Python Pillow - ImageOps.autocontrast() Function

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The PIL.ImageOps.autocontrast function is designed to maximize (normalize) the contrast of an image. It achieves this by calculating a histogram of the input image (or a specified mask region), removing a specified percentage (cutoff) of the lightest and darkest pixels from the histogram, and then remapping the image so that the darkest pixel becomes black (0), and the lightest becomes white (255).

Syntax

Following is the syntax of the function −

PIL.ImageOps.autocontrast(image, cutoff=0, ignore=None, mask=None, preserve_tone=False)

Parameters

Here are the details of this function parameters −

• image − The input image to process.

• cutoff − The percent to cut off from the histogram on the low and high ends. It can be either a tuple of (low, high) or a single number for both ends.

• ignore − The background pixel value; use None for no background.

• mask − If provided, the histogram used in the contrast operation is computed using pixels within the specified mask. If no mask is given, the entire image is used for histogram computation.

• preserve_tone − An optional parameter introduced in version 8.2.0. When set to True, it preserves image tone in a Photoshop-like style autocontrast.

Return Value

The function returns an image representing the result of the autocontrast operation.

Examples

Example 1

Here's an example of how to use the autocontrast function with default parameters.

from PIL import Image, ImageOps

# Open an image
original_image = Image.open("Images/image.jpg")

# Apply autocontrast with default parameters
result_image = ImageOps.autocontrast(original_image)

# Display the input and resulting images
original_image.show()
result_image.show()

Output

Input Image

Output Image

Example 2

In this example, we set a custom cutoff percentage (5%) and specify a background pixel value to be ignored during the autocontrast operation.

from PIL import Image, ImageOps

# Open an image
original_image = Image.open("Images/image.jpg")

# Cut off 5% from both low and high ends of the histogram
cutoff_percentage = 5

# Ignore pixels with value 50 as background
ignore_pixel_value = 50 

# Apply autocontrast with custom parameters
result_image = ImageOps.autocontrast(original_image, cutoff=cutoff_percentage, ignore=ignore_pixel_value)

# Display the input and resulting images
original_image.show()
result_image.show()

Output

Input Image

Output Image

Example 3

Here's another example demonstrating the use of PIL.ImageOps.autocontrast with a mask. we create a circular mask and apply it to the autocontrast function.

from PIL import Image, ImageOps

# Open an image
original_image = Image.open("Images/image.jpg")

# Create a mask (an example using a circular mask)
mask_radius = 100
mask = Image.new("L", original_image.size, 0)

mask.paste(255, (original_image.width // 2 - mask_radius, original_image.height // 2 - mask_radius),
   Image.new("L", (mask_radius * 2, mask_radius * 2), 255))

# Apply autocontrast with a mask
result_image = ImageOps.autocontrast(original_image, mask=mask)

# Display the input and resulting images
original_image.show()
result_image.show()

Output

Input Image

Output Image