11.8. Simple Linear Iterative Clustering (SLIC)

11.8. Simple Linear Iterative Clustering (SLIC)
	11. Taiteellinen-suotimet

11.8.1. Yleiskatsaus

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 main menu under Filters → Artistic → Simple Linear Iterative Clustering….

11.8.3. Asetukset

Kuva 17.209. ”Simple Linear Iterative Clustering” options

Presets, ”Input Type”, Clipping, Blending Options, Esikatselu, Merge filter, Split view

	Huomaa
	These options are described in Kohta 2, ”Common Features”.

Regions size

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

Kuva 17.210. ”Regions size” example

Regions size = 16

Regions size = 32

Compactness

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

Kuva 17.211. ”Compactness” example

Compactness = 20

Compactness = 40: look at the dome.

Iterations

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

Kuva 17.212. ”Regions size” example

Iterations = 1 (default)

Iterations = 15