scipy.ndimage.grey_opening#

scipy.ndimage.grey_opening(input, size=None, footprint=None, structure=None, output=None, mode='reflect', cval=0.0, origin=0)[source]#

Multidimensional grayscale opening.

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

Parameters

inputarray_like: Array over which the grayscale opening is to be computed.
sizetuple of ints: Shape of a flat and full structuring element used for the grayscale opening. Optional if footprint or structure is provided.
footprintarray of ints, optional: Positions of non-infinite elements of a flat structuring element used for the grayscale opening.
structurearray of ints, optional: Structuring element used for the grayscale opening. structure may be a non-flat structuring element.
outputarray, 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’
cvalscalar, optional: Value to fill past edges of input if mode is ‘constant’. Default is 0.0.
originscalar, optional: The origin parameter controls the placement of the filter. Default 0

Returns

grey_openingndarray: 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
>>> 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

scipy.ndimage.grey_erosion

scipy.ndimage.iterate_structure