Color Photo Denoising Via Hue, Saturation and Intensity Diffusion
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
On the critical point of gradient vector flow snake
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Gradient vector flow based on anisotropic diffusion
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
Fast gradient vector flow computation based on augmented Lagrangian method
Pattern Recognition Letters
Computers & Mathematics with Applications
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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.