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Multiple kernels noise for improved procedural texturing

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Abstract

Procedural texturing is a well known method to synthesize details onto virtual surfaces directly during rendering. But the creation of such textures is often a long and painstaking task. This paper introduces a new noise function, called multiple kernels noise. It is characterized by an arbitrary energy distribution in spectral domain. Multiple kernels noise is obtained by adaptively decomposing a user-defined power spectral density (PSD) into rectangular regions. These are then associated to kernel functions used to compute noise values by sparse convolution. We show how multiple kernels noise (1) increases the variety of noisy procedural textures that can be modeled and (2) helps creating structured procedural textures by automatic extraction of noise characteristics from user-supplied samples.

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Authors and Affiliations

  1. XLIM, University of Limoges, 123 Avenue Albert Thomas, 87000, Limoges, France

    G. Gilet & D. Ghazanfarpour

  2. LSIIT, University of Strasbourg, 11, Bd Sebastien Brandt, 67000, Illkirch Grafenstaden, France

    J-M. Dischler

Authors
  1. G. Gilet
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  2. J-M. Dischler
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  3. D. Ghazanfarpour
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Correspondence to G. Gilet.

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Gilet, G., Dischler, JM. & Ghazanfarpour, D. Multiple kernels noise for improved procedural texturing. Vis Comput 28, 679–689 (2012). https://doi.org/10.1007/s00371-012-0711-2

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  • DOI: https://doi.org/10.1007/s00371-012-0711-2

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