Jan Eric Kyprianidis1 Henry Kang2 Jürgen Döllner1
1Hasso-Plattner-Institut, Germany
2University of Missouri, St. Louis, USA
Poster at 7th Symposium on Non-Photorealistic Animation and Rendering (NPAR), 2008
We present a generalization of the Kuwahara filter that avoids clustering artifacts by adapting shape, scale and orientation of the filter to the local structure of the input. Due to this adaption of the filter to the local structure, directional image features are better preserved and emphasized. This results in overall sharper edges and a more feature-abiding painterly effect. Local orientation and a measure for the anisotropy are derived from the eigenvalues and eigenvectors of the smoothed structure tensor. Then structure-aware smoothing is performed using a novel nonlinear filter. This nonlinear filter uses weighting functions defined over sectors of an ellipse whose shape is based on the local orientation and anisotropy. The filter response is defined as a weighed sum of the local averages where more weight is given to those averages with low standard deviation. Our approach shows excellent temporal coherence without requiring expensive video motion estimation. Implemented on the GPU the algorithm processes video in real-time.
Kyprianidis, J. E., Kang, H., & Döllner, J. (2009). Image and Video Abstraction by Anisotropic Kuwahara Filtering. Poster at 7th Symposium on Non-Photorealistic Animation and Rendering (NPAR).
@INPROCEEDINGS{ kyprianidis-npar2009, author = { Kyprianidis, Jan Eric and Kang, Henry, D{\"o}llner, J{\"u}rgen}, title = { Image and Video Abstraction by Anisotropic Kuwahara Filtering }, booktitle = { Poster at 7th Symposium on Non-Photorealistic Animation and Rendering (NPAR) }, year = { 2009 } }