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The HSV, or HSB, model describes colors in terms of hue, saturation, and value (brightness). Note that the range of values for each attribute is arbitrarily defined by various tools or standards. Be sure to determine the value ranges before attempting to interpret a value.
Fig. 1. HSL (a–d) and HSV (e–h). Above (a, e): cut-away 3D models of each. Below: two-dimensional plots showing two of a model's three parameters at once, holding the other constant: cylindrical shells (b, f) of constant saturation, in this case the outside surface of each cylinder; horizontal cross-sections (c, g) of constant HSL lightness or HSV value, in this case the slices halfway ...
English: HSV-RGB-comparison. Created with Inkscape. Succeeds en:Image:HSV_RGB_Comparison.png, and has the same license. A graphical representation of RGB coordinates given values for HSV. This equation () = shows origin of marked vertical axis values
RGB (red, green, blue) describes the chromaticity component of a given color, when excluding luminance. RGB itself is not a color space, it is a color model. There are many different color spaces that employ this color model to describe their chromaticities because the R/G/B chromaticities are one facet for reproducing color in CRT & LED displays.
HSV is a transformation of an RGB color space, and its components and colorimetry are relative to the RGB color space from which it was derived. HSL (hue, saturation, lightness/luminance), also known as HLS or HSI (hue, saturation, intensity) is quite similar to HSV, with "lightness" replacing "brightness".
As most definitions of color difference are distances within a color space, the standard means of determining distances is the Euclidean distance.If one presently has an RGB (red, green, blue) tuple and wishes to find the color difference, computationally one of the easiest is to consider R, G, B linear dimensions defining the color space.
Side-by-side comparison of several different color solids for the HSL, HSV, and RGB color models. Potential shapes include cubes, cylinders, cones, spheres, pyramids, bipyramids, bicones, and irregular shapes.
Color histograms are flexible constructs that can be built from images in various color spaces, whether RGB, rg chromaticity or any other color space of any dimension. A histogram of an image is produced first by discretization of the colors in the image into a number of bins, and counting the number of image pixels in each bin.