k-nearest neighbors constrained smoothing

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

Author

Avants BB

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 ) )
}