Arithmetic Operations on Images using OpenCV | Set-1 (Addition and Subtraction)
Arithmetic Operations like Addition, Subtraction, and Bitwise Operations(AND, OR, NOT, XOR) can be applied to the input images. These operations can be helpful in enhancing the properties of the input images. The Image arithmetics are important for analyzing the input image properties. The operated images can be further used as an enhanced input image, and many more operations can be applied for clarifying, thresholding, dilating etc of the image.
Addition of Image:
We can add two images by using function cv2.add(). This directly adds up image pixels in the two images.
Syntax: cv2.add(img1, img2)
But adding the pixels is not an ideal situation. So, we use cv2.addweighted(). Remember, both images should be of equal size and depth.
Syntax: cv2.addWeighted(img1, wt1, img2, wt2, gammaValue)
Parameters:
img1: First Input Image array(Single-channel, 8-bit or floating-point)
wt1: Weight of the first input image elements to be applied to the final image
img2: Second Input Image array(Single-channel, 8-bit or floating-point)
wt2: Weight of the second input image elements to be applied to the final image
gammaValue: Measurement of light
Images used as Input:
Input Image1: 
Input Image2: 
Below is the code:
# Python programe to illustrate # arithmetic operation of # addition of two images # organizing imports import cv2 import numpy as np # path to input images are specified and # images are loaded with imread command image1 = cv2.imread('input1.jpg') image2 = cv2.imread('input2.jpg') # cv2.addWeighted is applied over the # image inputs with applied parameters weightedSum = cv2.addWeighted(image1, 0.5, image2, 0.4, 0) # the window showing output image # with the weighted sum cv2.imshow('Weighted Image', weightedSum) # De-allocate any associated memory usage if cv2.waitKey(0) & 0xff == 27: cv2.destroyAllWindows() |
chevron_right
filter_none
Output: 
Subtraction of Image:
Just like addition, we can subtract the pixel values in two images and merge them with the help of cv2.subtract(). The images should be of equal size and depth.
Syntax: cv2.subtract(src1, src2)
Images used as Input:
Input Image1: 
Input Image2: 
Below is the code:
# Python programe to illustrate # arithmetic operation of # subtraction of pixels of two images # organizing imports import cv2 import numpy as np # path to input images are specified and # images are loaded with imread command image1 = cv2.imread('input1.jpg') image2 = cv2.imread('input2.jpg') # cv2.subtract is applied over the # image inputs with applied parameters sub = cv2.subtract(image1, image2) # the window showing output image # with the subtracted image cv2.imshow('Subtracted Image', sub) # De-allocate any associated memory usage if cv2.waitKey(0) & 0xff == 27: cv2.destroyAllWindows() |
chevron_right
filter_none
Output: 
Recommended Posts:
- Arithmetic Operations on Images using OpenCV | Set-2 (Bitwise Operations on Binary Images)
- Addition and Blending of images using OpenCV in Python
- Arithmetic operations using OpenCV | Python
- Python | Background subtraction using OpenCV
- Python | Grayscaling of Images using OpenCV
- Stitching input images (panorama) using OpenCV with C++
- Python | Denoising of colored images using opencv
- Draw geometric shapes on images using OpenCV
- Erosion and Dilation of images using OpenCV in python
- Python | Create video using multiple images using OpenCV
- Python | Intensity Transformation Operations on Images
- Python | Arithmetic operations in excel file using openpyxl
- Python | Subtraction of dictionaries
- Reading images in Python
- Working with Images in Python
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.
