# Neighborhood / cutoff distance of smoothing with itkSmoothingRecursiveGaussianImageFilter

**URL:** <https://discourse.itk.org/t/neighborhood-cutoff-distance-of-smoothing-with-itksmoothingrecursivegaussianimagefilter/1570>\
**Category:** Algorithms\
**Created:** [January 31, 2019, 4:04pm UTC](https://discourse.itk.org/t/neighborhood-cutoff-distance-of-smoothing-with-itksmoothingrecursivegaussianimagefilter/1570 "2019-01-31T16:04:43Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![cookpa](https://discourse.itk.org/user_avatar/discourse.itk.org/cookpa/32/255_2.png) [@cookpa](https://discourse.itk.org/u/cookpa)\
**Post date:** [January 31, 2019, 4:04pm UTC](https://discourse.itk.org/t/neighborhood-cutoff-distance-of-smoothing-with-itksmoothingrecursivegaussianimagefilter/1570/1 "2019-01-31T16:04:43Z")

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In the itkGaussianInterpolateImageFunction filter, we set sigma, the standard deviation of the Gaussian smoothing and alpha, the cutoff distance from the center voxel, over which the kernel is sampled.

Is there an equivalent parameter to alpha for itkSmoothingRecursiveGaussianImageFilter?

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**Author:** ![blowekamp](https://discourse.itk.org/user_avatar/discourse.itk.org/blowekamp/32/79_2.png) [@blowekamp](https://discourse.itk.org/u/blowekamp)\
**Post date:** [January 31, 2019, 4:20pm UTC](https://discourse.itk.org/t/neighborhood-cutoff-distance-of-smoothing-with-itksmoothingrecursivegaussianimagefilter/1570/2 "2019-01-31T16:20:04Z")

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The implementations of the Gaussian smoothing is done quite differently. The Gaussian interpolator uses a N-D weighted region to perform the convolution. This is similar to the [DiscreteGaussianImageFilter](https://itk.org/Doxygen/html/classitk_1_1DiscreteGaussianImageFilter.html), which has a similar a `MaximumError` and `MaximumKernelWidth`. The convolution will be done with N separated 1-D kernels.

The recursive Gaussian filters use a… recursive algorithm which does a 1-D forward processed to imaginary space, and a backwards processing step. The result is closer to “infinite” support of an approximation to a Gaussian. The [doxygen](https://itk.org/Doxygen/html/classitk_1_1RecursiveGaussianImageFilter.html) has some links to some papers, but you may find other interesting reads about recursive Gaussian implementations other places.

Here is another recursive implementation available as a remote module: [http://www.insight-journal.org/browse/publication/896](http://www.insight-journal.org/browse/publication/896)

To answer your questions: no.

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**Author:** ![cookpa](https://discourse.itk.org/user_avatar/discourse.itk.org/cookpa/32/255_2.png) [@cookpa](https://discourse.itk.org/u/cookpa)\
**Post date:** [February 6, 2019, 9:06pm UTC](https://discourse.itk.org/t/neighborhood-cutoff-distance-of-smoothing-with-itksmoothingrecursivegaussianimagefilter/1570/3 "2019-02-06T21:06:39Z")

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Thanks @blowekamp.