Python Pillow - ImageChops.subtract() Function

---

---

The PIL.ImageChops.subtract() function is used to subtract one image (image2) from another image (image1). After the subtraction, the result is divided by a specified scale and then an offset is added. The mathematical representation of this operation is given by the formula −

$$\mathrm{out\:=\:((image1\:-\:image2)/scale\:+\:offset)}$$

Similar to ImageChops.add, this operation is not reversible due to the data type being uint8. When using ImageChops.subtract, if the resulting value is negative, it is clipped to zero. This clipping to the range [0, 255] leads to data loss, and the original image cannot be accurately reconstructed from the result.

Syntax

Following is the syntax of the function −

PIL.ImageChops.subtract(image1, image2, scale=1.0, offset=0)

Parameters

Here are the details of this function parameters −

• image1 − This is the first input image.

• image2 − This is the second input image.

• scale (optional, default value: 1.0) − Scale is a factor by which the result of subtracting image1 and image2 is divided. If you omit this parameter, it defaults to 1.0.

• offset (optional, default value: 0.0) − Offset is a value that is added to the result after the division by the scale. If you don't provide an offset value, it defaults to 0.0.

Return Value

This Function returns the Image object.

Examples

Example 1

In this example, two random RGB images (image1 and image2) are created using NumPy arrays. Then the ImageChops.subtract function is applied to see how the pixel values of the two images are represented in the output image after performing the subtraction.

from PIL import Image, ImageChops
import numpy as np

# Create two random RGB images
image1 = Image.fromarray(np.array([(235, 64, 3), (255, 0, 0), (255, 255, 0), (255, 255, 255), (164, 0, 3)]), mode="RGB")
print("Pixel values of image1 at (0, 0):", image1.getpixel((0, 0)))

image2 = Image.fromarray(np.array([(255, 14, 3), (25, 222, 0), (255, 155, 0), (255, 55, 100), (180, 0, 78)]), mode="RGB")
print("Pixel values of image2 at (0, 0):", image2.getpixel((0, 0)))

# Subtract the two images
result = ImageChops.subtract(image1, image2)
print("Pixel values of the result at (0, 0) after subtraction:", result.getpixel((0, 0)))

Output

Pixel values of image1 at (0, 0): (235, 0, 0)
Pixel values of image2 at (0, 0): (255, 0, 0)
Pixel values of the result at (0, 0) after subtraction: (0, 0, 0)

We can observe the output, the pixel at (0, 0) is (0, 0, 0), as the subtraction (235 - 255) is clipped to 0.

Example 2

The following example subtract the second image from the first with default parameters (scale=1.0, offset=0.0).

from PIL import Image, ImageChops

# Open two image files
image1 = Image.open('Images/TP logo.jpg')
image2 = Image.open('Images/Rose_.jpg')

# Subtract the second image from the first with default parameters (scale=1.0, offset=0.0)
result = ImageChops.subtract(image1, image2)

# Display the input and resulting images
image1.show()
image2.show()
result.show()

Output

Input Image 1

Input Image 2

Output Image

Example 3

Here is an example that subtracts the second image from the first with specific scale and offset values.

from PIL import Image, ImageChops

# Open two image files
image1 = Image.open('Images/Rose_.jpg')
image2 = Image.open('Images/TP logo.jpg')

# Subtract the second image from the first with specific scale and offset values
result = ImageChops.subtract(image1, image2, scale=5.0, offset=100)

# Display the input and resulting images
image1.show()
image2.show()
result.show()

Output

Input Image 1

Input Image 2

Output Image