`scipy.ndimage._morphology:grey_closing`

source: build-install/usr/lib/python3.14/site-packages/scipy/ndimage/_morphology.py:1541

Signature

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

Summary

Multidimensional grayscale closing.

Extended Summary

A grayscale closing consists in the succession of a grayscale dilation, and a grayscale erosion.

Parameters

input : array_like: Array over which the grayscale closing is to be computed.
size : tuple of ints: Shape of a flat and full structuring element used for the grayscale closing. 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 closing.
structure : array of ints, optional: Structuring element used for the grayscale closing. 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 closing 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_closing : ndarray: Result of the grayscale closing of input with structure.

Notes

The action of a grayscale closing with a flat structuring element amounts to smoothen deep local minima, whereas binary closing fills small holes.

Examples

from scipy import ndimage
import numpy as np
a = np.arange(36).reshape((6,6))
a[3,3] = 0
a
ndimage.grey_closing(a, size=(3,3))

✓

array([[ 7,  7,  8,  9, 10, 11],
       [ 7,  7,  8,  9, 10, 11],
       [13, 13, 14, 15, 16, 17],
       [19, 19, 20, 20, 22, 23],
       [25, 25, 26, 27, 28, 29],
       [31, 31, 32, 33, 34, 35]])

Aliases

scipy.ndimage.grey_closing