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

11.8. Simple Linear Iterative Clustering (SLIC)

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. Käynnistetään suodin

This filter is found in the image window menu under Filters → Artistic → Simple Linear Iterative Clustering….

11.8.3. Asetukset

Kuva 17.211. ”Simple Linear Iterative Clustering” options

”Simple Linear Iterative Clustering” options

Presets, ”Input Type”, Clipping, Blending Options, Preview, Split view
[Huomaa] 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 17.212. ”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.

Kuva 17.213. ”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.

Kuva 17.214. ”Regions size” example

”Regions size” example

Iterations = 1 (default)

”Regions size” example

Iterations = 15


Edellinen  Ylös  Seuraava
11.7. Valokopio  Alkuun  11.9. Pehmeä hehku
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