regional_thresholding: Regional thresholding

In rcaiman: CAnopy IMage ANalysis

Regional thresholding

Description

Regional thresholding of greyscale images.

Usage

regional_thresholding(
  r,
  segmentation,
  method,
  intercept = NULL,
  slope = NULL,
  prob = NULL
)

Arguments

r	SpatRaster. A normalized greyscale image. Typically, the blue channel extracted from a canopy photograph. Please see read_caim() and normalize().
segmentation	SpatRaster. The result of segmenting r. Arguably, the result of a call to rings_segmentation() will be the preferred choice for fisheye images.
method	Character vector of length one. See details for current options.
intercept, slope	Numeric vector of length one. These are linear function coefficients.
prob	Numeric vector of length one. Probability for stats::quantile() calculation.

Details

Methods currently implemented are:

• Diaz2018: method presented in \insertCiteDiaz2018;textualrcaiman applied regionally. If this method is selected, the arguments intercept, slope, and prob should be provided. It works segment-wise extracting the digital numbers per segment and passing them to stats::quantile() along with prob, which aggregated result is in turn passed to thr_mblt() along with intercept and slope. Finally, this threshold image is applied to obtain a binarized image.

• Methods from autothresholdr package: this function can call methods from autothresholdr::auto_thresh(). For instance, use "IsoData" to use the algorithm by \insertCiteisodata;textualrcaiman, which was recommended by \insertCiteJonckheere2005;textualrcaiman.

• Method isodata from this package: Use "thr_isodata" to use thr_isodata().

Value

An object of class SpatRaster with values 0 and 1.

References

\insertAllCited

See Also

Other Binarization Functions: apply_thr(), obia(), ootb_mblt(), ootb_obia(), thr_isodata(), thr_mblt()

Examples

## Not run: 
path <- system.file("external/DSCN4500.JPG", package = "rcaiman")
caim <- read_caim(path, c(1250, 1020) - 745, 745 * 2, 745 * 2)
z <- zenith_image(ncol(caim), lens("Nikon_FCE9"))
r <- gbc(caim$Blue)
r <- correct_vignetting(r, z, c(0.0638, -0.101)) %>% normalize()
rings <- rings_segmentation(z, 15)
bin <- regional_thresholding(r, rings, "Diaz2018", -7.8, 0.95 * 0.5, 0.99)
plot(bin)
bin <- regional_thresholding(r, rings, "thr_isodata")
plot(bin)
#' 
## End(Not run)

rcaiman documentation built on Nov. 15, 2023, 1:08 a.m.