Arithmetic operations on Images in OpenCV

Arithmetic operations on images using OpenCV are fundamental tasks in computer vision and image processing. These operations can be used for various purposes such as image blending, brightness adjustments, and more.

Here's a rundown of some basic arithmetic operations on images using OpenCV in Python:

Image Addition:

import cv2
import numpy as np

img1 = cv2.imread('path_to_image1.jpg')
img2 = cv2.imread('path_to_image2.jpg')

# Ensure the images are the same size or resize as necessary
# img2 = cv2.resize(img2, (img1.shape[1], img1.shape[0]))

result = cv2.add(img1, img2)

Image Subtraction:
```
result = cv2.subtract(img1, img2)
```

Image Blending (weighted addition):

alpha = 0.7  # weight of the first image (img1)
beta = 0.3   # weight of the second image (img2)
gamma = 0    # scalar added to each sum

blend = cv2.addWeighted(img1, alpha, img2, beta, gamma)

Bitwise Operations (useful for masking and ROI extraction):

Bitwise AND:

result = cv2.bitwise_and(img1, img2, mask=None)

Bitwise OR:

result = cv2.bitwise_or(img1, img2, mask=None)

Bitwise NOT:

result = cv2.bitwise_not(img1, mask=None)

Bitwise XOR:

result = cv2.bitwise_xor(img1, img2, mask=None)

Brightness Adjustment: Adjusting the brightness of an image can be done by adding or subtracting a scalar value.

M = np.ones(img1.shape, dtype="uint8") * 50
brighter = cv2.add(img1, M)  # Increase brightness
darker = cv2.subtract(img1, M)  # Decrease brightness

When performing arithmetic operations on images, always be aware of the data type and its range. Most images in OpenCV are represented as uint8 with values ranging from 0 to 255. Operations can result in overflow or underflow which might lead to unintended results, so always ensure that the resultant values are clipped within the valid range.

Also, always make sure that images used in arithmetic operations have the same size (height, width) and number of channels. If not, you'll need to resize or crop the images as necessary before performing the operations.

1. Performing arithmetic operations on images with OpenCV:

OpenCV allows for arithmetic operations such as addition, subtraction, multiplication, and division on images, providing a flexible way to manipulate pixel values.

2. Addition and subtraction of images in OpenCV:

import cv2
import numpy as np

# Load two images
image1 = cv2.imread('image1.jpg')
image2 = cv2.imread('image2.jpg')

# Add images
addition_result = cv2.add(image1, image2)

# Subtract images
subtraction_result = cv2.subtract(image1, image2)

# Display results
cv2.imshow('Addition Result', addition_result)
cv2.imshow('Subtraction Result', subtraction_result)
cv2.waitKey(0)
cv2.destroyAllWindows()

3. Multiplying and dividing images in OpenCV:

# Multiply images
multiplication_result = cv2.multiply(image1, image2)

# Divide images
division_result = cv2.divide(image1, image2)

# Display results
cv2.imshow('Multiplication Result', multiplication_result)
cv2.imshow('Division Result', division_result)
cv2.waitKey(0)
cv2.destroyAllWindows()

4. OpenCV image arithmetic examples and techniques:

Explore additional image arithmetic operations such as bitwise AND, OR, XOR, and NOT.

# Bitwise AND
bitwise_and_result = cv2.bitwise_and(image1, image2)

# Bitwise OR
bitwise_or_result = cv2.bitwise_or(image1, image2)

# Bitwise XOR
bitwise_xor_result = cv2.bitwise_xor(image1, image2)

# Bitwise NOT
bitwise_not_result = cv2.bitwise_not(image1)

# Display results
cv2.imshow('Bitwise AND Result', bitwise_and_result)
cv2.imshow('Bitwise OR Result', bitwise_or_result)
cv2.imshow('Bitwise XOR Result', bitwise_xor_result)
cv2.imshow('Bitwise NOT Result', bitwise_not_result)
cv2.waitKey(0)
cv2.destroyAllWindows()

5. Sample code for image arithmetic in OpenCV:

A complete sample code showcasing basic image arithmetic operations.

6. Arithmetic operations for image enhancement in OpenCV:

Use arithmetic operations for image enhancement, such as adjusting brightness and contrast.

# Brightness adjustment
brightness_factor = 1.5
brightness_result = cv2.addWeighted(image1, 1, np.zeros(image1.shape, image1.dtype), 0, brightness_factor)

# Contrast adjustment
contrast_factor = 1.5
contrast_result = cv2.addWeighted(image1, contrast_factor, np.zeros(image1.shape, image1.dtype), 0, 0)

# Display results
cv2.imshow('Brightness Adjustment', brightness_result)
cv2.imshow('Contrast Adjustment', contrast_result)
cv2.waitKey(0)
cv2.destroyAllWindows()

7. Image blending and combining with arithmetic in OpenCV:

Combine images through blending and alpha blending techniques.

# Image blending
alpha = 0.5
blend_result = cv2.addWeighted(image1, alpha, image2, 1 - alpha, 0)

# Display result
cv2.imshow('Image Blending Result', blend_result)
cv2.waitKey(0)
cv2.destroyAllWindows()

8. Python OpenCV arithmetic operations for image processing:

Combine various arithmetic operations for advanced image processing tasks.

# Custom arithmetic operation (e.g., image1 - 0.5 * image2)
custom_result = cv2.subtract(image1, cv2.multiply(image2, 0.5))

# Display result
cv2.imshow('Custom Arithmetic Result', custom_result)
cv2.waitKey(0)
cv2.destroyAllWindows()