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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:
Downloads:
Reverse dependencies:
Linking:
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https://CRAN.R-project.org/package=supercells
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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