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Chromaticity versus chrominance

Color spaces can generally be classified as chromaticity or chrominance based. Both are different styles of defining color. Chromaticity is “color” defined independent of luminance (or the equivalent of luminance in a particular color space). Suppose you used a neutral density filter on a camera or changed the intensity of the lighting. The chromaticity values of the image would stay the same. In a chrominance based color space, the chrominance values of the image will change if the intensity of light is varied as in the example. Chrominance can be thought of as a paint/pigment that adds “colorfulness” to an image. If mixing a gallon of paint, a certain amount of such a pigment would be needed. If mixing twice as much paint, twice as much of the pigment would be needed. And for three times the paint, three times the pigment would be needed, etc. etc. In a chromaticity based system, you would define color as the proportion to mix all the paints/pigments together.

If you are concerned with compression/bandwidth efficiency and/or uniform distribution of JNDs (just noticeable differences), then chrominance based color spaces tend to be more useful. For color correction however, chrominance based color spaces can cause problems if changing the luminance channel (or equivalent) without making similar changes to chrominance.

The first image below shows the original image. The second image below shows the L* channel in LAB space being halved in Photoshop. The third image shows the Luminosity channel being halved via a Levels adjustment Layer and the Luminosity blending mode (again, in Photoshop). The fourth image shows the RGB channels being halved - halving the luminance channel in a chromaticity based color space would yield similar/analogous results.


L* channel reduced 50% in LAB space (Photoshop).

Luminosity channel reduced 50% (Photoshop).

RGB channels reduced 50%. *Halving the luminance channel in a chromaticity based color space will produce results similar to this.

The chrominance based color space adjustments cause the resulting image to have oversaturated colors. To go back to the paint mixing analogy, there is now too much “colorfulness” paint. This can be avoided by doing adjustments in a chromaticity based color space. It is possible to convert any chrominance based color space into a chromaticity based one by dividing chrominance by luminance (or its equivalent) to yield chromaticity. Most programs do not do this unfortunately. In some situations like the one here, it is possible to get this by reducing the chrominance components by the same amount. However, this generally will not work if curve-based manipulations (e.g. s shaped curves) are applied to the luminance channel.

If doing color correction work with chrominance based color spaces or transformations, this is something to watch out for! If the adjustments are very minor then the error will be low and likely at an acceptable level. But push the image too much and you run the risk of unintended saturation shifts.


Kerr, Douglas. “Chromaticity and Chrominance in Color Definition”


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