24. Color Spaces and Transforms

Color Spaces

A color space is a specific organization of colors; color spaces provide a way to categorize colors and represent them in digital images.

RGB is red-green-blue color space. You can think of this as a 3D space, in this case a cube, where any color can be represented by a 3D coordinate of R, G, and B values. For example, white has the coordinate (255, 255, 255), which has the maximum value for red, green, and blue.

There are many other ways to represent the colors in an image besides just composed of red, green, and blue values.

There is also HSV color space (hue, saturation, and value), and HLS space (hue, lightness, and saturation). These are some of the most commonly used color spaces in image analysis.

To get some intuition about these color spaces, you can generally think of Hue as the value that represents color independent of any change in brightness. So if you imagine a basic red paint color, then add some white to it or some black to make that color lighter or darker -- the underlying color remains the same and the hue for all of these colors will be the same.

HSV and HLS

On the other hand, Lightness and Value represent different ways to measure the relative lightness or darkness of a color. For example, a dark red will have a similar hue but much lower value for lightness than a light red. Saturation also plays a part in this; saturation is a measurement of colorfulness. So, as colors get lighter and closer to white, they have a lower saturation value, whereas colors that are the most intense, like a bright primary color (imagine a bright red, blue, or yellow), have a high saturation value. You can get a better idea of these values by looking at the 3D color spaces pictured below.

Most of these different color spaces were either inspired by the human vision system, and/or developed for efficient use in television screen displays and computer graphics. You can read more about the history and the derivation of HLS and HSV color spaces here.