### 3.6. Median Blur

#### 3.6.1. Overview

Figure 17.19. Example for the “Median Blur” filter

Original image

Filter applied

While the “Gaussian” blur filter calculates the mean of the neighboring pixels, the “Median” blur filter calculates the median:

Figure 17.20. Calculating Median

A 3×3 neighborhood. Values in ascending order. Median surrounded in red.

This calculation does not create a new value, and an unrepresentative pixel in the neighborhood will not affect the result. So, the filter preserves edges and rounds corners. It is used to reduce noise, especially salt and pepper noise, and delete scratches on photographs.

#### 3.6.2. Activating the Filter

This filter is found in the main menu under Filters → Blur → Median Blur….

#### 3.6.3. Options

Figure 17.21. “Median” filter parameters

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

  | Note
  These options are described in Section 2, “Common Features”.

Neighborhood

  The shape of the neighborhood. Three options: Square, Circle (default), Diamond. Differences are subtle and not predictable: experiment, on-canvas editing makes this easy.

  Figure 17.22. “Median” Neighborhood

  Radius=3. Left: Square.

  Middle: Circle. Right: Diamond.

Radius

  The radius of the neighborhood. Increasing radius increases blur. Contrary to the “Gaussian” filter, edges are not blurred. Corners are rounded and convex surfaces are eroded.

  Figure 17.23. “Median” blur vs “Gaussian” blur

  Left: Original image

  Middle: Median Blur filter applied

  Right: Gaussian Blur filter applied

  Increasing radius too much can create unwanted effects:

  Left: Origin

  Right: Radius=100

Percentile

  By default, the Median Blur filter finds the median value at the neighborhood of each pixel. In spite of its name, the filter can actually find *any* arbitrary percentile, not just the median (i.e., the 50th percentile). The "Percentile" parameter controls the percentile used for the color components. Lower values shift the image toward darker tones and higher values toward brighter ones.

  Left: Origin

  Middle: Percentile=0. Image is darker. Stems are enlarged but sharp.

  Right: Percentile=100. Image is brighter and much blurred.

Alpha percentile

  To see the effect of this parameter, you need an image with transparency. If the alpha channel is opaque everywhere, the result will also be fully opaque, regardless of the percentile.

  Lower values for the “Alpha percentile” parameter shift the image toward more transparency, and higher values shift the image toward more opacity, where a value of 50% is balanced. Roughly speaking, values less than 50% make the opaque regions of the image smaller, while values greater than 50% make the opaque regions of the image larger.

  Figure 17.24. “Alpha percentile” option example

  Left: Origin. The image has an alpha channel. A circle is transparent.

  Middle: Percentile=0%. Transparent circle is enlarged.

  Right: Alpha percentile=100%. Transparent circle is reduced.

Abyss policy

  Abyss policy (border management) is treated with Abyss policy.

High precision

  This option avoids clipping and quantization but is slower.

#### 3.6.4. Using Median Blur

Reducing salt and pepper noise

  Left: origin

  Middle: radius = 1 applied twice

  Right: radius = 1 applied three times

Reducing scratches

  Left: origin

  Middle: radius = 2

  Right: radius = 1 applied twice. The image is less blurred.

3.5. Mean Curvature Blur |  | 3.7. Pixelize

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