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Image and Video-Based Artistic Stylisation pp 77–101Cite as

Artistic Stylization by Nonlinear Filtering

Part of the Computational Imaging and Vision book series (CIVI,volume 42)

Abstract

Image processing techniques that perform local filtering operations provide an interesting alternative to other classical techniques, such as stroke-based rendering or segmentation-based approaches. In this chapter, several popular approaches developed in the previous years are reviewed. Among these are approaches based on the bilateral filter, the difference of Gaussians filter, and the Kuwahara filter, as well as approaches that combine diffusion with shock filtering. In addition, a brief introduction to approaches based on morphological filtering and techniques working in the gradient domain is given. Besides discussing isotropic approaches, a focus is placed on anisotropic generalizations that take the local structure into account. These typically create a strong artistic look by enhancing and exaggerating directional image features.

Keywords

  • Partial Differential Equation
  • Bilateral Filter
  • Canny Edge Detector
  • Gradient Domain
  • Line Integral Convolution

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  1. Hasso-Plattner-Institut, University of Potsdam, Potsdam, Germany

    Jan Eric Kyprianidis

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  1. School of Computer Science & Informatics, Cardiff University, The Parade, Roath 5, Cardiff, CF24 3AA, United Kingdom

    Paul Rosin

  2. Centre for Vision Speech & Signal Proc., University of Surrey, Guildford, GU2 7XH, Surrey, United Kingdom

    John Collomosse

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Kyprianidis, J.E. (2013). Artistic Stylization by Nonlinear Filtering. In: Rosin, P., Collomosse, J. (eds) Image and Video-Based Artistic Stylisation. Computational Imaging and Vision, vol 42. Springer, London. https://doi.org/10.1007/978-1-4471-4519-6_5

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