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# scipy.ndimage.grey_closing

`scipy.ndimage.``grey_closing`(input, size=None, footprint=None, structure=None, output=None, mode='reflect', cval=0.0, origin=0)

  Multi-dimensional greyscale closing.

  A greyscale closing consists in the succession of a greyscale dilation, and a greyscale 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. output : array, optional An array used for storing the ouput 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
  Returns: | grey_closing : ndarray Result of the grayscale closing of input with structure.

  See also

  `binary_closing`, `grey_dilation`, `grey_erosion`, `grey_opening`, `generate_binary_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

  [R145] | http://en.wikipedia.org/wiki/Mathematical_morphology

  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