RGB Түс Моделінің Баламалы Түрлері: HSL, HSV және HSI

Alternative representations of the RGB color model

HSL and HSV are the two most common cylindrical coordinate representations of points in an RGB color model. The two representations rearrange the geometry of RGB in an attempt to be more intuitive and perceptually relevant than the cartesian (cube) representation. Developed in the 1970s for computer graphics applications, HSL and HSV are used today in color pickers, in image editing software, and less commonly in image analysis and computer vision. HSL stands for hue, saturation, and lightness, and is often also called HLS. HSV stands for hue, saturation, and value, and is also often called HSB (B for brightness). A third model, common in computer vision applications, is HSI, for hue, saturation, and intensity. However, while typically consistent, these definitions are not standardized, and any of these abbreviations might be used for any of these three or several other related cylindrical models. (For technical definitions of these terms, see below.) In each cylinder, the angle around the central vertical axis corresponds to "hue", the distance from the axis corresponds to "saturation", and the distance along the axis corresponds to "lightness", "value" or "brightness". Note that while "hue" in HSL and HSV refers to the same attribute, their definitions of "saturation" differ dramatically. Because HSL and HSV are simple transformations of device dependent RGB models, the physical colors they define depend on the colors of the red, green, and blue primaries of the device or of the particular RGB space, and on the gamma correction used to represent the amounts of those primaries. Each unique RGB device therefore has unique HSL and HSV spaces to accompany it, and numerical HSL or HSV values describe a different color for each basis RGB space. Both of these representations are used widely in computer graphics, and one or the other of them is often more convenient than RGB, but both are also criticized for not adequately separating color making attributes, or for their lack of perceptual uniformity. Other more computationally intensive models, such as CIELAB or CIECAM02 are said to better achieve these goals.

HSL and HSV are both cylindrical geometries (fig. 2), with hue, their angular dimension, starting at the red primary at 0°, passing through the green primary at 120° and the blue primary at 240°, and then wrapping back to red at 360°. In each geometry, the central vertical axis comprises the neutral, achromatic, or gray colors ranging, from top to bottom, white at lightness 1 (value 1) to black at lightness 0 (value 0). In both geometries, the additive primary and secondary colors – red, yellow, green, cyan, blue and magenta – and linear mixtures between adjacent pairs of them, sometimes called pure colors, are arranged around the outside edge of the cylinder with saturation 1. These saturated colors have lightness 0.5 in HSL, while in HSV they have value 1. Mixing these pure colors with black – producing so called shades – leaves saturation unchanged. In HSL, saturation is also unchanged by tinting with white, and only mixtures with both black and white – called tones – have saturation less than 1. In HSV, tinting alone reduces saturation. Because these definitions of saturation – in which very dark (in both models) or very light (in HSL) near neutral colors are considered fully saturated (for instance, from the bottom right in the sliced HSL cylinder or from the top right) – conflict with the intuitive notion of color purity, often a conic or biconic solid is drawn instead (fig. 3), with what this article calls chroma as its radial dimension (equal to the range of the RGB values), instead of saturation (where the saturation is equal to the chroma over the maximum chroma in that slice of the (bi)cone). Confusingly, such diagrams usually label this radial dimension "saturation", blurring or erasing the distinction between saturation and chroma. As described below, computing chroma is a helpful step in the derivation of each model. Because such an intermediate model – with dimensions hue, chroma, and HSV value or HSL lightness – takes the shape of a cone or bicone, HSV is often called the "hexcone model" while HSL is often called the "bi hexcone model" (fig. 8).

Most televisions, computer displays, and projectors produce colors by combining red, green, and blue light in varying intensities – the so called RGB additive primary colors. The resulting mixtures in RGB color space can reproduce a wide variety of colors (called a gamut); however, the relationship between the constituent amounts of red, green, and blue light and the resulting color is unintuitive, especially for inexperienced users, and for users familiar with subtractive color mixing of paints or traditional artists' models based on tints and shades (fig. 4). Furthermore, neither additive nor subtractive color models define color relationships the same way the human eye does. For example, imagine we have an RGB display whose color is controlled by three sliders ranging from 0–255, one controlling the intensity of each of the red, green, and blue primaries. If we begin with a relatively colorful orange , with sRGB values 1=R = 217, 1=G = 118, 1=B = 33, and want to reduce its colorfulness by half to a less saturated orange , we would need to drag the sliders to decrease R by 31, increase G by 24, and increase B by 59, as pictured below. Beginning in the 1950s, color television broadcasts used a compatible color system whereby "luminance" and "chrominance" signals were encoded separately, so that existing unmodified black and white televisions could still receive color broadcasts and show a monochrome image. In an attempt to accommodate more traditional and intuitive color mixing models, computer graphics pioneers at PARC and NYIT introduced the HSV model for computer display technology in the mid 1970s, formally described by Alvy Ray Smith in the August 1978 issue of Computer Graphics. In the same issue, Joblove and Greenberg described the HSL model – whose dimensions they labeled hue, relative chroma, and intensity – and compared it to HSV (fig. 1). Their model was based more upon how colors are organized and conceptualized in human vision in terms of other color making attributes, such as hue, lightness, and chroma; as well as upon traditional color mixing methods – e. g., in painting – that involve mixing brightly colored pigments with black or white to achieve lighter, darker, or less colorful colors. The following year, 1979, at SIGGRAPH, Tektronix introduced graphics terminals using HSL for color designation, and the Computer Graphics Standards Committee recommended it in their annual status report (fig. 7). These models were useful not only because they were more intuitive than raw RGB values, but also because the conversions to and from RGB were extremely fast to compute: they could run in real time on the hardware of the 1970s. Consequently, these models and similar ones have become ubiquitous throughout image editing and graphics software since then. Some of their uses are described below.

The dimensions of the HSL and HSV geometries – simple transformations of the not perceptually based RGB model – are not directly related to the photometric color making attributes of the same names, as defined by scientists such as the CIE or ASTM. Nonetheless, it is worth reviewing those definitions before leaping into the derivation of our models. For the definitions of color making attributes which follow, see:

Hue The "attribute of a visual sensation according to which an area appears to be similar to one of the perceived colors: red, yellow, green, and blue, or to a combination of two of them". who clearly states that "We shall assume that an RGB monitor is a linear device", and thus designed HSV using linear RGB. We will drop the primes, and the labels R, G, and B should be taken to stand for the three attributes of the origin RGB space, whether or not it is gamma corrected. – 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, starting with red at 0°. Then they came up with a characterization of brightness/value/lightness, and defined saturation to range from 0 along the axis to 1 at the most colorful point for each pair of other parameters. (The atan2 function, a "two argument arctangent", computes the angle from a cartesian coordinate pair.) Notice that these two definitions of hue (H and H2) nearly coincide, with a maximum difference between them for any color of about 1.12° – which occurs at twelve particular hues, for instance 1=H = 13.38°, 1=H2 = 12.26° – and with 1=H = H2 for every multiple of 30°. The two definitions of chroma (C and C2) differ more substantially: they are equal at the corners of our hexagon, but at points halfway between two corners, such as 1=H = H2 = 30°, we have 1=C = 1, but a difference of about 13.4%.

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 H ∈ [0°, 360°), C ∈ [0, 1], and V ∈ [0, 1] 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

Using the same name for these three different definitions of saturation leads to some confusion, as the three attributes describe substantially different color relationships; in HSV and HSI, the term roughly matches the psychometric definition, of a chroma of a color relative to its own lightness, but in HSL it does not come close. Even worse, the word saturation is also often used for one of the measurements we call chroma above (C or C2).

All parameter values shown below are given as values in the interval [0, 1], except those for H and H2, which are in the interval [0°, 360°). ColorRGBHH2CC2VLI601SHSVSHSLSHSI#FFFFFF 1.000 1.000 1.000n/an/a 0.000 0.000 1.000 1.000 1.000 1.000 0.000 0.000 0.000#808080 0.500 0.500 0.500n/an/a 0.000 0.000 0.500 0.500 0.500 0.500 0.000 0.000 0.000#000000 0.000 0.000 0.000n/an/a 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000#FF0000 1.000 0.000 0.000 0.0° 0.0° 1.000 1.000 1.000 0.500 0.333 0.299 1.000 1.000 1.000#BFBF00 0.750 0.750 0.000 60.0° 60.0° 0.750 0.750 0.750 0.375 0.500 0.664 1.000 1.000 1.000#008000 0.000 0.500 0.000 120.0° 120.0° 0.500 0.500 0.500 0.250 0.167 0.293 1.000 1.000 1.000#80FFFF 0.500 1.000 1.000 180.0° 180.0° 0.500 0.500 1.000 0.750 0.833 0.850 0.500 1.000 0.400#8080FF 0.500 0.500 1.000 240.0° 240.0° 0.500 0.500 1.000 0.750 0.667 0.557 0.500 1.000 0.250#BF40BF 0.750 0.250 0.750 300.0° 300.0° 0.500 0.500 0.750 0.500 0.583 0.457 0.667 0.500 0.571#A0A424 0.628 0.643 0.142 61.8° 61.5° 0.501 0.494 0.643 0.393 0.471 0.581 0.779 0.638 0.699#411BEA 0.255 0.104 0.918 251.1° 250.0° 0.814 0.750 0.918 0.511 0.426 0.242 0.887 0.832 0.756#1EAC41 0.116 0.675 0.255 134.9° 133.8° 0.559 0.504 0.675 0.396 0.349 0.460 0.828 0.707 0.667#F0C80E 0.941 0.785 0.053 49.5° 50.5° 0.888 0.821 0.941 0.497 0.593 0.748 0.944 0.893 0.911#B430E5 0.704 0.187 0.897 283.7° 284.8° 0.710 0.636 0.897 0.542 0.596 0.423 0.792 0.775 0.686#ED7651 0.931 0.463 0.316 14.3° 13.2° 0.615 0.556 0.931 0.624 0.570 0.586 0.661 0.817 0.446#FEF888 0.998 0.974 0.532 56.9° 57.4° 0.466 0.454 0.998 0.765 0.835 0.931 0.467 0.991 0.363#19CB97 0.099 0.795 0.591 162.4° 163.4° 0.696 0.620 0.795 0.447 0.495 0.564 0.875 0.779 0.800#362698 0.211 0.149 0.597 248.3° 247.3° 0.448 0.420 0.597 0.373 0.319 0.219 0.750 0.601 0.533#7E7EB8 0.495 0.493 0.721 240.5° 240.4° 0.228 0.227 0.721 0.607 0.570 0.520 0.316 0.290 0.135

The original purpose of HSL and HSV and similar models, and their most common current application, is in color selection tools. At their simplest, some such color pickers provide three sliders, one for each attribute. Most, however, show a two dimensional slice through the model, along with a slider controlling which particular slice is shown. The latter type of GUI exhibits great variety, because of the choice of cylinders, hexagonal prisms, or cones/bicones that the models suggest (see the diagram near the top of the page). Several color choosers from the 1990s are shown to the right, most of which have remained nearly unchanged in the intervening time: today, nearly every computer color chooser uses HSL or HSV, at least as an option. Some more sophisticated variants are designed for choosing whole sets of colors, basing their suggestions of compatible colors on the HSL or HSV relationships between them. Most web applications needing color selection also base their tools on HSL or HSV, and pre packaged open source color choosers exist for most major web front end frameworks. The CSS 3 specification allows web authors to specify colors for their pages directly with HSL coordinates. HSL and HSV are sometimes used to define gradients for data visualization, as in maps or medical images. For example, the popular GIS program ArcGIS historically applied customizable HSV based gradients to numerical geographical data. Fig. 17. xv's HSV based color modifier. Fig. 18. The hue/saturation tool in Photoshop 2.5, ca. 1992. Image editing software also commonly includes tools for adjusting colors with reference to HSL or HSV coordinates, or to coordinates in a model based on the "intensity" or luma defined above. In particular, tools with a pair of "hue" and "saturation" sliders are commonplace, dating to at least the late 1980s, but various more complicated color tools have also been implemented. For instance, the Unix image viewer and color editor xv allowed six user definable hue (H) ranges to be rotated and resized, included a dial like control for saturation (SHSV), and a curves like interface for controlling value (V) – see fig. 17. The image editor Picture Window Pro includes a "color correction" tool which affords complex remapping of points in a hue/saturation plane relative to either HSL or HSV space. Video editors also use these models. For example, both Avid and Final Cut Pro include color tools based on HSL or a similar geometry for use adjusting the color in video. With the Avid tool, users pick a vector by clicking a point within the hue/saturation circle to shift all the colors at some lightness level (shadows, mid tones, highlights) by that vector. Since version 4.0, Adobe Photoshop's "Luminosity", "Hue", "Saturation", and "Color" blend modes composite layers using a luma/chroma/hue color geometry. These have been copied widely, but several imitators use the HSL (e. g. PhotoImpact, Paint Shop Pro) or HSV geometries instead.

HSL, HSV, HSI, or related models are often used in computer vision and image analysis for feature detection or image segmentation. The applications of such tools include object detection, for instance in robot vision; object recognition, for instance of faces, text, or license plates; content based image retrieval; and analysis of medical images.