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bundles / skimage 0.26.1rc0.dev0+git20260530.b607368ff / skimage / morphology / gray / white_tophat

function

skimage.morphology.gray:white_tophat

source: /dev/scikit-image/src/skimage/morphology/gray.py :494

Signature

def   white_tophat ( image ,  footprint = None ,  out = None ,  * ,  mode = reflect ,  cval = 0.0 )

Summary

Return white top hat of an image.

Extended Summary

The white top hat of an image is defined as the image minus its morphological opening. This operation returns the bright spots of the image that are smaller than the footprint.

Parameters

image : ndarray

Image array.

footprint : ndarray or tuple, optional

The neighborhood expressed as a 2-D array of 1's and 0's. If None, use a cross-shaped footprint (connectivity=1). The footprint can also be provided as a sequence of smaller footprints as described in the notes below.

out : ndarray, optional

The array to store the result of the morphology. If None is passed, a new array will be allocated.

mode : str, optional

The mode parameter determines how the array borders are handled. Valid modes are: 'reflect', 'constant', 'nearest', 'mirror', 'wrap', 'max', 'min', or 'ignore'. See skimage.morphology.opening. Default is 'reflect'.

cval : scalar, optional

Value to fill past edges of input if mode is 'constant'. Default is 0.0.

Returns

out : array, same shape and type as `image`

The result of the morphological white top hat.

Notes

The footprint can also be a provided as a sequence of 2-tuples where the first element of each 2-tuple is a footprint ndarray and the second element is an integer describing the number of times it should be iterated. For example footprint=[(np.ones((9, 1)), 1), (np.ones((1, 9)), 1)] would apply a 9x1 footprint followed by a 1x9 footprint resulting in a net effect that is the same as footprint=np.ones((9, 9)), but with lower computational cost. Most of the builtin footprints such as skimage.morphology.disk provide an option to automatically generate a footprint sequence of this type.

Examples

import numpy as np
from skimage.morphology import footprint_rectangle
bright_on_gray = np.array([[2, 3, 3, 3, 2],
                           [3, 4, 5, 4, 3],
                           [3, 5, 9, 5, 3],
                           [3, 4, 5, 4, 3],
                           [2, 3, 3, 3, 2]], dtype=np.uint8)
white_tophat(bright_on_gray, footprint_rectangle((3, 3)))
✓

See also

black_tophat

Aliases

  • skimage.morphology.white_tophat

Referenced by

This package