skimage2.filters.rank.autolevel

skimage2.filters.rank.autolevel(image, footprint, out=None, mask=None, shift_x=0, shift_y=0, shift_z=0)

Auto-level image using local histogram.

This filter locally stretches the histogram of gray values to cover the entire range of values from “white” to “black”.

Parameters:

imagendarray of shape ([P,] M, N) and dtype (uint8 or uint16)

Input image.

footprintndarray

The neighborhood expressed as an ndarray of 1’s and 0’s.

outndarray of shape ([P,] M, N), same dtype as input image

If None, a new array is allocated.

maskndarray of dtype (int or float), optional

Mask array that defines (>0) area of the image included in the local neighborhood. If None, the complete image is used (default).

shift_x, shift_y, shift_zint

Offset added to the footprint center point. Shift is bounded to the footprint sizes (center must be inside the given footprint).

Returns:

outndarray of shape ([P,] M, N), same dtype as input image

Output image.

Examples

>>> from _skimage2 import data
>>> from _skimage2.morphology import disk, ball
>>> from _skimage2.filters.rank import autolevel
>>> import numpy as np
>>> img = data.camera()
>>> rng = np.random.default_rng()
>>> volume = rng.integers(0, 255, size=(10,10,10), dtype=np.uint8)
>>> auto = autolevel(img, disk(5))
>>> auto_vol = autolevel(volume, ball(5))