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AutoContrast

Targets:
image
volume
Image Types:uint8, float32

Automatically adjust image contrast by stretching the intensity range.

This transform provides two methods for contrast enhancement:

  1. CDF method (default): Uses cumulative distribution function for more gradual adjustment
  2. PIL method: Uses linear scaling like PIL.ImageOps.autocontrast

The transform can optionally exclude extreme values from both ends of the intensity range and preserve specific intensity values (e.g., alpha channel).

Arguments
cutoff
float
0

Percentage of pixels to exclude from both ends of the histogram. Range: [0, 100]. Default: 0 (use full intensity range)

  • 0 means use the minimum and maximum intensity values found
  • 20 means exclude darkest and brightest 20% of pixels
ignore
int | None

Intensity value to preserve (e.g., alpha channel). Range: [0, 255]. Default: None

  • If specified, this intensity value will not be modified
  • Useful for images with alpha channel or special marker values
method
cdf | pil
cdf

Algorithm to use for contrast enhancement. Default: "cdf"

  • "cdf": Uses cumulative distribution for smoother adjustment
  • "pil": Uses linear scaling like PIL.ImageOps.autocontrast
p
float
0.5

Probability of applying the transform. Default: 0.5

Examples
>>> import albumentations as A
>>> # Basic usage
>>> transform = A.AutoContrast(p=1.0)
>>>
>>> # Exclude extreme values
>>> transform = A.AutoContrast(cutoff=20, p=1.0)
>>>
>>> # Preserve alpha channel
>>> transform = A.AutoContrast(ignore=255, p=1.0)
>>>
>>> # Use PIL-like contrast enhancement
>>> transform = A.AutoContrast(method="pil", p=1.0)
Notes
  • The transform processes each color channel independently
  • For grayscale images, only one channel is processed
  • The output maintains the same dtype as input
  • Empty or single-color channels remain unchanged