bayes_smooth: Smooth probability images

In bayesEO: Bayesian Smoothing of Remote Sensing Image Classification

Smooth probability images

Description

Takes a classified image with probabilities, and reduces outliers and smoothens probability according to Bayesian statistics

Usage

bayes_smooth(x, window_size = 7, neigh_fraction = 0.5, smoothness = 10)

Arguments

x	SpatRaster object with probabilities images
window_size	Size of the neighborhood.
neigh_fraction	Fraction of neighbors with high probabilities to be used in Bayesian inference.
smoothness	Estimated variance of logit of class probabilities (Bayesian smoothing parameter). It can be either a vector or a scalar.

Value

A SpatRaster object

Author(s)

Gilberto Camara, [e-mail]

Examples

if (bayes_run_examples()) {
    # select a file with probability values
    data_dir <- system.file("/extdata/probs/", package = "bayesEO")
    file <- list.files(data_dir)
    # create a full path for the file
    probs_file <- paste0(data_dir, "/", file)
    # provide the labels
    labels <- c("Water", "ClearCut_Burn", "ClearCut_Soil",
             "ClearCut_Veg", "Forest", "Wetland")
    # read the probs file
    probs <- bayes_read_probs(probs_file, labels)
    # smooth the probability image
    probs_smooth <- bayes_smooth(probs,
            window_size = 7,
            smoothness = 20
    )
    # plot the probability image
    bayes_plot_probs(probs_smooth)
}

bayesEO documentation built on June 22, 2024, 10:32 a.m.