https://github.com/kadyb/image-segmentation
Comparison of kmeans and supercells for image semgentiation in R
https://github.com/kadyb/image-segmentation
clustering image kmeans pixel r raster segmentation slic spatial superpixels
Last synced: over 1 year ago
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Comparison of kmeans and supercells for image semgentiation in R
- Host: GitHub
- URL: https://github.com/kadyb/image-segmentation
- Owner: kadyb
- Created: 2023-02-09T10:09:45.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-02-12T16:35:11.000Z (over 3 years ago)
- Last Synced: 2024-01-27T05:11:29.976Z (over 2 years ago)
- Topics: clustering, image, kmeans, pixel, r, raster, segmentation, slic, spatial, superpixels
- Language: R
- Homepage:
- Size: 11.4 MB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Image segmentation in R
In this repository you will find examples of image segmentation scripts in R.
Example `ortho.R` shows segmentation on a small RGB orthoimage, while example
`landsat.R` uses a multiband spectral image (8261 x 8201 pixels x 7 bands).
The Quarto file `comparison.qmd` contains a comparison of the simple kmeans
clustering algorithm with [supercells](https://github.com/Nowosad/supercells)
based on SLIC algorithm.
Note: Currently the kmeans prediction method in `landsat.R` is very slow
(calculations take ~1 hour). Alternatively, you can check out the example
in `landsat_blocks.R`, which uses processing in blocks (it takes ~18 min),
but unfortunately the boundaries between blocks are strongly visible.
