k-nearest neighbors constrained smoothing — knnSmoothingMatrix • ANTsR

Compute a smoothing matrix based on an input matrix of point coordinates

knnSmoothingMatrix(x, k, sigma, segmentation, ...)

Arguments

x	input matrix of point coordinates of dimensions n-spatial spatial dimensions by p points
k	number of neighbors, higher causes more smoothing
sigma	sigma for the gaussian function
segmentation	optional boolean to restrict specific rows to have minimal respons
...	arguments passed to `sparseDistanceMatrix`

Value

sparse matrix is output

Examples


if (FALSE) {
mask = getMask( antsImageRead( getANTsRData( 'r16' ) ) )
spatmat = t( imageDomainToSpatialMatrix( mask, mask ) )
smoothingMatrix = knnSmoothingMatrix( spatmat, k = 25, sigma = 3.0 )
rvec = rnorm( nrow( smoothingMatrix ) )
srvec = smoothingMatrix %*% rvec
rvi = makeImage( mask, rvec )
srv = makeImage( mask,  as.numeric( srvec ) )
}