Package 'GLCMTextures'

Calculates the GLCM Texture Metrics from a GLCM

Description

Calculates the GLCM Texture Metrics from a GLCM

Usage

glcm_metrics(
  GLCM,
  metrics = c("glcm_contrast", "glcm_dissimilarity", "glcm_homogeneity", "glcm_ASM",
    "glcm_entropy", "glcm_mean", "glcm_variance", "glcm_correlation", "glcm_SA")
)

Arguments

GLCM	A numeric matrix representing a Normalized GLCM.
metrics	A vector of texture metrics to return. Valid entries include "glcm_contrast", "glcm_dissimilarity", "glcm_homogeneity", "glcm_ASM", "glcm_entropy", "glcm_mean", "glcm_variance", "glcm_correlation".

Value

GLCM based texture measures as a numeric vector.

References

Hall-Beyer, M., 2017. GLCM Texture: A Tutorial v. 3.0. University of Calgary, Alberta, Canada.

Haralick, R.M., Shanmugam, K., Dinstein, I., 1973. Textural features for image classification. IEEE Transactions on Systems, Man, and Cybernetics 610–621. https://doi.org/10.1109/TSMC.1973.4309314

Examples

test_matrix<- matrix(data=c(2,0,1,3,0,0,0,3,2), nrow = 3, ncol=3)
horizontal_glcm<- make_glcm(test_matrix, n_levels = 4,
shift = c(1,0), normalize = TRUE)
metrics<-glcm_metrics(horizontal_glcm, metrics= c("glcm_contrast",
"glcm_dissimilarity", "glcm_homogeneity", "glcm_ASM",
"glcm_entropy", "glcm_mean", "glcm_variance", "glcm_correlation"))

---

Calculates GLCM texture metrics of a Raster Layer

Description

Calculates GLCM texture metrics of a RasterLayer over a sliding rectangular window

Usage

glcm_textures(
  r,
  w = c(3, 3),
  n_levels,
  shift = list(c(1, 0), c(1, 1), c(0, 1), c(-1, 1)),
  metrics = c("glcm_contrast", "glcm_dissimilarity", "glcm_homogeneity", "glcm_ASM",
    "glcm_entropy", "glcm_mean", "glcm_variance", "glcm_correlation", "glcm_SA"),
  quantization,
  min_val = NULL,
  max_val = NULL,
  maxcell = Inf,
  na.rm = FALSE,
  include_scale = FALSE,
  filename = NULL,
  overwrite = FALSE,
  wopt = list()
)

Arguments

r	A single layer SpatRaster or RasterLayer. If already quantized set quantization to "none". The valid range of values for a quantized raster is from 0 to n_levels-1 (e.g. a raster with 32 grey levels would have a valid range of 0-31).
w	A vector of length 2 specifying the dimensions of the rectangular window to use where the first number is the number of rows and the second number is the number of columns. Window size must be an odd number.
n_levels	Number of grey levels used in the quantization (Typically set to 16 or 32).
shift	A vector of length 2, or a list of vectors each of length 2 specifying the relationship between neighboring pixel to the reference pixel. The first number represents the shift in the x direction and the second number represents the shift in the y direction, where up and right are positive. For example c(1,0) is the pixel directly to the right. The GLCM is made symmetrical by counting each pair twice, once "forwards" and once "backwards" by interchanging reference and neighbor pixels. Therefore a shift directly to the right c(1,0) is equivalent to a shift directly to the left c(-1,0). To average over "all directions" you can use shift=list(c(1,0), c(1,1), c(0,1), c(-1,1)), which is the default.
metrics	A vector of glcm texture metrics to return. Valid entries include "glcm_contrast", "glcm_dissimilarity", "glcm_homogeneity", "glcm_ASM" (angular second moment), "glcm_entropy", "glcm_mean", "glcm_variance", "glcm_correlation", "glcm_SA" (Sum Average).
quantization	quantization method (either "equal range", "equal prob", or "none"). "equal range" quantization will create bins that cover a range of equal size. "equal prob" performs equal probability quantization and will use quantiles to create bins with approximately equal number of samples. "none" means the layer has already been quantized.
min_val	minimum value for equal range quantization (if not supplied, the minimum value of the raster is used)
max_val	maximum value for equal range quantization (if not supplied, the maximum value of the raster is used)
maxcell	positive integer used to take a regular sample for quantization if "equal prob" is used (default is Inf)
na.rm	a logical value indicating whether NA values should be stripped before the computation proceeds (default=FALSE)
include_scale	Logical indicating whether to append window size to the layer names (default = FALSE).
filename	character Output filename. Can be a single filename, or as many filenames as there are layers to write a file for each layer
overwrite	logical. If TRUE, filename is overwritten (default is FALSE).
wopt	list with named options for writing files as in writeRaster

Value

a SpatRaster or Raster* Object

References

Hall-Beyer, M., 2017. GLCM Texture: A Tutorial v. 3.0. University of Calgary, Alberta, Canada.

Haralick, R.M., Shanmugam, K., Dinstein, I., 1973. Textural features for image classification. IEEE Transactions on Systems, Man, and Cybernetics 610–621. https://doi.org/10.1109/TSMC.1973.4309314

Examples

r<- rast(volcano, extent= ext(2667400, 2667400 + ncol(volcano)*10,
6478700, 6478700 + nrow(volcano)*10), crs = "EPSG:27200")
txt <- glcm_textures(r, w = c(3,5), n_levels = 16,
quantization = "equal prob", shift = list(c(1, 0), c(1, 1),
c(0, 1), c(-1, 1)))
plot(txt)

---

Creates a symmetrical normalized GLCM for a given matrix and shift

Description

Creates a symmetrical normalized GLCM for a given matrix and shift

Usage

make_glcm(x, n_levels, shift, na.rm = FALSE, normalize = TRUE)

Arguments

x	a matrix of integers representing quantized values. The valid range of values is from 0 to n_levels-1 (e.g. a matrix with 32 grey levels would have a valid range of 0-31).
n_levels	Number of grey levels used in the quantization
shift	A vector of length 2 specifying the relationship between neighboring pixel to the reference pixel. The first number represents the shift in the x direction and the second number represents the shift in the y direction, where up and right are positive. For example c(1,0) is the pixel directly to the right. The GLCM is made symmetrical by counting each pair twice, once "forwards" and once "backwards" by interchanging reference and neighbor pixels. Therefore a shift directly to the right c(1,0) is equivalent to a shift directly to the left c(-1,0)
na.rm	a logical value indicating whether NA values should be stripped before the computation proceeds (default=FALSE)
normalize	a logical specifying whether to normalize the counts to probabilities by dividing by the sum of the GLCM (TRUE, the default) or to express the GLCM as counts (FALSE)

Value

A symmetric GLCM as a matrix

References

Hall-Beyer, M., 2017. GLCM Texture: A Tutorial v. 3.0. University of Calgary, Alberta, Canada.

Haralick, R.M., Shanmugam, K., Dinstein, I., 1973. Textural features for image classification. IEEE Transactions on Systems, Man, and Cybernetics 610–621. https://doi.org/10.1109/TSMC.1973.4309314

Examples

test_matrix<- matrix(data=c(2,0,1,3,0,0,0,3,2), nrow = 3, ncol=3)
# Tabulate a GLCM of counts
horizontal_glcm_counts<- make_glcm(test_matrix, n_levels = 4, shift = c(1,0), normalize = FALSE)
# Calculate a normalized GLCM of probabilities
horizontal_glcm_norm<- make_glcm(test_matrix, n_levels = 4, shift = c(1,0), normalize = TRUE)

---

Quantizes raster to a set number of discrete levels

Description

Quantizes raster to a set number of discrete levels starting at 0. There are 2 methods of quantization are available: "equal range" and "equal prob"

Usage

quantize_raster(
  r,
  n_levels,
  method,
  min_val = NULL,
  max_val = NULL,
  maxcell = Inf,
  filename = NULL,
  overwrite = FALSE,
  wopt = list()
)

Arguments

r	A single layer SpatRaster or RasterLayer.
n_levels	number of levels to quantize to
method	quantization method (either "equal range" or "equal prob"). "equal range" quantization will create bins that cover a range of equal size. "equal prob" performs equal probability quantization and will use quantiles to create bins with approximately equal number of samples.
min_val	minimum value for equal range quantization (if not supplied, the minimum value of the raster is used)
max_val	maximum value for equal range quantization (if not supplied, the maximum value of the raster is used)
maxcell	positive integer used to take a regular sample of x if "equal prob" is used (default is Inf)
filename	character Output filename.
overwrite	logical. If TRUE, filename is overwritten (default is FALSE).
wopt	list with named options for writing files as in writeRaster

Details

Equal probability quantization is the method recommended in Haralick et al., 1973. However, equal range may be more desirable if making comparisons across several different rasters where you need the gray levels to correspond in a consistent way to the original data, as you can supply the global max/min or the theoretical max/min values that could occur. When equal probability quantization is used, quantiles are generated using type 8 as recommended by Hyndman and Fan (1996). This method provides estimates that are approximately median-unbiased regardless of the distribution of x.

Value

a single layer SpatRaster or RasterLayer with integer values ranging from 0 to n_levels-1

References

Haralick, R.M., Shanmugam, K., Dinstein, I., 1973. Textural features for image classification. IEEE Transactions on Systems, Man, and Cybernetics 610–621. https://doi.org/10.1109/TSMC.1973.4309314

Hyndman, R.J., Fan, Y., 1996. Sample Quantiles in Statistical Packages. The American Statistician 50, 361–365. https://doi.org/10.1080/00031305.1996.10473566

Examples

r<- rast(volcano, extent= ext(2667400, 2667400 + ncol(volcano)*10,
6478700, 6478700 + nrow(volcano)*10),
crs = "EPSG:27200")
rq1 <- quantize_raster(r = r, n_levels = 16, method = "equal prob")
rq2 <- quantize_raster(r = r, n_levels = 16, method = "equal range")

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