The white top-hat of an image computes the bright spots smaller than the structuring element. It is defined as the difference image of the original image and its morphological opening. Similarly, the black top-hat of an image computes the dark spots smaller than the structuring element. It is defined as the difference image of the morphological closing image of original image. The dark spots in the original image become bright spots after the black top-hat operation. The following code block demonstrates how to use these two morphological operations using the scikit-image morphology module functions on the input binary image of Tagore:

from skimage.morphology import white_tophat, black_tophat, square
im = imread('../images/tagore.png')[...,3]
im[im <= 0.5] = 0
im[im > 0.5] = 1
im1 = white_tophat(im, square(5))
im2 = black_tophat(im, square(5))
pylab.figure(figsize=(20,15))
pylab.subplot(1,2,1), plot_image(im1, 'white tophat')
pylab.subplot(1,2,2), plot_image(im2, 'black tophat')
pylab.show()

The following screenshot shows the output for the white and black top-hats: