im.classify {imageRy}R Documentation

Classify a Raster Image Using K-Means Clustering

Description

This function performs unsupervised classification on a raster image using k-means clustering. It rescales the pixel values to 0–255 to improve visual clustering of scientific TIFFs.

Usage

im.classify(
  input_image,
  num_clusters = 3,
  seed = NULL,
  do_plot = TRUE,
  custom_colors = NULL,
  num_colors = 100
)

Arguments

input_image

A 'SpatRaster' object representing the input raster image.

num_clusters

An integer specifying the number of clusters (default: 3).

seed

An optional integer seed for reproducibility of k-means clustering results (default: NULL).

do_plot

A logical value indicating whether to display the classified raster (default: TRUE).

custom_colors

A vector of custom colors to be used for classification visualization (default: NULL). If NULL, a predefined set of colors is used.

num_colors

The number of colors to interpolate in the visualization palette (default: 100).

Value

A 'SpatRaster' object with cluster assignments.


[Package imageRy version 0.3.0 Index]