Focal statistics, filters and grey morphology

FocalStatistics: moving-window mean, sum, min, max, range, median, sample variance or standard deviation, or Shannon entropy, as terra::focal (cells outside the grid are NA). FilterKernel: mean, binomial, Gaussian, Laplacian, sharpen, Prewitt, Sobel and Gabor kernels. FocalFilter: weighted window sum (correlation) as terra::focal(x, w, fun = "sum"). CannyEdges: Canny (1986) detector. GreyMorphology: erosion, dilation, opening and closing with a flat square element. Identical to the Python arm morie.fn.rastops.

Usage

FocalStatistics(grid, size = 3, fun = "mean", na_rm = FALSE)

FilterKernel(
  name,
  size = 3,
  sigma = 1,
  theta = 0,
  wavelength = 4,
  gamma = 0.5,
  psi = 0
)

FocalFilter(grid, kernel, na_rm = FALSE)

CannyEdges(grid, sigma = 1, low = 0.1, high = 0.2, size = 5)

GreyMorphology(grid, operation, size = 3)

Arguments

grid: Numeric matrix (row 1 = north).
size: Window or kernel size (odd).
fun: Statistic.
na_rm: Drop NA values.
name: Kernel name.
sigma, theta, wavelength, gamma, psi: Gaussian and Gabor parameters.
kernel: Weight matrix.
low, high: Hysteresis thresholds (fractions of the maximum gradient).
operation: "erosion", "dilation", "opening" or "closing".

Value

Matrix.

References

Canny, J. (1986). A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8, 679-698.

Serra, J. (1982). Image Analysis and Mathematical Morphology. Academic Press.

Examples

FocalStatistics(matrix(1:9, 3, byrow = TRUE), fun = "median", na_rm = TRUE)
#>      [,1] [,2] [,3]
#> [1,]  3.0  3.5  4.0
#> [2,]  4.5  5.0  5.5
#> [3,]  6.0  6.5  7.0
FocalFilter(matrix(1:9, 3, byrow = TRUE), FilterKernel("prewitt_x"))[2, 2]
#> [1] 6