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

#### 11.8.3. Options

图 17.223. “Simple Linear Iterative Clustering” options

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

  | 注意
  These options are described in 第 2 节 “Common Features”.

Regions size

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

  图 17.224. “Regions size” example

  Regions size = 16

  Regions size = 32

Compactness

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

  图 17.225. “Compactness” example

  Compactness = 20

  Compactness = 40: look at the dome.

Iterations

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

  图 17.226. “Regions size” example

  Iterations = 1 (default)

  Iterations = 15

11.7. Photocopy |  | 11.9. Softglow

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