mid-range of the RGB components. This definition also puts the primary and secondary colors into a plane, but a plane passing halfway between white and black. The resulting color solid is a double-cone similar to Ostwald's, shown above. A more perceptually relevant alternative is to use luma, , as a lightness dimension (). Luma is the weighted average of gamma-corrected R, G, and B, based on their contribution to perceived lightness, long used as the monochromatic dimension in color television broadcast. For sRGB, the Rec. 709 primaries yield , digital NTSC uses according to Rec. 601 and some other primaries are also in use which result in different coefficients. (SDTV) (Adobe) (HDTV) (UHDTV, HDR) All four of these leave the neutral axis alone. That is, for colors with , any of the four formulations yields a lightness equal to the value of R, G, or B. For a graphical comparison, see fig. 13 below. Saturation When encoding colors in a hue/lightness/chroma or hue/value/chroma model (using the definitions from the previous two sections), not all combinations of lightness (or value) and chroma are meaningful: that is, half of the colors denotable using , , and fall outside the RGB gamut (the gray parts of the slices in figure 14). The creators of these models considered this a problem for some uses. For example, in a color selection interface with two of the dimensions in a rectangle and the third on a slider, half of that rectangle is made of unused space. Now imagine we have a slider for lightness: the user's intent when adjusting this slider is potentially ambiguous: how should the software deal with out-of-gamut colors? Or conversely, If the user has selected as colorful as possible a dark purple and then shifts the lightness slider upward, what should be done: would the user prefer to see a lighter purple still as colorful as possible for the given hue and lightness or a lighter purple of exactly the same chroma as the original color To solve problems such as these, the HSL and HSV models scale the chroma so that it always fits into the range for every combination of hue and lightness or value, calling the new attribute saturation in both cases (fig. 14). To calculate either, simply divide the chroma by the maximum chroma for that value or lightness. The HSI model commonly used for computer vision, which