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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.
The difference is that a perfectly light color in HSL is pure white; but a perfectly bright color in HSV is analogous to shining a white light on a colored object. I.e. shining a bright white light on a red object causes the object to still appear red, just brighter and more intense.
The HSL and HSV model-builders took an RGB cube – with constituent amounts of red, green, and blue light in a color denoted R, G, B ∈ [E] – and tilted it on its corner, so that black rested at the origin with white directly above it along the vertical axis, then measured the hue of the colors in the cube by their angle around that axis ...
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.
RGB is a device-dependent color model: different devices detect or reproduce a given RGB value differently, since the color elements (such as phosphors or dyes) and their response to the individual red, green, and blue levels vary from manufacturer to manufacturer, or even in the same device over time.
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.