Histogram Equalization

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Power Law Adaptive Histogram Equalization.

Histogram equalization modifies the contrast in an image. Adaptive histogram equalization is a superset of many contrast enhancing filters. By modifying its parameters, this filter can produce an adaptively equalized histogram or a version of unsharp mask (local mean subtraction). Instead of applying a strict histogram equalization in a window about a pixel, this filter prescribes a mapping function (power law) controlled by the parameters α and β.



Input image(s).

Type: Image, List, Required, Single



Output image(s).

Type: Image, List


Alpha Float

The parameter alpha controls how much the filter acts like the classical histogram equalization method (α=0) to how much the filter acts like an unsharp mask (α=1).

Beta Float

The parameter beta controls how much the filter acts like an unsharp mask (β=0) to much the filter acts like pass through (β=1, with α=1).

Radius [px] Integers

Controls the size of the region in voxels over which local statistics are calculated, specified as [i, j, k].

See also