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Adaptive Incremental Stippling using the Poisson-Disk Distribution

Abstract Recently efficient algorithms have been published for generating large point sets with Poisson-disk distribution. With their blue noise spectral characteristics, Poisson-disk distributions are considered to produce visually pleasing patterns. Some applications, e.g., non photo-realistic rendering (NPR), require, in addition to efficiency, the production of aesthetically pleasing point sets adapted to an arbitrary image or function. We present a novel linear order stippling method that generates a set of points with Poisson-disk distribution adapted to arbitrary images and compare this method with existing methods using two quantitative evaluation metrics, radial mean and anisotropy, to assess the technique.