Approximate Separable 3D Anisotropic Gauss Filter

Oliver Wirjadi, Thomas Breuel
Proc. IEEE International Conference on Image Processing (ICIP 2005) volume II, Pages 149-152, Genova, IEEE, Genova, Italy, 9/2005

Abstract:

Anisotropic Gaussian filters are useful for adaptive smoothing and feature extraction. In our application, micro - tomographic images of fibers were smoothed by anisotropic Gaussians. In this case, this is more natural than using their isotropic counterparts. But filtering in large 3D data is very time consuming. We extend the work of Geusebroek et al. on fast Gauss filtering to three dimensions. We propose an approximate separable filtering scheme which consists of three 1D convolutions. Initial experiments suggest that this filter can outperform an FFT based implementation when the kernel size is small compared to the size of the 3D images.

Files:

  WirjadiBreuelSep3DAniGaussFilt.pdf

BibTex:

@inproceedings{ WIRJ2005,
	Title = {Approximate Separable 3D Anisotropic Gauss Filter},
	Author = {Oliver Wirjadi and Thomas Breuel},
	BookTitle = {Proc. IEEE International Conference on Image Processing (ICIP 2005)},
	Month = {9},
	Year = {2005},
	Publisher = {IEEE},
	Publisher = {II},
	Pages = {149-152},
	Address = {Genova, Italy}
}

     
Last modified:: 30.08.2016