gaussianSmooth {mmand} | R Documentation |
Smooth a numeric array with a Gaussian kernel
Description
This function smoothes an array using a Gaussian kernel with a specified standard deviation.
Usage
gaussianSmooth(x, sigma)
Arguments
x |
An object that can be coerced to an array, or for which a
|
sigma |
A numeric vector giving the standard deviation of the kernel in each dimension. Can have lower dimensionality than the target array. |
Details
This implementation takes advantage of the separability of the Gaussian kernel for speed when working in multiple dimensions. It is therefore equivalent to, but much faster than, directly applying a multidimensional kernel.
Value
A morphed array with the same dimensions as the original array.
Author(s)
Jon Clayden <code@clayden.org>
See Also
morph
for the function underlying this operation,
gaussianKernel
for generating Gaussian kernels (which is
also used by this function), and erode
for mathematical
morphology functions.