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This is an implementation of fast bilateral filtering for 3D images. This filter smoothes the image while preserving edges, but in its most straightforward implementation is very computationally demanding, especially with large 3D images. Fast bilateral filtering (S. Paris and F. Durand, MIT[1]) is an approximation technique which drastically improves the speed of computation. My implementation closely follows the Matlab version of the fast 2D filter[2] with some modifications.
The core function allows to control all of the parameters of the filter (4 for the Gaussian kernel, 4 for the subsampling), and a wrapper function makes some simplifications for ease of use.
To perform the separable 4D convolution, I used my own function submitted separately to File Exchange (27957).
[1] http://people.csail.mit.edu/sparis/bf/
[2] http://people.csail.mit.edu/jiawen/software/bilateralFilter.m
Citation pour cette source
Igor Solovey (2026). Fast Bilateral Filter for 3D Images (https://fr.mathworks.com/matlabcentral/fileexchange/30833-fast-bilateral-filter-for-3d-images), MATLAB Central File Exchange. Extrait(e) le .
Remerciements
Inspiré par : Separable N-Dimensional Convolution
Informations générales
- Version 1.1.0.0 (718 ko)
Compatibilité avec les versions de MATLAB
- Compatible avec toutes les versions
Plateformes compatibles
- Windows
- macOS
- Linux
| Version | Publié le | Notes de version | Action |
|---|---|---|---|
| 1.1.0.0 | Removed dependency on the Statistics Toolbox (range.m). |
||
| 1.0.0.0 |
