Image Anisotropic Diffusion Based on Gradient Vector Flow Fields

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.