11.8. Simple Linear Iterative Clustering (SLIC)
| 11. Фильтры имитации |

### 11.8. Simple Linear Iterative Clustering (SLIC)

#### 11.8.1. Общая информация

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. Активация фильтра

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

#### 11.8.3. Параметры

Рисунок 17.198. «Simple Linear Iterative Clustering» options

Presets, Preview, Split view

  | Примечание
  These options are described in Раздел 2, «Common Features».

Regions size

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

  Рисунок 17.199. «Regions size» example

  Regions size = 16

  Regions size = 32

Compactness

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

  Рисунок 17.200. «Compactness» example

  Compactness = 20

  Compactness = 40: look at the dome.

Iterations

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

  Рисунок 17.201. «Regions size» example

  Iterations = 1 (default)

  Iterations = 15

11.7. Фотокопия |  | 11.9. Мягкий свет

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