11.8. Simple Linear Iterative Clustering (SLIC)

11.8.1. Overview

This filter creates superpixels based on k-means clustering.

Superpixels are small cluster of pixels that share similar properties. Superpixels simplifies images with a great number of pixels making them more easy to be treated in many domains (computer vision, pattern recognition and machine intelligence). GIMP's aim is more humble: create a posterization effect.

k-means clustering is one of the most used algorithms to create superpixels. Superpixel color is the mean of pixels color in the corresponding region.

11.8.2. Activating the filter

This filter is found in the image window menu under FiltersArtisticSimple Linear Iterative Clustering….

11.8.3. Options

Slika 17.211. Simple Linear Iterative Clustering options

“Simple Linear Iterative Clustering” options

Presets, Input Type, Clipping, Blending Options, Preview, Split view
[Bilješka] Bilješka

These options are described in Odjeljak 2, “Common Features”.

Regions size

Increasing regions size collects more pixels, and so superpixels size increases also.

Slika 17.212. Regions size example

“Regions size” example

Regions size = 16

“Regions size” example

Regions size = 32


Superpixels borders may be irregular. Increasing this option gives superpixels more regular border.

Slika 17.213. Compactness example

“Compactness” example

Compactness = 20

“Compactness” example

Compactness = 40: look at the dome.


How many times filter is repeated. Increasing this value gives more details.

Slika 17.214. Regions size example

“Regions size” example

Iterations = 1 (default)

“Regions size” example

Iterations = 15