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Module « scipy.ndimage »
Signature de la fonction grey_opening
def grey_opening(input, size=None, footprint=None, structure=None, output=None, mode='reflect', cval=0.0, origin=0, *, axes=None)
Description
help(scipy.ndimage.grey_opening)
Multidimensional grayscale opening.
A grayscale opening consists in the succession of a grayscale erosion,
and a grayscale dilation.
Parameters
----------
input : array_like
Array over which the grayscale opening is to be computed.
size : tuple of ints
Shape of a flat and full structuring element used for the grayscale
opening. Optional if `footprint` or `structure` is provided.
footprint : array of ints, optional
Positions of non-infinite elements of a flat structuring element
used for the grayscale opening.
structure : array of ints, optional
Structuring element used for the grayscale opening. `structure`
may be a non-flat structuring element. The `structure` array applies
offsets to the pixels in a neighborhood (the offset is additive during
dilation and subtractive during erosion).
output : array, optional
An array used for storing the output of the opening may be provided.
mode : {'reflect', 'constant', 'nearest', 'mirror', 'wrap'}, optional
The `mode` parameter determines how the array borders are
handled, where `cval` is the value when mode is equal to
'constant'. Default is 'reflect'
cval : scalar, optional
Value to fill past edges of input if `mode` is 'constant'. Default
is 0.0.
origin : scalar, optional
The `origin` parameter controls the placement of the filter.
Default 0
axes : tuple of int or None
The axes over which to apply the filter. If None, `input` is filtered
along all axes. If an `origin` tuple is provided, its length must match
the number of axes.
Returns
-------
grey_opening : ndarray
Result of the grayscale opening of `input` with `structure`.
See Also
--------
binary_opening, grey_dilation, grey_erosion, grey_closing
generate_binary_structure
Notes
-----
The action of a grayscale opening with a flat structuring element amounts
to smoothen high local maxima, whereas binary opening erases small objects.
References
----------
.. [1] https://en.wikipedia.org/wiki/Mathematical_morphology
Examples
--------
>>> from scipy import ndimage
>>> import numpy as np
>>> a = np.arange(36).reshape((6,6))
>>> a[3, 3] = 50
>>> a
array([[ 0, 1, 2, 3, 4, 5],
[ 6, 7, 8, 9, 10, 11],
[12, 13, 14, 15, 16, 17],
[18, 19, 20, 50, 22, 23],
[24, 25, 26, 27, 28, 29],
[30, 31, 32, 33, 34, 35]])
>>> ndimage.grey_opening(a, size=(3,3))
array([[ 0, 1, 2, 3, 4, 4],
[ 6, 7, 8, 9, 10, 10],
[12, 13, 14, 15, 16, 16],
[18, 19, 20, 22, 22, 22],
[24, 25, 26, 27, 28, 28],
[24, 25, 26, 27, 28, 28]])
>>> # Note that the local maximum a[3,3] has disappeared
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