laplace_enhance: Laplacian Enhancement Filter for Volumetric Images

In bbuchsbaum/neuroim2: Data Structures and IO for Neuroimaging Data with an Emphasis on Functional Magnetic Resonance Imaging (FMRI)

Laplacian Enhancement Filter for Volumetric Images

Description

This function applies a multi-layer Laplacian enhancement filter to a volumetric image (3D brain MRI data). The filter enhances details while preserving edges using a non-local means approach with multiple scales.

Usage

laplace_enhance(
  vol,
  mask,
  k = 2,
  patch_size = 3,
  search_radius = 2,
  h = 0.7,
  mapping_params = NULL,
  use_normalization_free = TRUE
)

Arguments

vol	A NeuroVol object representing the image volume to be enhanced.
mask	A LogicalNeuroVol object specifying the region to process. If not provided, the entire volume will be processed.
k	An integer specifying the number of layers in the decomposition (default is 2).
patch_size	An integer specifying the size of patches for non-local means. Must be odd (default is 3).
search_radius	An integer specifying the radius of the search window (default is 2).
h	A numeric value controlling the filtering strength. Higher values mean more smoothing (default is 0.7).
mapping_params	An optional list of parameters for the enhancement mappings.
use_normalization_free	Logical indicating whether to use normalization-free weights (default is TRUE).

Value

A NeuroVol object representing the enhanced image.

bbuchsbaum/neuroim2 documentation built on Jan. 2, 2025, 3:38 p.m.