11.8. Simple Linear Iterative Clustering (SLIC)

11.8.1. Översikt

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. Alternativ

Figur 17.206. Simple Linear Iterative Clustering options

”Simple Linear Iterative Clustering” options

Presets, Preview, Split view
[Notera] Notera

Dessa alternativ beskrivs i Avsnitt 2, ”Gemensamma funktioner”.

Regions size

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

Figur 17.207. Regions size example

”Regions size” example

Regions size = 16

”Regions size” example

Regions size = 32


Compactness

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

Figur 17.208. Compactness example

”Compactness” example

Compactness = 20

”Compactness” example

Compactness = 40: look at the dome.


Iterations

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

Figur 17.209. Regions size example

”Regions size” example

Iterations = 1 (default)

”Regions size” example

Iterations = 15


Clipping

Resultatet av detta filer kan vara större än originalbilden. Med alternativet Justera kommer lagret automatiskt att ändra storlek som nödvändigt när filtret tillämpas. Med alternativet Klipp kommer resultatet att klippas till lagergränsen.