GVF-based anisotropic diffusion models

Authors: Yu, H. and Chua, C.-S.

Journal: IEEE Transactions on Image Processing

Volume: 15

Pages: 1517-1524

ISSN: 1057-7149

DOI: 10.1109/TIP.2006.871143

Abstract:

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.

https://eprints.bournemouth.ac.uk/14068/

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1632205&tag=1

Source: Manual

Preferred by: Hongchuan Yu

GVF-based anisotropic diffusion models.

Authors: Yu, H. and Chua, C.-S.

Journal: IEEE Trans. Image Process.

Volume: 15

Pages: 1517-1524

DOI: 10.1109/TIP.2006.871143

https://eprints.bournemouth.ac.uk/14068/

Source: DBLP

GVF-based anisotropic diffusion models

Authors: Yu, H. and Chua, C.-S.

Journal: IEEE Transactions on Image Processing

Volume: 15

Issue: 6

Pages: 1517-1524

ISSN: 1057-7149

Abstract:

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.

https://eprints.bournemouth.ac.uk/14068/

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1632205&tag=1

Source: BURO EPrints