How to do it...

Perform the following steps:

1. Import the packages:

import math
import cv2
import numpy as np
import matplotlib.pyplot as plt

2. Read the test image:

image = cv2.imread('../data/Lena.png')

3. Create an 11x11 sharpening kernel:

KSIZE = 11
ALPHA = 2

kernel = cv2.getGaussianKernel(KSIZE, 0)
kernel = -ALPHA * kernel @ kernel.T
kernel[KSIZE//2, KSIZE//2] += 1 + ALPHA

4. Filter the image using the kernel we just created:

filtered = cv2.filter2D(image, -1, kernel)

5. Visualize the results:

plt.figure(figsize=(8,4))
plt.subplot(121)
plt.axis('off')
plt.title('image')
plt.imshow(image[:, :, [2, 1, 0]])
plt.subplot(122)
plt.axis('off')
plt.title('filtered')
plt.imshow(filtered[:, :, [2, 1, 0]])
plt.tight_layout(True)
plt.show()