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Apply a bilateral filter to a volumetric image

Source: R/spat_filter.R
bilateral_filter.Rd

This function smooths a volumetric image (3D brain MRI data) using a bilateral filter. The bilateral filter considers both spatial closeness and intensity similarity for smoothing. Only in-mask, in-bounds neighbors contribute to each local weighted average.

Usage

bilateral_filter(
  vol,
  mask,
  spatial_sigma = 2,
  intensity_sigma = 1,
  window = 1,
  range_scale = NULL
)

Arguments

vol

A NeuroVol object representing the image volume to be smoothed.

mask

An optional LogicalNeuroVol object representing the image mask that defines the region where the filtering is applied. If not provided, the entire volume is considered.

spatial_sigma

A numeric value specifying the standard deviation of the spatial Gaussian kernel (default is 2).

intensity_sigma

A numeric value specifying the standard deviation of the intensity Gaussian kernel (default is 1).

window

An integer specifying the number of voxels around the center voxel to include on each side. For example, window=1 for a 3x3x3 kernel (default is 1).

range_scale

Optional positive numeric range scale used by the intensity kernel. If NULL, the scale is estimated as the standard deviation of the current input values inside mask. Supply a fixed value to apply the same range bandwidth across observed and null maps.

Value

A smoothed image of class NeuroVol.

Details

With range_scale = NULL, the intensity bandwidth is estimated separately for each input volume. Equal intensity_sigma values therefore do not imply equal bandwidths across subjects, contrasts, or observed/null maps. For batch or group workflows, choose one positive finite range_scale from a reference or pooled in-mask intensity distribution and reuse it, along with the same intensity_sigma, for every map in comparable intensity units. The effective bandwidth is intensity_sigma * range_scale.

Examples

brain_mask <- read_vol(system.file("extdata", "global_mask_v4.nii", package="neuroim2"))

# Apply bilateral filtering to the brain volume
filtered_vol <- bilateral_filter(brain_mask, brain_mask, spatial_sigma = 2,
intensity_sigma = 25, window = 1)