dilation(image, selem=None, out=None, shift_x=False, shift_y=False)
Morphological dilation sets a pixel at (i,j) to the maximum over all pixels in the neighborhood centered at (i,j). Dilation enlarges bright regions and shrinks dark regions.
For :None:None:`uint8` (and :None:None:`uint16` up to a certain bit-depth) data, the lower algorithm complexity makes the skimage.filters.rank.maximum
function more efficient for larger images and structuring elements.
Image array.
The neighborhood expressed as a 2-D array of 1's and 0's. If None, use cross-shaped structuring element (connectivity=1).
The array to store the result of the morphology. If None, is passed, a new array will be allocated.
shift structuring element about center point. This only affects eccentric structuring elements (i.e. selem with even numbered sides).
The result of the morphological dilation.
Return greyscale morphological dilation of an image.
>>> # Dilation enlarges bright regionsSee :
... import numpy as np
... from skimage.morphology import square
... bright_pixel = np.array([[0, 0, 0, 0, 0],
... [0, 0, 0, 0, 0],
... [0, 0, 1, 0, 0],
... [0, 0, 0, 0, 0],
... [0, 0, 0, 0, 0]], dtype=np.uint8)
... dilation(bright_pixel, square(3)) array([[0, 0, 0, 0, 0], [0, 1, 1, 1, 0], [0, 1, 1, 1, 0], [0, 1, 1, 1, 0], [0, 0, 0, 0, 0]], dtype=uint8)
The following pages refer to to this document either explicitly or contain code examples using this.
skimage.filters.rank.generic.maximum
skimage.morphology.grey.dilation
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