scipy.ndimage.grey_closing¶

scipy.ndimage.
grey_closing
(input, size=None, footprint=None, structure=None, output=None, mode='reflect', cval=0.0, origin=0)[source]¶ Multidimensional grayscale closing.
A grayscale closing consists in the succession of a grayscale dilation, and a grayscale erosion.
 Parameters
 inputarray_like
Array over which the grayscale closing is to be computed.
 sizetuple of ints
Shape of a flat and full structuring element used for the grayscale closing. Optional if footprint or structure is provided.
 footprintarray of ints, optional
Positions of noninfinite elements of a flat structuring element used for the grayscale closing.
 structurearray of ints, optional
Structuring element used for the grayscale closing. structure may be a nonflat structuring element.
 outputarray, 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’
 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_closingndarray
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.
References
Examples
>>> from scipy import ndimage >>> a = np.arange(36).reshape((6,6)) >>> a[3,3] = 0 >>> a array([[ 0, 1, 2, 3, 4, 5], [ 6, 7, 8, 9, 10, 11], [12, 13, 14, 15, 16, 17], [18, 19, 20, 0, 22, 23], [24, 25, 26, 27, 28, 29], [30, 31, 32, 33, 34, 35]]) >>> 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]]) >>> # Note that the local minimum a[3,3] has disappeared