Misplaced Pages

#567432

83-507: HSV may refer to: Computing [ edit ] HSL and HSV color space, which describes colors by hue, saturation, and lightness (or luminosity) Virology [ edit ] Herpes simplex virus (HSV) spreads in skin contact with skin and herpes wounds on the skin; transmitted by kissing Places [ edit ] Huntsville, Alabama , United States Huntsville International Airport Sport [ edit ] Hamburger SV ,

166-429: A "generalized LHS model". 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 ∈ [0, 1] – 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

249-414: A * and b * coordinates is technically unbounded, though it is commonly clamped to the range of −128 to 127 for use with integer code values, though this results in potentially clipping some colors depending on the size of the source color space. The gamut's large size and inefficient utilization of the coordinate space means the best practice is to use floating-point values for all three coordinates. Unlike

332-493: A * and b * to C * and h ° is performed as follows: Conversely, given the polar coordinates , conversion to Cartesian coordinates is achieved with: The LCh (or HLC) color space is not the same as the HSV, HSL or HSB color models, although their values can also be interpreted as a base color, saturation and lightness of a color. The HSL values are a polar coordinate transformation of what is technically defined RGB cube color space. LCh

415-551: A German football club HSV Handball , a German handball club in Hamburg Hannover 96 , or Hannoverscher Sportverein von 1896, a German football club Other uses [ edit ] HSV (TV station) broadcasting in Melbourne, Australia Hennessey Special Vehicles , a recently established American automobile division by Hennessey Holden Special Vehicles , an Australian automobile manufacturer Topics referred to by

498-476: 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. In each of our models, we calculate both hue and what this article will call chroma , after Joblove and Greenberg (1978), in the same way – that is, the hue of a color has the same numerical values in all of these models, as does its chroma. If we take our tilted RGB cube, and project it onto

581-466: A color precisely requires reporting not only HSL or HSV values, but also the characteristics of the RGB space they are based on, including the gamma correction in use. If we take an image and extract the hue, saturation, and lightness or value components, and then compare these to the components of the same name as defined by color scientists, we can quickly see the difference, perceptually. For example, examine

664-566: A computer monitor or a printer, but instead relate to the CIE standard observer which is an averaging of the results of color matching experiments under laboratory conditions. The CIELAB space is three-dimensional and covers the entire gamut (range) of human color perception. It is based on the opponent model of human vision, where red and green form an opponent pair and blue and yellow form an opponent pair. The lightness value, L* (pronounced "L star"), defines black at 0 and white at 100. The a* axis

747-487: A discontinuity at 360°, it is difficult to use in statistical computations or quantitative comparisons: analysis requires the use of circular statistics . Furthermore, hue is defined piecewise, in 60° chunks, where the relationship of lightness, value, and chroma to R , G , and B depends on the hue chunk in question. This definition introduces discontinuities, corners which can plainly be seen in horizontal slices of HSL or HSV. Charles Poynton, digital video expert, lists

830-599: 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

913-463: A lightness dimension, does not attempt to "fill" a cylinder by its definition of saturation. Instead of presenting color choice or modification interfaces to end users, the goal of HSI is to facilitate separation of shapes in an image. Saturation is therefore defined in line with the psychometric definition: chroma relative to lightness ( fig. 15 ). See the Use in image analysis section of this article. Using

SECTION 10

#1732844841568

996-592: 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 . For

1079-716: A saturated yellow and saturated blue may be designated as the same 'lightness' but have wide differences in perceived lightness. These flaws make the systems difficult to use to control the look of a color scheme in a systematic manner. If much tweaking is required to achieve the desired effect, the system offers little benefit over grappling with raw specifications in RGB or CMY. If these problems make HSL and HSV problematic for choosing colors or color schemes, they make them much worse for image adjustment. HSL and HSV, as Brewer mentioned, confound perceptual color-making attributes, so that changing any dimension results in non-uniform changes to all three perceptual dimensions, and distorts all of

1162-403: A single color, they ignore much of the complexity of color appearance. Essentially, they trade off perceptual relevance for computation speed, from a time in computing history (high-end 1970s graphics workstations, or mid-1990s consumer desktops) when more sophisticated models would have been too computationally expensive. HSL and HSV are simple transformations of RGB which preserve symmetries in

1245-441: A transformation, hue is precisely the angle around the origin and chroma the distance from the origin: the angle and magnitude of the vector pointing to a color. Sometimes for image analysis applications, this hexagon-to-circle transformation is skipped, and hue and chroma (we'll denote these H 2 and C 2 ) are defined by the usual cartesian-to-polar coordinate transformations ( fig. 11 ). The easiest way to derive those

1328-446: Is being used it is common to clamp a* and b* in the range of −128 to 127. CIELAB is calculated relative to a reference white , for which the CIE recommends the use of CIE Standard illuminant D65 . D65 is used in the vast majority of industries and applications, with the notable exception being the printing industry which uses D50. The International Color Consortium largely supports

1411-485: 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 R = 217 , G = 118 , 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. [REDACTED] Beginning in

1494-685: Is different from Wikidata All article disambiguation pages All disambiguation pages HSL and HSV 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,

1577-664: Is held to have the same saturation as the green primary   , even though the former color has almost no chroma or saturation by the conventional psychometric definitions. Such perversities led Cynthia Brewer, expert in color scheme choices for maps and information displays, to tell the American Statistical Association : Computer science offers a few poorer cousins to these perceptual spaces that may also turn up in your software interface, such as HSV and HLS. They are easy mathematical transformations of RGB, and they seem to be perceptual systems because they make use of

1660-420: Is impossible for a monitor to display the full gamut of LAB colors. The green-red and blue-yellow opponent channels relate to the human vision system's opponent color process. This makes CIELAB a Hering opponent color space. The nature of the transformations also characterizes it as an chromatic value color space. The nonlinear relations for L* , a* and b* are intended to mimic the nonlinear response of

1743-549: Is most easily expressed using the inverse of the function f above: where and where δ = ⁠ 6 / 29 ⁠ . The "CIELCh" or "CIEHLC" space is a color space based on CIELAB, which uses the polar coordinates C * ( chroma , relative saturation) and h ° (hue angle, angle of the hue in the CIELAB color wheel) instead of the Cartesian coordinates a * and b *. The CIELAB lightness L* remains unchanged. The conversion of

SECTION 20

#1732844841568

1826-548: Is no particular reason to strictly mimic human color response. John Kender's 1976 master's thesis proposed the HSI model. Ohta et al. (1980) instead used a model made up of dimensions similar to those we have called I , α , and β . In recent years, such models have continued to see wide use, as their performance compares favorably with more complex models, and their computational simplicity remains compelling. While HSL, HSV, and related spaces serve well enough to, for instance, choose

1909-473: Is relative to the green–red opponent colors, with negative values toward green and positive values toward red. The b* axis represents the blue–yellow opponents, with negative numbers toward blue and positive toward yellow. The a* and b* axes are unbounded and depending on the reference white they can easily exceed ±150 to cover the human gamut. Nevertheless, software implementations often clamp these values for practical reasons. For instance, if integer math

1992-542: 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

2075-399: Is simply the maximum of the other two components. This chroma is M in the particular case of a color with a zero component, and M − m in general. The hue is the proportion of the distance around the edge of the hexagon which passes through the projected point, originally measured on the range [0, 1] but now typically measured in degrees [0°, 360°) . For points which project onto

2158-434: Is sometimes used to differentiate from L*C*h(uv). A related color space, the CIE 1976 L * u * v * color space (a.k.a. CIELUV ), preserves the same L* as L*a*b* but has a different representation of the chromaticity components. CIELAB and CIELUV can also be expressed in cylindrical form (CIELCh ab and CIELCh uv , respectively), with the chromaticity components replaced by correlates of chroma and hue . Since

2241-518: Is still perceptually uniform . Further, H and h are not identical, because HSL space uses as primary colors the three additive primary colors red, green and blue ( H = 0, 120, 240°). Instead, the LCh system uses the four colors red, yellow, green and blue ( h = 0, 90, 180, 270°). Regardless the angle h , C = 0 means the achromatic colors (non saturated), that is, the gray axis. The simplified spellings LCh, LCh(ab), LCH, LCH(ab) and HLC are common, but

2324-579: Is via a pair of cartesian chromaticity coordinates which we'll call α and β : (The atan2 function, a "two-argument arctangent", computes the angle from a cartesian coordinate pair.) Notice that these two definitions of hue ( H and H 2 ) nearly coincide, with a maximum difference between them for any color of about 1.12° – which occurs at twelve particular hues, for instance H = 13.38° , H 2 = 12.26° – and with H = H 2 for every multiple of 30°. The two definitions of chroma ( C and C 2 ) differ more substantially: they are equal at

2407-539: The RGB and CMYK color models, CIELAB is designed to approximate human vision. The L* component closely matches human perception of lightness, though it does not take the Helmholtz–Kohlrausch effect into account. CIELAB is less uniform in the color axes, but is useful for predicting small differences in color. The CIELAB coordinate space represents the entire gamut of human photopic (daylight) vision and far exceeds

2490-440: The interval [0, 1] , except those for H and H 2 , which are in the interval [0°, 360°) . 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

2573-561: 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

HSV - Misplaced Pages Continue

2656-518: The spectral distribution of light entering the eye, while lightness and chroma are measured relative to some white point, and are thus often used for descriptions of surface colors, remaining roughly constant even as brightness and colorfulness change with different illumination . Saturation can be defined as either the ratio of colorfulness to brightness, or that of chroma to lightness. HSL, HSV, and related models can be derived via geometric strategies, or can be thought of as specific instances of

2739-413: The value of HSV and the saturation of HSL are particular offenders. In HSV, the blue primary   and white   are held to have the same value, even though perceptually the blue primary has somewhere around 10% of the luminance of white (the exact fraction depends on the particular RGB primaries in use). In HSL, a mix of 100% red, 100% green, 90% blue – that is, a very light yellow   –

2822-424: The "chromaticity plane " perpendicular to the neutral axis, our projection takes the shape of a hexagon, with red, yellow, green, cyan, blue, and magenta at its corners ( fig. 9 ). Hue is roughly the angle of the vector to a point in the projection, with red at 0°, while chroma is roughly the distance of the point from the origin. More precisely, both hue and chroma in this model are defined with respect to

2905-403: 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

2988-405: 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

3071-413: 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

3154-597: 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

3237-492: 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: Brightness and colorfulness are absolute measures, which usually describe

3320-438: The HSL and HSV models scale the chroma so that it always fits into the range [0, 1] 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 takes H 2 as a hue dimension and the component average I ("intensity") as

3403-455: 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,

HSV - Misplaced Pages Continue

3486-865: 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

3569-594: The RGB cube unrelated to human perception, such that its R , G , and B corners are equidistant from the neutral axis, and equally spaced around it. If we plot the RGB gamut in a more perceptually-uniform space, such as CIELAB (see below ), it becomes immediately clear that the red, green, and blue primaries do not have the same lightness or chroma, or evenly spaced hues. Furthermore, different RGB displays use different primaries, and so have different gamuts. Because HSL and HSV are defined purely with reference to some RGB space, they are not absolute color spaces : to specify

3652-415: 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

3735-501: The RGB or CMYK data must be linearized relative to light. The reference illuminant of the RGB or CMYK data must be known, as well as the RGB primary coordinates or the CMYK printer's reference data in the form of a color lookup table (CLUT). In color managed systems, ICC profiles contains these needed data, which are then used to perform the conversions. As mentioned previously, the L * coordinate nominally ranges from 0 to 100. The range of

3818-489: The above problems with HSL and HSV in his Color FAQ , and concludes that: CIELAB The CIELAB color space , also referred to as L*a*b* , is a color space defined by the International Commission on Illumination (abbreviated CIE) in 1976. It expresses color as three values: L* for perceptual lightness and a* and b* for the four unique colors of human vision: red, green, blue and yellow. CIELAB

3901-414: 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,

3984-408: 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

4067-402: The color dimensions used. Because the R , G , and B components of an object's color in a digital image are all correlated with the amount of light hitting the object, and therefore with each other, image descriptions in terms of those components make object discrimination difficult. Descriptions in terms of hue/lightness/chroma or hue/lightness/saturation are often more relevant. Starting in

4150-418: The color relationships in the image. For instance, rotating the hue of a pure dark blue   toward green   will also reduce its perceived chroma, and increase its perceived lightness (the latter is grayer and lighter), but the same hue rotation will have the opposite impact on lightness and chroma of a lighter bluish-green –   to   (the latter is more colorful and slightly darker). In

4233-429: The color stimulus considered and X n , Y n , Z n describe a specified white achromatic reference illuminant. for the CIE 1931 (2°) standard colorimetric observer and assuming normalization where the reference white has Y = 100 , the values are: For Standard Illuminant D65 : For illuminant D50 , which is used in the printing industry: The division of the domain of the f function into two parts

SECTION 50

#1732844841568

4316-443: 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

4399-420: The corners of our hexagon, but at points halfway between two corners, such as H = H 2 = 30° , we have C = 1 , but C 2 = 3 4 ≈ 0.866 , {\textstyle C_{2}={\sqrt {\frac {3}{4}}}\approx 0.866,} a difference of about 13.4%. While the definition of hue is relatively uncontroversial – it roughly satisfies the criterion that colors of

4482-686: The cube root of the relative luminance with an offset near black. This results in an effective power curve with an exponent of approximately 0.43 which represents the human eye's response to light under daylight ( photopic ) conditions. The three coordinates of CIELAB represent the lightness of the color ( L* = 0 yields black and L* = 100 indicates white), its position between red and green ( a* , where negative values indicate green and positive values indicate red) and its position between yellow and blue ( b* , where negative values indicate blue and positive values indicate yellow). The asterisks (*) after L* , a*, and b* are pronounced star and are part of

4565-504: The example below ( fig. 21 ), the image (a) is the original photograph of a green turtle . In the image (b), we have rotated the hue ( H ) of each color by −30° , while keeping HSV value and saturation or HSL lightness and saturation constant. In the image right (c), we make the same rotation to the HSL/HSV hue of each color, but then we force the CIELAB lightness ( L *, a decent approximation of perceived lightness) to remain constant. Notice how

4648-461: The following images of a fire breather ( fig. 13 ). The original is in the sRGB colorspace. CIELAB L * is a CIE-defined achromatic lightness quantity (dependent solely on the perceptually achromatic luminance Y , but not the mixed-chromatic components X or Z , of the CIEXYZ colorspace from which the sRGB colorspace itself is derived), and it is plain that this appears similar in perceptual lightness to

4731-446: The four formulations yields a lightness equal to the value of R , G , or B . For a graphical comparison, see fig. 13 below . 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

4814-644: The full gamut extends past the bounding coordinate space. Ideally, CIELAB should be used with floating-point data to minimize obvious quantization errors. CIE standards and documents are copyright by the CIE and must be purchased; however, the formulas for CIELAB are available on the CIE website. where t is X / X n , {\displaystyle X/X_{\mathrm {n} },} Y / Y n , {\displaystyle Y/Y_{\mathrm {n} },} or Z / Z n {\displaystyle Z/Z_{\mathrm {n} }} : X , Y , and Z describe

4897-472: The full name to distinguish L * a * b * from Hunter's Lab , described below. Since the L*a*b* model has three axes, it requires a three-dimensional space to be represented completely. Also, because each axis is non-linear, it is not possible to create a two-dimensional chromaticity diagram. Additionally, the visual representations shown in the plots of the full CIELAB gamut on this page are an approximation, as it

4980-450: The gamut for sRGB or CMYK. In an integer implementation such as TIFF, ICC or Photoshop, the large coordinate space results in substantial data inefficiency due to unused code values. Only about 35% of the available coordinate code values are inside the CIELAB gamut with an integer format. Using CIELAB in an 8-bit per channel integer format typically results in significant quantization errors. Even 16-bit per channel can result in clipping, as

5063-652: The hexagonal shape of the projection. The chroma is the proportion of the distance from the origin to the edge of the hexagon. In the lower part of the adjacent diagram, this is the ratio of lengths OP / OP ′ , or alternatively the ratio of the radii of the two hexagons. This ratio is the difference between the largest and smallest values among R , G , or B in a color. To make our definitions easier to write, we'll define these maximum, minimum, and chroma component values as M , m , and C , respectively. To understand why chroma can be written as M − m , notice that any neutral color, with R = G = B , projects onto

SECTION 60

#1732844841568

5146-432: The hue-shifted middle version without such a correction dramatically changes the perceived lightness relationships between colors in the image. In particular, the turtle's shell is much darker and has less contrast, and the background water is much lighter. Image (d) uses CIELAB to hue shift; the difference from (c) demonstrates the errors in hue and saturation. Because hue is a circular quantity, represented numerically with

5229-501: The hue–lightness/value–saturation terminology. But take a close look; don't be fooled. Perceptual color dimensions are poorly scaled by the color specifications that are provided in these and some other systems. For example, saturation and lightness are confounded, so a saturation scale may also contain a wide range of lightnesses (for example, it may progress from white to green which is a combination of both lightness and saturation). Likewise, hue and lightness are confounded so, for example,

5312-402: The late 1970s, transformations like HSV or HSI were used as a compromise between effectiveness for segmentation and computational complexity. They can be thought of as similar in approach and intent to the neural processing used by human color vision, without agreeing in particulars: if the goal is object detection, roughly separating hue, lightness, and chroma or saturation is effective, but there

5395-514: 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 ( S HSV ), 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

5478-457: The letter presents a different order. HCL color space (Hue-Chroma-Luminance) on the other hand is a commonly used alternative name for the L*C*h(uv) color space, also known as the cylindrical representation or polar CIELUV . This name is commonly used by information visualization practitioners who want to present data without the bias implicit in using varying saturation . The name Lch(ab)

5561-402: The most part, computer vision algorithms used on color images are straightforward extensions to algorithms designed for grayscale images, for instance k-means or fuzzy clustering of pixel colors, or canny edge detection . At the simplest, each color component is separately passed through the same algorithm. It is important, therefore, that the features of interest can be distinguished in

5644-402: The origin and so has 0 chroma. Thus if we add or subtract the same amount from all three of R , G , and B , we move vertically within our tilted cube, and do not change the projection. Therefore, any two colors of ( R , G , B ) and ( R − m , G − m , B − m ) project on the same point, and have the same chroma. The chroma of a color with one of its components equal to zero ( m = 0)

5727-416: The origin in the chromaticity plane (i.e., grays), hue is undefined. Mathematically, this definition of hue is written piecewise : Sometimes, neutral colors (i.e. with C = 0 ) are assigned a hue of 0° for convenience of representation. These definitions amount to a geometric warping of hexagons into circles: each side of the hexagon is mapped linearly onto a 60° arc of the circle ( fig. 10 ). After such

5810-453: The original color image. Luma is roughly similar, but differs somewhat at high chroma, where it deviates most from depending solely on the true achromatic luminance ( Y , or equivalently L *) and is influenced by the colorimetric chromaticity ( x,y , or equivalently, a*,b* of CIELAB). HSL L and HSV V , by contrast, diverge substantially from perceptual lightness. Though none of the dimensions in these spaces match their perceptual analogs,

5893-401: 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

5976-661: 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

6059-465: 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

6142-422: The popular GIS program ArcGIS historically applied customizable HSV-based gradients to numerical geographical data. 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

6225-478: The printing industry and uses D50 with either CIEXYZ or CIELAB in the Profile Connection Space, for v2 and v4 ICC profiles . While the intention behind CIELAB was to create a space that was more perceptually uniform than CIEXYZ using only a simple formula, CIELAB is known to lack perceptual uniformity , particularly in the area of blue hues. The lightness value, L* in CIELAB is calculated using

6308-506: 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 C 2 ). All parameter values shown below are given as values in

6391-411: The same perceived hue should have the same numerical hue – the definition of a lightness or value dimension is less obvious: there are several possibilities depending on the purpose and goals of the representation. Here are four of the most common ( fig. 12 ; three of these are also shown in fig. 8 ): All four of these leave the neutral axis alone. That is, for colors with R = G = B , any of

6474-403: The same term [REDACTED] This disambiguation page lists articles associated with the title HSV . If an internal link led you here, you may wish to change the link to point directly to the intended article. Retrieved from " https://en.wikipedia.org/w/index.php?title=HSV&oldid=1173408656 " Category : Disambiguation pages Hidden categories: Short description

6557-436: 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,

6640-513: The visual system. Furthermore, uniform changes of components in the L*a*b* color space aim to correspond to uniform changes in perceived color, so the relative perceptual differences between any two colors in L*a*b* can be approximated by treating each color as a point in a three-dimensional space (with three components: L* , a* , b* ) and taking the Euclidean distance between them. In order to convert RGB or CMYK values to or from L*a*b* ,

6723-505: The work on CIELAB and CIELUV, the CIE has been incorporating an increasing number of color appearance phenomena into their models and difference equations to better predict human color perception. These color appearance models , of which CIELAB is a simple example, culminated with CIECAM02 . Oklab is built on the same spatial structure and achieves greater perceptual uniformity. Some systems and software applications that support CIELAB include: Hunter Lab (also known as Hunter L,a,b)

6806-603: Was done to prevent an infinite slope at t = 0 . The function f was assumed to be linear below some t = t 0 and was assumed to match the t 3 {\displaystyle {\sqrt[{3}]{t}}} part of the function at t 0 in both value and slope. In other words: The intercept f (0) = c was chosen so that L * would be 0 for Y = 0 : c = ⁠ 16 / 116 ⁠ = ⁠ 4 / 29 ⁠ . The above two equations can be solved for m and t 0 : where δ = ⁠ 6 / 29 ⁠ . The reverse transformation

6889-545: Was intended as a perceptually uniform space, where a given numerical change corresponds to a similar perceived change in color. While the LAB space is not truly perceptually uniform, it nevertheless is useful in industry for detecting small differences in color. Like the CIEXYZ space it derives from, CIELAB color space is a device-independent, "standard observer" model. The colors it defines are not relative to any particular device such as

#567432