The anisotropic Kuwahara filter is an edge-preserving filter that is especially useful for creating stylized abstractions from images or videos. It is based on a generalization of the Kuwahara filter that is adapted to the local structure of image features. In this work, two limitations of the anisotropic Kuwahara filter are addressed. First, it is shown that by adding thresholding to the weighting term computation of the sectors, artifacts are avoided and smooth results in noise-corrupted regions are achieved. Second, a multi-scale computation scheme is proposed that simultaneously propagates local orientation estimates and filtering results up a low-pass filtered pyramid. This allows for a strong abstraction effect and avoids artifacts in large low-contrast regions. The propagation is controlled by the local variances and anisotropies that are derived during the computation without extra overhead, resulting in a highly efficient scheme that is particularly suitable for real-time processing on a GPU.
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