Anisotropic Noise Samples

We present a practical approach to generate stochastic anisotropic samples with Poisson-disk characteristic over a two-dimensional domain. In contrast to isotropic samples, we understand anisotropic samples as non-overlapping ellipses whose size and density match a given anisotropic metric. Anisotropic noise samples are useful for many visualization and graphics applications. The spot samples can be used as input for texture generation, e.g., line integral convolution (LIC), but can also be used directly for visualization. The definition of the spot samples using a metric tensor makes them especially suitable for the visualization of tensor fields that can be translated into a metric. Our work combines ideas from sampling theory and mesh generation to approximate generalized blue noise properties. To generate these samples with the desired properties we first construct a set of non-overlapping ellipses whose distribution closely matches the underlying metric. This set of samples is use...

• Type: Journal
• Year: 2008
• Where: TVCG
• Authors: Louis Feng, Ingrid Hotz, Bernd Hamann, Kenneth I. Joy
• Keywords: Anisotropic, Anisotropic Samples, Stochastic Anisotropic Samples, TVCG 2008