Generic Function for Smoothing a Surface or Associated Data

The smooth function is a generic function designed to apply smoothing operations to various surface objects. The specific behavior of the function depends on the class of the object passed as the x argument. It can be used to smooth the geometry of a surface, the data associated with a surface, or other related operations depending on the method implemented for the object's class.

This method applies smoothing to a brain surface geometry object of class SurfaceGeometry using various algorithms. Smoothing is useful for removing noise and creating a more continuous surface.

Usage

smooth(x, ...)

# S4 method for class 'SurfaceGeometry'
smooth(
  x,
  type = c("taubin", "laplace", "HClaplace", "fujiLaplace", "angWeight",
    "surfPreserveLaplace"),
  lambda = 0.7,
  mu = -0.53,
  delta = 0.1,
  iteration = 5
)

Arguments

x

A SurfaceGeometry object representing the brain surface to be smoothed.

...

Additional arguments passed to the specific method for smoothing the surface object.

type

A character string specifying the smoothing algorithm to use. Available options are:

"taubin"

Applies Taubin smoothing, which preserves the overall shape of the surface while reducing noise.

"laplace"

Performs Laplacian smoothing, which is a basic smoothing method that averages the position of each vertex with its neighbors.

"HClaplace"

Applies a Laplacian smoothing with hard constraints. It preserves the boundary vertices and is useful for surfaces with important edge features.

"fujiLaplace"

Uses a Laplacian smoothing method that preserves features more aggressively than the basic Laplacian method.

"angWeight"

Performs angle-weighted smoothing, which considers the angles between faces to preserve sharp features.

"surfPreserveLaplace"

Applies surface-preserving Laplacian smoothing, aiming to maintain the original surface's key characteristics while smoothing.

lambda

A numeric value that controls the amount of smoothing. Higher values lead to more aggressive smoothing. This parameter is particularly relevant for Taubin and Laplacian smoothing methods.

mu

A numeric value used in Taubin smoothing to control shrinkage. A value close to zero reduces shrinkage, while a negative value can help in shape preservation.

delta

A numeric value used in certain smoothing algorithms to adjust the influence of smoothing (e.g., in surface-preserving methods).

iteration

An integer specifying the number of smoothing iterations to apply. More iterations result in a smoother surface but can also lead to excessive flattening.

Value

The function returns the smoothed SurfaceGeometry object with the updated mesh.

Details

The smooth function provides a common interface for smoothing operations on different types of surface objects. The actual smoothing process varies based on the class of the object provided:

• For SurfaceGeometry objects, the function smooths the surface geometry, modifying the shape of the mesh to reduce noise.

• For NeuroSurface objects, the function smooths the data values associated with each vertex, preserving the surface geometry but producing a smoother dataset.

Users should refer to the specific method documentation for the class of object they are working with to understand the exact behavior and parameters.

See also

smooth,SurfaceGeometry-method, smooth,NeuroSurface-method

vcgSmooth for more details on the underlying smoothing algorithms.

Examples

if (FALSE) { # \dontrun{
  # Smooth a SurfaceGeometry object
  smoothed_geom <- smooth(surface_geom_obj, type="taubin", lambda=0.7, iteration=10)

  # Smooth a NeuroSurface object's data
  smoothed_data_surface <- smooth(neuro_surf_obj, sigma=5)
} # }

# Load a surface file from the extdata directory
surf_file <- system.file("extdata", "std.8_lh.inflated.asc", package = "neurosurf")
surface <- read_surf_geometry(surf_file)
#> loading /private/var/folders/9h/nkjq6vss7mqdl4ck7q1hd8ph0000gp/T/Rtmp0Nbniq/temp_libpath80e31f94425b/neurosurf/extdata/std.8_lh.inflated.asc

# Apply Taubin smoothing to the brain surface
smoothed_surface1 <- smooth(surface, type = "taubin", lambda = 0.5, mu = -0.5, iteration = 10)

# Apply surface-preserving Laplacian smoothing
smoothed_surface2 <- smooth(surface, type = "surfPreserveLaplace", iteration = 5)