We can read and display images in Python as follows. In image processing we can

Question

We can read and display images in Python as follows. In image processing we can think of the image u as a function of two variables u(x, y) defined on some region ohm R^2. While implementing some algorithms, one has to maintain proper boundary conditions. For example, Neumann boundary condition implies that deltau n = 0 on the boundary, where n is the outward pointing unit normal to the boundary. One way to achieve this is to extend the boundary by some factor. For example, if u is a 512 times 512 image, we obtain another image U with size 514 times 514. The image U Ls obtained expanding the image u by 1 pixel unit on all four sides, and the expansion is done by repeating the boundary values, i.e. the image U has top two rows same as the first row of u, bottom two rows same as the bottom row of u, and so one. Write a python function expand(u, n), which expands the image u by n pixels on all four sides.

Explanation / Answer

import cv2

def expand(u,n):
   n=25
   r = 100.0 / u.shape[1]
   # set the dimension to resize by n pixels
   dim = (n, int(u.shape[0] * r))
   # perform actual resizing of the image and display it
   resized = cv2.resize(u, dim, interpolation = cv2.INTER_AREA)
   cv2.imshow("resized", resized)
   cv2.waitKey(0)
   return

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