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Addition and Subtraction of Images using OpenCV

Last Updated : 11 Aug, 2025
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Arithmetic operations like addition and subtraction can be performed on images because digital images are stored as numerical arrays. For RGB images, these are 3-dimensional arrays (height, width, color channels), while grayscale images are represented as 2-dimensional arrays.

Step-by-Step Implementation

Let's see the step by step implementation of Addition and Subtraction Arithmetic Operations on images.

Step 1: Import Libraries

Let's import the required libraries,

  • cv2: Used for image processing tasks like reading, resizing and performing arithmetic.
  • numpy: Used for numerical operations and handling the underlying array structure of images.
  • matplotlib.pyplot: Used for plotting and displaying the images in the output cells.

Step 2: Upload the Images

Let's upload the images on which we want to perform the tasks.

  • uploaded = files.upload(): This command opens the file upload dialog. It returns a dictionary where the keys are the filenames of the uploaded files.
  • first_image_path = list(uploaded.keys()): This line takes the dictionary of uploaded files, gets a list of its keys (the filenames) and selects the first one. 
Python 
print("Upload the first image (background):")
uploaded = files.upload()
first_image_path = list(uploaded.keys())[0]

print("\nUpload the second image (overlay):")
uploaded = files.upload()
second_image_path = list(uploaded.keys())[0]

Step 3: Prepare the Images for Operations

Now we prepare our both the images for the arithmetic operations,

Python 
first_img = cv2.imread(first_image_path)
second_img = cv2.imread(second_image_path)

height = first_img.shape[0]
aspect_ratio = second_img.shape[1] / second_img.shape[0]
new_width = int(height * aspect_ratio)
resized_second_img = cv2.resize(second_img, (new_width, height))

separator = np.zeros((height, 5, 3), dtype=np.uint8)

combined_inputs = np.hstack([first_img, separator, resized_second_img])

combined_inputs_rgb = cv2.cvtColor(combined_inputs, cv2.COLOR_BGR2RGB)

print("\n--- Combined Input Images ---")
plt.figure(figsize=(12, 6))
plt.imshow(combined_inputs_rgb)
plt.title('Input Images')
plt.axis('off')
plt.show()

Output:

inputt
Input Images

Step 4: Perform the Arithmetic Operations

4.1 Image Addition: We blends the two images together using weighted addition.

Python 
dim = (first_img.shape[1], first_img.shape[0])
resized_second_img_for_blending = cv2.resize(
    second_img, dim, interpolation=cv2.INTER_AREA)

blended_img = cv2.addWeighted(
    first_img, 0.7, resized_second_img_for_blending, 0.3, 0)
blended_img_rgb = cv2.cvtColor(blended_img, cv2.COLOR_BGR2RGB)

plt.figure(figsize=(8, 8))
plt.imshow(blended_img_rgb)
plt.title('Blended Image Result')
plt.axis('off')
plt.show()

Output:

mergedd
After Addition

4.2 Image Subtraction: We subtract the pixel values of the second image from the first.

Python 
dim = (first_img.shape[1], first_img.shape[0])
resized_second_img_for_subtraction = cv2.resize(
    second_img, dim, interpolation=cv2.INTER_AREA)

subtracted_img = cv2.subtract(first_img, resized_second_img_for_subtraction)
subtracted_img_rgb = cv2.cvtColor(subtracted_img, cv2.COLOR_BGR2RGB)

print("\n--- Final Subtracted Image ---")
plt.figure(figsize=(8, 8))
plt.imshow(subtracted_img_rgb)
plt.title('Subtracted Image Result')
plt.axis('off')
plt.show()

Output:

subs
After Subtraction

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Sourabh_Sinha
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