Image Abstraction by Structure Adaptive Filtering

Abstract

Photorealistic visualizations used in 3D applications designed for typical desktops usually show high visual information density. We present non-photorealistic image processing techniques to distill the perceptually important information and optimize the content for the limited screen space of small displays. Our method extends the approach of [Winnemöller et al. 2006] to use iterated bilateral filtering for abstraction and difference-of-Gaussians (DoG) for edge extraction by adapting it to the local orientation of the input.

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Citation

Kyprianidis, J. E., & Döllner, J. (2008). Image Abstraction by Structure Adaptive Filtering. Poster at 6th Symposium on Non-Photorealistic Animation and Rendering (NPAR).

@INPROCEEDINGS{ kyprianidis-npar2008,
  author     = { Kyprianidis, Jan Eric and D{\"o}llner, J{\"u}rgen},
  title      = { Image Abstraction by Structure Adaptive Filtering },
  booktitle  = { Poster at 6th Symposium on Non-Photorealistic Animation and Rendering (NPAR) },
  year       = { 2008 }
}

Related

• Kyprianidis, J. E. & Döllner, J. (2008). Image Abstraction by Structure Adaptive Filtering. In: Proc. EG UK Theory and Practice of Computer Graphics, pp. 51–58.
• Kyprianidis, J. E. & Döllner, J. (2009). Real-Time Image Abstraction by Directed Filtering. In: W. Engel (Ed.), ShaderX7 - Advanced Rendering Techniques. Charles River Media, pp. 285–302.