View source: R/multiscaleSVDxpts.R
knnSmoothImage | R Documentation |
Compute a smoothing matrix based on an input matrix of point coordinates as well as neighborhood intensity patterns. this performs a form of edge preserving smoothing.
knnSmoothImage(
img,
mask,
radius,
intensityWeight = 0.1,
spatialSigma = 20,
iterations = 1,
returnMatrix = FALSE
)
img |
input image to smooth |
mask |
input image mask |
radius |
number of neighbors, higher causes more smoothing |
intensityWeight |
weight for intensity component, value 1 will weight local voxel intensity roughly equally to spatial component |
spatialSigma |
for gaussian defining spatial distances |
iterations |
number of iterations over which to apply smoothing kernel |
returnMatrix |
boolean, will return smoothing matrix instead of image. |
antsImage is output
Avants BB
## Not run:
img <- antsImageRead(getANTsRData("r16"))
mask <- getMask(img)
simg <- knnSmoothImage(
img = img, mask = mask, radius = 2, intensityWeight = 1,
spatialSigma = 1.5, iterations = 1
)
## End(Not run)
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