We can compute the (partial) derivatives of a digital image using finite differences. In this section, let us discuss how to compute the image derivatives, Gradient and Laplacian, and why they are useful. As usual, let us start by importing the required libraries, as shown in the following code block:
import numpy as npfrom scipy import signal, misc, ndimagefrom skimage import filters, feature, img_as_floatfrom skimage.io import imreadfrom skimage.color import rgb2grayfrom PIL import Image, ImageFilterimport matplotlib.pylab as pylab
