Distance between two colors:

Distance between a color and each pixel of an image:

Distance between colors defined in different color spaces:

Distance between each element of a color array and a color:

Distance between color arrays:

Color distance between two images:

Color distance between the central regions of images with different dimensions:

Highlight details in an image using a selective desaturation:

Segment components of specific colors in an image:

Detect motion by comparing two images:

This image has a strong red color cast:

The default distance considers differences in hue, luminance, and chroma:

Use DistanceFunction"DeltaH" to measure only the differences in hue:

Cluster a list of colors based on their distance:

Sort a list of colors using their perceptual distance from a reference color:

Compare to sorting based on RGB values:

ColorDistance is equivalent to EuclideanDistance of the color in the LABColor space:

The distance between a color and itself is always zero:

The distance between a color represented in two color spaces is zero:

Notice that this distance may be nonzero if the color is not available in the new color space:

The alpha channel is not used when computing the distance:

For RGB colors, the typical range of distances for each method is as follows:

Define a sample set using the boundary of the RGB cube:

Compute all pairwise distances between the sample colors:

Compute the range:

Not all the color distances are metrics in a mathematical sense:

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"CIE94" and "CMC" are not symmetric:

"CIE94", "CIE2000", "CMC", and "DeltaH" do not always satisfy the triangle inequality:

Simulated frequencies of satisfying the triangular inequality depend on the specified distance:

"CIE2000" is one of the latest standards, introducing many improvements over the simple Lab distance. It is perceptually more accurate compared to "CIE76" and "CIE94":

Show constant-distance curves on the plane for a fixed lightness, :

However, "CIE2000" is computationally more expensive compared to the older metrics:

ImageDistance by default computes the Euclidean distance between two images in the RGB space:

ColorDistance by default computes the Euclidean distance between two pixels in the LAB space:

ColorDistance returns the distance between the central regions of images with different dimensions:

The distance between two images may be identically zero if their overlapping regions coincide:

Colorize an image using distance maps from three primary colors: