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GVF-based anisotropic diffusion models.

Yu, H. and Chua, C.-s., 2006. GVF-based anisotropic diffusion models. IEEE Transactions on Image Processing, 15 (6), 1517-1524.

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IEEETIP06-proof.pdf - Published Version


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DOI: 10.1109/TIP.2006.871143


In this paper, the gradient vector flow fields are introduced in image restoration. Within the context of flow fields, the shock filter, mean curvature flow, and Perona-Malik equation are reformulated. Many advantages over the original models can be obtained; these include numerical stability, large capture range, and high-order derivative estimation. In addition, a fairing process is introduced in the anisotropic diffusion, which contains a fourth-order derivative and is reformulated as the intrinsic Laplacian of curvature under the level set framework. By applying this fairing process, the shape boundaries will become more apparent. In order to overcome numerical errors, the intrinsic Laplacian of curvature is computed from the gradient vector flow fields instead of the observed images.

Item Type:Article
Uncontrolled Keywords:Anisotropic diffusion models; Gradient vector flow (GVF) fields; Intrinsic laplacian of curvature
Group:Faculty of Media & Communication
ID Code:14068
Deposited By: Mr Hongchuan Yu
Deposited On:29 Apr 2010 18:22
Last Modified:14 Mar 2022 13:30


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