotropic diffusion, and the shock filter, mean curvature flow and Perona-Malik equation are reformulated respectively in the context of this flow fields. Many advantages over the original models can be obtained, such as numerical stability, a large capture range, and computational simplification etc. In addition, the fairing process is introduced in the anisotropic diffusion, which contains the fourth order derivative and is reformulated as the intrinsic Laplacian of curvature under the level set framework. By this fairing process, the boundaries of shape will become more outstanding. In order to overcome numerical errors, the intrinsic Laplacian of curvature is computed from the gradient vector flow fields, but not directly from the observed images.
| Item Type: | Book Section |
|---|---|
| ISBN: | 978-3-540-21982-8 |
| Series Name: | Lecture Notes in Computer Science |
| Number: | 3023 |
| Number of Pages: | 288 |
| Series Name: | Lecture Notes in Computer Science |
| Additional Information: | 8th European Conference on Computer Vision, Prague, Czech Republic, 11-14 May 2004. Proceedings, Part III |
| Subjects: | Generalities > Computer Science and Informatics |
| Group: | Media School > National Centre for Computer Animation |
| ID Code: | 14716 |
| Deposited By: | Mr Hongchuan Yu |
| Deposited On: | 21 May 2010 12:15 |
| Last Modified: | 07 Mar 2013 15:29 |
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