gaussKernel: 1 dimensional Gaussian smoothing kernel
In FIACH: Retrospective Noise Control for fMRI
Description
Usage
Arguments
Value
Examples
Description
This function produces a Gaussian smoothing kernel that can be used in separable convolution to smooth images.
Usage
1
gaussKernel(fwhm=8,ksize=5,voxsize=1)
Arguments
fwhm
Full width at half maximum of the kernel.
ksize
Size of kernel. Must be Odd
voxsize
Size of the voxel in the direction you wish to smooth in. If smoothing a non medical image leave voxsize as 1 unless anisotropic smoothing is required.
Value
Returns a Kernel
Examples
1
ts.plot(gaussKernel(ksize=23,voxsize=1))
FIACH documentation built on May 1, 2019, 8:02 p.m.
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Description Usage Arguments Value Examples
Description
This function produces a Gaussian smoothing kernel that can be used in separable convolution to smooth images.
Usage
1 | gaussKernel(fwhm=8,ksize=5,voxsize=1)
|
Arguments
fwhm |
Full width at half maximum of the kernel. |
ksize |
Size of kernel. Must be Odd |
voxsize |
Size of the voxel in the direction you wish to smooth in. If smoothing a non medical image leave voxsize as 1 unless anisotropic smoothing is required. |
Value
Returns a Kernel
Examples
1 | ts.plot(gaussKernel(ksize=23,voxsize=1))
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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