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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: To solve problems such as these, 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.

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 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: See the Use in image analysis section of this article.

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 C 2. 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.

Several color choosers from the s are shown to the right, most of which have remained nearly unchanged in the intervening time: 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.

HSL and HSV are sometimes used to define gradients for data visualization , as in maps or medical images. 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 lates, 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.

Video editors also use these models. These have been copied widely, but several imitators use the HSL e. 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 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 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.

Starting in the late s, 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: 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 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 s graphics workstations, or mids consumer desktops when more sophisticated models would have been too computationally expensive.

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. 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 the following images of a fire breather fig. The original is in the sRGB colorspace. Though none of the dimensions in these spaces match their perceptual analogs, the value of HSV and the saturation of HSL are particular offenders.

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.

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.

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 the color relationships in the image.

In the example below fig. Notice how the hue-shifted middle version without such a correction dramatically changes the perceived lightness relationships between colors in the image.

The creators of HSL and HSV were far from the first to imagine colors fitting into conic or spherical shapes, with neutrals running from black to white in a central axis, and hues corresponding to angles around that axis.

Similar arrangements date back to the 18th century, and continue to be developed in the most modern and scientific models.

First, we compute chroma, by multiplying saturation by the maximum chroma for a given lightness or value. Next, we find the point on one of the bottom three faces of the RGB cube which has the same hue and chroma as our color and therefore projects onto the same point in the chromaticity plane.

Finally, we add equal amounts of R , G , and B to reach the proper lightness or value. Then we can find a point R 1 , G 1 , B 1 along the bottom three faces of the RGB cube, with the same hue and chroma as our color using the intermediate value X for the second largest component of this color:.

Finally, we can find R , G , and B by adding the same amount to each component, to match lightness:. First, we find chroma:.

Then we can, again, find a point R 1 , G 1 , B 1 along the bottom three faces of the RGB cube, with the same hue and chroma as our color using the intermediate value X for the second largest component of this color:.

Finally, we can find R , G , and B by adding the same amount to each component, to match value:. Then we can find R , G , and B by adding the same amount to each component, to match luma:.

Mouse over the swatches below to see the R , G , and B values for each swatch in a tooltip. From Wikipedia, the free encyclopedia.

Alternative representations of the RGB color model. If we plot hue and a HSL lightness or b HSV value against chroma range of RGB values rather than saturation chroma over maximum chroma for that slice , the resulting solid is a bicone or cone , respectively, not a cylinder.

Such diagrams often claim to represent HSL or HSV directly, with the chroma dimension confusingly labelled "saturation".

Painters long mixed colors by combining relatively bright pigments with black and white. Mixtures with white are called tints , mixtures with black are called shades , and mixtures with both are called tones.

See Tints and shades. This color model by German chemist Wilhelm Ostwald exemplifies the "mixtures with white and black" approach, organizing 24 "pure" colors into a hue circle , and colors of each hue into a triangle.

The model thus takes the shape of a bicone. The same image, with a portion removed for clarity. Tektronix graphics terminals used the earliest commercial implementation of HSL, in This diagram, from a patent filed in , shows the bicone geometry underlying the model.

Color picker and Image editing. The herpes simplex virus, also known as HSV, is an infection that causes herpes. Herpes can appear in various parts of the body, most commonly on the genitals or mouth.

There are two types of the herpes simplex virus. The herpes simplex virus is a contagious virus that can be passed from person to person through direct contact.

Children will often contract HSV-1 from early contact with an infected adult. They then carry the virus with them for the rest of their lives.

The virus spreads more quickly when an infected person is experiencing an outbreak. Anywhere from 30 to 95 percent of adults are seropositive for HSV-1, though they may never experience an outbreak.

While HSV-2 infections are spread through contact with a herpes sore, the AAD reports that most people get HSV-1 from an infected person who is asymptomatic, or does not have sores.

Anyone can be infected with HSV, regardless of age. Your risk is based almost entirely on exposure to the infection. In cases of sexually transmitted HSV, people are more at risk when they participate in risky sexual behavior without the use of protection, such as condoms.

Other risk factors for HSV-2 include:. If a pregnant woman is having an outbreak of genital herpes at the time of childbirth, it can expose the baby to both types of HSV, and may put them at risk for serious complications.

It is important to understand that someone may not have visible sores or symptoms and still be infected by the virus. And they may transmit the virus to others.

You may also experience symptoms that are similar to the flu. These symptoms can include:. HSV can also spread to the eyes, causing a condition called herpes keratitis.

This can cause symptoms such as eye pain , discharge, and a gritty feeling in the eye. This type of virus is generally diagnosed with a physical exam.

Your doctor may check your body for sores and ask you about some of your symptoms. Your doctor may also request HSV testing.

This is known as a herpes culture. It will confirm the diagnosis if you have sores on your genitals. During this test, your doctor will take a swab sample of fluid from the sore and then send it to a laboratory for testing.

This is especially helpful when there are no sores present. There is currently no cure for this virus. Treatment focuses on getting rid of sores and limiting outbreaks.

It is possible that your sores will disappear without treatment. However, your doctor may determine you need one or more of the following medications:.

These medications can help infected individuals reduce the risk of spreading the virus to others. The medications also help to lower the intensity and frequency of outbreaks.

These medications may come in oral pill form, or may be applied as a cream. For severe outbreaks, these medications may also be administered by injection.

People who become infected with HSV will have the virus for the rest of their lives. Some people may experience regular outbreaks.

Others will only experience one outbreak after they have been infected and then the virus may become dormant. Even if a virus is dormant, certain stimuli can trigger an outbreak.

It is believed that outbreaks may become less intense over time because the body starts creating antibodies.

If a generally healthy individual is infected with the virus, there are usually no complications. Although there is no cure for herpes, you can take measures to avoid becoming infected, or to prevent spreading HSV to another person.

Individuals with HSV-2 should avoid any type of sexual activity with other people during an outbreak. If the individual is not experiencing symptoms but has been diagnosed with the virus, a condom should be used during intercourse.

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