supercells: Superpixels of Spatial Data

Creates superpixels based on input spatial data. This package works on spatial data with one variable (e.g., continuous raster), many variables (e.g., RGB rasters), and spatial patterns (e.g., areas in categorical rasters). It is based on the SLIC algorithm (Achanta et al. (2012) <doi:10.1109/TPAMI.2012.120>), and readapts it to work with arbitrary dissimilarity measures.

Version:	1.0.0
Imports:	sf, terra (≥ 1.4-21), philentropy (≥ 0.6.0), future.apply
LinkingTo:	cpp11
Suggests:	knitr, covr, testthat (≥ 3.0.0), rmarkdown, stars
Published:	2024-02-11
DOI:	10.32614/CRAN.package.supercells
Author:	Jakub Nowosad [aut, cre], Pascal Mettes [ctb] (Author of the initial C++ implementation of the SLIC Superpixel algorithm for image data), Charles Jekel [ctb] (Author of underlying C++ code for dtw)
Maintainer:	Jakub Nowosad <nowosad.jakub at gmail.com>
BugReports:	https://github.com/Nowosad/supercells/issues
License:	GPL (≥ 3)
URL:	https://jakubnowosad.com/supercells/
NeedsCompilation:	yes
Citation:	supercells citation info
Materials:	README NEWS
CRAN checks:	supercells results

Documentation:

Reference manual:

supercells.pdf

Downloads:

Package source:	supercells_1.0.0.tar.gz
Windows binaries:	r-devel: supercells_1.0.0.zip, r-release: supercells_1.0.0.zip, r-oldrel: supercells_1.0.0.zip
macOS binaries:	r-release (arm64): supercells_1.0.0.tgz, r-oldrel (arm64): supercells_1.0.0.tgz, r-release (x86_64): supercells_1.0.0.tgz, r-oldrel (x86_64): supercells_1.0.0.tgz
Old sources:	supercells archive

Reverse dependencies:

Reverse suggests:

regional, sits

Linking:

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