A Texton for Fast and Flexible Gaussian Texture Synthesis

Abstract : Gaussian textures can be easily simulated by convolving an initial image sample with a conveniently normalized white noise. However, this procedure is not very flexible (it does not allow for non-uniform grids in particular), and can become computationally heavy for large domains. We here propose an algorithm that summarizes a texture sample into a synthesis-oriented texton, that is, a small image for which the discrete spot noise simulation (summed and normalized randomly-shifted copies of the texton) is more efficient than the classical convolution algorithm. Using this synthesis-oriented texture summary, Gaussian textures can be generated in a faster, simpler, and more flexible way.
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Bruno Galerne, Arthur Leclaire, Lionel Moisan. A Texton for Fast and Flexible Gaussian Texture Synthesis. European Signal Processing Conference, Sep 2014, Lisbon, Portugal. pp. 1686-1690. ⟨hal-00957746⟩

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