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Module « scipy.ndimage »

Fonction grey_erosion - module scipy.ndimage

Signature de la fonction grey_erosion

def grey_erosion(input, size=None, footprint=None, structure=None, output=None, mode='reflect', cval=0.0, origin=0, *, axes=None) 

Description

help(scipy.ndimage.grey_erosion)

Calculate a greyscale erosion, using either a structuring element,
or a footprint corresponding to a flat structuring element.

Grayscale erosion is a mathematical morphology operation. For the
simple case of a full and flat structuring element, it can be viewed
as a minimum filter over a sliding window.

Parameters
----------
input : array_like
    Array over which the grayscale erosion is to be computed.
size : tuple of ints
    Shape of a flat and full structuring element used for the grayscale
    erosion. 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 erosion. Non-zero values give the set of
    neighbors of the center over which the minimum is chosen.
structure : array of ints, optional
    Structuring element used for the grayscale erosion. `structure`
    may be a non-flat structuring element. The `structure` array applies a
    subtractive offset for each pixel in the neighborhood.
output : array, optional
    An array used for storing the output of the erosion 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
-------
output : ndarray
    Grayscale erosion of `input`.

See Also
--------
binary_erosion, grey_dilation, grey_opening, grey_closing
generate_binary_structure, minimum_filter

Notes
-----
The grayscale erosion of an image input by a structuring element s defined
over a domain E is given by:

(input+s)(x) = min {input(y) - s(x-y), for y in E}

In particular, for structuring elements defined as
s(y) = 0 for y in E, the grayscale erosion computes the minimum of the
input image inside a sliding window defined by E.

Grayscale erosion [1]_ is a *mathematical morphology* operation [2]_.

References
----------
.. [1] https://en.wikipedia.org/wiki/Erosion_%28morphology%29
.. [2] https://en.wikipedia.org/wiki/Mathematical_morphology

Examples
--------
>>> from scipy import ndimage
>>> import numpy as np
>>> a = np.zeros((7,7), dtype=int)
>>> a[1:6, 1:6] = 3
>>> a[4,4] = 2; a[2,3] = 1
>>> a
array([[0, 0, 0, 0, 0, 0, 0],
       [0, 3, 3, 3, 3, 3, 0],
       [0, 3, 3, 1, 3, 3, 0],
       [0, 3, 3, 3, 3, 3, 0],
       [0, 3, 3, 3, 2, 3, 0],
       [0, 3, 3, 3, 3, 3, 0],
       [0, 0, 0, 0, 0, 0, 0]])
>>> ndimage.grey_erosion(a, size=(3,3))
array([[0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0],
       [0, 0, 1, 1, 1, 0, 0],
       [0, 0, 1, 1, 1, 0, 0],
       [0, 0, 3, 2, 2, 0, 0],
       [0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0]])
>>> footprint = ndimage.generate_binary_structure(2, 1)
>>> footprint
array([[False,  True, False],
       [ True,  True,  True],
       [False,  True, False]], dtype=bool)
>>> # Diagonally-connected elements are not considered neighbors
>>> ndimage.grey_erosion(a, footprint=footprint)
array([[0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0],
       [0, 0, 1, 1, 1, 0, 0],
       [0, 0, 3, 1, 2, 0, 0],
       [0, 0, 3, 2, 2, 0, 0],
       [0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0]])

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