How to handle Data, and Images(7) Merging Image

Lesson Notes in .ipynb file

How to handle Data, and Images(7) - Merging Image

Topics

• Merging Image
• Summary

Merging Image

There are two ways to add images

1. cv2.add(): uses saturation arithmetic, meaning that if addition results below 0, it returns 0. If addition results greater than 255, returns 255
2. np.add(): uses modulo arithmetic, meaning that if addition results modulo 256 (Example: addition results in 257, then it would return 257 % 256 = 1)

Because of this, when adding images, it’s much better to use cv2.add() in most cases

When using these functions, the two images must have same size

import cv2
import matplotlib.pyplot as plt

image1 = cv2.imread('chanelsun.jpg')
image2 = cv2.imread('bga.jpg')

# checking size of the image
print(image1.shape)
print(image2.shape)

# since two images have different size, we must resize
height, width = image1.shape[0], image1.shape[1]

image2 = cv2.resize(image2, (width, height))
# after resizing
print(image2.shape)

# using cv2.add() saturation arithmetic
result = cv2.add(image1, image2)
plt.imshow(cv2.cvtColor(result, cv2.COLOR_BGR2RGB))
plt.show()

# using np.add() modulo arithmetic
result = image1 + image2
plt.imshow(cv2.cvtColor(result, cv2.COLOR_BGR2RGB))
plt.show()

Output:

(720, 1280, 3)
(360, 694, 3)
(720, 1280, 3)

As you can see, cv2.add() shows a better result with sautration arithmetic.

Summary

• cv2.add(): uses saturation arithmetic, meaning that if addition results below 0, it returns 0. If addition results greater than 255, returns 255
• np.add(): uses modulo arithmetic, meaning that if addition results modulo 256 (Example: addition results in 257, then it would return 257 % 256 = 1)
• The two images you’re trying to add must be in same size.
• Due to how cv2.add() uses saturation arithmetic, it shows much better result when adding image.