An improved stopping criterion for anisotropic diffusion
Maryam Khanian, Michael Breuß, Ali Davari · AIP conference proceedings · 2015
Anisotropic diffusion is a time-dependent process in image processing useful for denoising and related tasks. Applied at an input image, the latter is gradually simplified in such a way that edges tend to be preserved. Meaningful image structures can then be detected depending on the diffusion time and the spatial scale of a structure. One of the most important points in anisotropic diffusion filtering is introducing a stopping criterion for the time evolution as this defines the quality of output images. In this paper, we follow the approach of a recent method by Ilyevsky and Turkel for determining a useful stopping time. While following the same basic idea, we simplify the underlying algorithm and improve at the same time the quality of filtering results significantly. The superiority of our scheme is validated by several numerical experiments with standard test images in the field.