transforms pixel values of image so that its histogram is nearly flat.


modifies pixel values of image so that its histogram matches the probability density function (PDF) of the distribution dist.


matches the histogram of image with the histogram of the reference image ref.


transforms values xi.



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Basic Examples  (3)

Equalize the histogram of an image:

Match the image histogram with a reference image:

Match histograms of two color images:

Scope  (6)

Data  (5)

Transform a dataset so that it is distributed normally:

Transform multiple datasets so that they are distributed uniformly:

Make the pixel values follow a normal distribution:

Compare the two histograms:

Reshape the image histogram so that each channel follows a normal distribution:

Equalize the histogram of a 3D image:

Parameters  (1)

Reducing the number of quantiles will affect the quality of the transformation function:

Applications  (6)

Basic Applications  (3)

Equalize only the brightness of a color image:

Equalize only the saturation of a color image:

Create an image effect by composing an image and its equalized version:

Color Transformation  (2)

Transfer colors between images:

Perform the transfer in the Lab color space instead:

Colorize a grayscale image by searching for neighborhoods with similar luminance in a color image:

Convert images into a color space where luminance and color information are not correlated:

Normalize the luminance images by reshaping the histogram:

Compute luminance neighborhood statistics and construct a function that gives the color associated to the closest luminance neighborhood:

For each pixel of the grayscale image, create a new pixel by preserving the initial luminance and selecting the nearest color in the reference image:

Multidimensional Probability Density Function Transfer  (1)

Reshape the histogram of a multidimensional dataset by iteratively reshaping random marginal histograms:

Reshape a bivariate dataset to match binormal samples:

Assess the result by visualizing the joint histograms before and after the transfer:

Test whether the transformed data is distributed according to the reference distribution:

Reshape the joint histogram of the hue and the saturation to a circle:

Visualize the joint histograms before and after the transfer:

Create the corresponding result image:

Reshape the 3D joint histogram of an RGB image:

Properties & Relations  (1)

HistogramTransformInterpolation can be used to get the transformation function used in HistogramTransform:

Introduced in 2012
Updated in 2014