On the impact of anisotropic diffusion on edge detection

Content-aware, edge-preserving smoothing techniques have gained visibility in recent years. However, they have had a rather limited impact on the edge detection literature compared to content-unaware (linear) techniques, often based on Gaussian filters. In this work, we focus on Anisotropic Diffusion, covering its initial definition by Perona and Malik and subsequent extensions. A visual case study is used to illustrate their features. We perform a quantitative evaluation of the performance of the Canny method for edge detection when substituting linear Gaussian smoothing filters by Anisotropic Diffusion. HighlightsReviewing the main trends in Anisotropic Diffusion.Identifying the practical scenarios on which Anisotropic Diffusion fails.Quantifying the improvement of edge detection when Anisitropic Diffusion is applied.

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