HCL color space

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HCL (Hue-Chroma-Luminance) or LCh refers to any of the many cylindrical color space models that are designed to accord with human perception of color with the three parameters. Lch has been adopted by information visualization practitioners to present data without the bias implicit in using varying saturation. [1] [2] [3] They are, in general, designed to have characteristics of both cylindrical translations of the RGB color space, such as HSL and HSV, and the L*a*b* color space. Some conflicting definitions of the terms are:

Contents

The sRGB gamut plotted within the cylindrical CIELCh color spaces. L is the vertical axis; C is the cylinder radius; h is the angle around the circumference. Left: CIELChab; right: CIELChuv

Derivation

Color-making attributes

HCL concerns the following attributes of color appearance: [upper-alpha 1]

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". [8]
Lightness, value
The "brightness relative to the brightness of a similarly illuminated white". [8]
Luminance (Y or Lv,Ω)
The radiance weighted by the effect of each wavelength on a typical human observer, measured in SI units in candela per square meter (cd/m2). Often the term luminance is used for the relative luminance, Y/Yn, where Yn is the luminance of the reference white point.
Colorfulness
The "attribute of a visual sensation according to which the perceived color of an area appears to be more or less chromatic". [8]

The HSL and HSV color spaces are more intuitive translations of the RGB color space, because they provide a single hue number. However, their luminance variation does not match the way humans perceive color. Perceptually uniform color spaces outperform RGB in cases such as high noise environments. [9]

CIE color spaces

CIE-based LCh color spaces are transformations of the two chroma values (ab or uv) into the polar coordinate. The source color spaces are still very well-regarded for their uniformity, and the transformation does not cause degradation in this aspect. See the respective articles for how the underlying coordinates are derived.

Sarifuddin 2005

Sarifuddin, noting the lack of blue hue consistency of CIELABa common complaint among its users [10] decided to make their own color space by mashing up some of the features. [5]

According to the Stack Overflow user Tatarize, what Sarifuddin proposes as "HCL" is algorithmically similar to HSL. While pointing out advantages in computational efficiency, they argue that Sarifuddin's work does not represent a significant improvement over the CIELAB color space while showing failure to reproduce the paper's claims. [11] [12] They also propose what they consider to be an improved version of Sarifuddin's algorithm. [13] [ original research ]

Other color appearance models

In general, any color appearance model with a lightness and two chroma components can also be transformed into a HCL-type color space by turning the chroma components into polar coordinates.

Implementations

CIELCh has been implemented in a wide range of ways: as programmatic code for generating color swatches in statistics tools, as standalone tools for designing and testing swatches, or as libraries that allow other programs to use the color space. Some implementations include:

Related Research Articles

<span class="mw-page-title-main">Hue</span> Property of a color

In color theory, hue is one of the main properties of a color, defined technically in the CIECAM02 model as "the degree to which a stimulus can be described as similar to or different from stimuli that are described as red, orange, yellow, green, blue, violet," within certain theories of color vision.

<span class="mw-page-title-main">Munsell color system</span> Color space

In colorimetry, the Munsell color system is a color space that specifies colors based on three properties of color: hue, value (lightness), and chroma. It was created by Albert H. Munsell in the first decade of the 20th century and adopted by the United States Department of Agriculture (USDA) as the official color system for soil research in the 1930s.

<span class="mw-page-title-main">HSL and HSV</span> 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.

<span class="mw-page-title-main">Chromaticity</span> Specification of color hue and saturation

Chromaticity is an objective specification of the quality of a color regardless of its luminance. Chromaticity consists of two independent parameters, often specified as hue (h) and colorfulness (s), where the latter is alternatively called saturation, chroma, intensity, or excitation purity. This number of parameters follows from trichromacy of vision of most humans, which is assumed by most models in color science.

<span class="mw-page-title-main">CIELAB color space</span> Standard color space with color-opponent values

The CIELAB color space, also referred to as L*a*b*, is a color space defined by the International Commission on Illumination 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 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.

<span class="mw-page-title-main">Colorfulness</span> Perceived intensity of a specific color

Colorfulness, chroma and saturation are attributes of perceived color relating to chromatic intensity. As defined formally by the International Commission on Illumination (CIE) they respectively describe three different aspects of chromatic intensity, but the terms are often used loosely and interchangeably in contexts where these aspects are not clearly distinguished. The precise meanings of the terms vary by what other functions they are dependent on.

<span class="mw-page-title-main">Spectral color</span> Color evoked by a single wavelength of light in the visible spectrum

A spectral color is a color that is evoked by monochromatic light, i.e. either a spectral line with a single wavelength or frequency of light in the visible spectrum, or a relatively narrow spectral band. Every wave of visible light is perceived as a spectral color; when viewed as a continuous spectrum, these colors are seen as the familiar rainbow. Non-spectral colors are evoked by a combination of spectral colors.

<span class="mw-page-title-main">Hold-And-Modify</span> Display mode used in Commodore Amiga computers

Hold-And-Modify, usually abbreviated as HAM, is a display mode of the Commodore Amiga computer. It uses a highly unusual technique to express the color of pixels, allowing many more colors to appear on screen than would otherwise be possible. HAM mode was commonly used to display digitized photographs or video frames, bitmap art and occasionally animation. At the time of the Amiga's launch in 1985, this near-photorealistic display was unprecedented for a home computer and it was widely used to demonstrate the Amiga's graphical capability. However, HAM has significant technical limitations which prevent it from being used as a general purpose display mode.

In color science, a color model is an abstract mathematical model describing the way colors can be represented as tuples of numbers, typically as three or four values or color components. When this model is associated with a precise description of how the components are to be interpreted, taking account of visual perception, the resulting set of colors is called "color space."

<span class="mw-page-title-main">Lightness</span> Property of a color

Lightness is a visual perception of the luminance of an object. It is often judged relative to a similarly lit object. In colorimetry and color appearance models, lightness is a prediction of how an illuminated color will appear to a standard observer. While luminance is a linear measurement of light, lightness is a linear prediction of the human perception of that light.

In colorimetry, the CIE 1976L*, u*, v*color space, commonly known by its abbreviation CIELUV, is a color space adopted by the International Commission on Illumination (CIE) in 1976, as a simple-to-compute transformation of the 1931 CIE XYZ color space, but which attempted perceptual uniformity. It is extensively used for applications such as computer graphics which deal with colored lights. Although additive mixtures of different colored lights will fall on a line in CIELUV's uniform chromaticity diagram, such additive mixtures will not, contrary to popular belief, fall along a line in the CIELUV color space unless the mixtures are constant in lightness.

In color science, color difference or color distance is the separation between two colors. This metric allows quantified examination of a notion that formerly could only be described with adjectives. Quantification of these properties is of great importance to those whose work is color-critical. Common definitions make use of the Euclidean distance in a device-independent color space.

<span class="mw-page-title-main">Color gradient</span> Specifies a range of position-dependent colors

In color science, a color gradient specifies a range of position-dependent colors, usually used to fill a region.

<span class="mw-page-title-main">Color space</span> Standard that defines a specific range of colors

A color space is a specific organization of colors. In combination with color profiling supported by various physical devices, it supports reproducible representations of color – whether such representation entails an analog or a digital representation. A color space may be arbitrary, i.e. with physically realized colors assigned to a set of physical color swatches with corresponding assigned color names, or structured with mathematical rigor. A "color space" is a useful conceptual tool for understanding the color capabilities of a particular device or digital file. When trying to reproduce color on another device, color spaces can show whether shadow/highlight detail and color saturation can be retained, and by how much either will be compromised.

HWB is a cylindrical-coordinate representation of points in an RGB color model, similar to HSL and HSV. It was developed by HSV’s creator Alvy Ray Smith in 1996 to address some of the issues with HSV. HWB was designed to be more intuitive for humans to use and slightly faster to compute. The first coordinate, H (Hue), is the same as the Hue coordinate in HSL and HSV. W and B stand for Whiteness and Blackness respectively and range from 0–100%. The mental model is that the user can pick a main hue and then “mix” it with white and/or black to produce the desired color.

A color appearance model (CAM) is a mathematical model that seeks to describe the perceptual aspects of human color vision, i.e. viewing conditions under which the appearance of a color does not tally with the corresponding physical measurement of the stimulus source.

In colorimetry, the HSLuvcolor space is a human-friendly alternative to the HSL color space. It was formerly known as "husl". It is a variation of the CIE LCH(uv) color space, where the C (colorfulness) component is replaced by a "Saturation" (S) component representing the colorfulness percentage relative to the maximum sRGB can provide given the L and H values. The value has nothing to do with "saturation" in color theory.

<span class="mw-page-title-main">Oklab color space</span> Standard color space with color-opponent values

The Oklab color space is a uniform color space for device independent color designed to improve perceptual uniformity, hue and lightness prediction, color blending, and usability while ensuring numerical stability and ease of implementation. Introduced by Björn Ottosson in December 2020, Oklab and its cylindrical counterpart, Oklch, have been included in the CSS Color Level 4 and Level 5 drafts for device-independent web colors since December 2021. They are supported by recent versions of major web browsers and allow the specification of wide-gamut P3 colors.

References

  1. "Clearly, if color appearance is to be described in a systematic, mathematical way, definitions of the phenomena being described need to be precise and universally agreed upon." [8]
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  2. 1 2 Zeileis, Achim; Hornik, Kurt; Murrell, Paul (2009). "Escaping RGBland: Selecting Colors for Statistical Graphics" (PDF). Computational Statistics & Data Analysis. 53 (9): 3259–3270. doi:10.1016/j.csda.2008.11.033.
  3. Stauffer, Reto; Mayr, Georg J.; Dabernig, Markus; Zeileis, Achim (2015). "Somewhere over the Rainbow: How to Make Effective Use of Colors in Meteorological Visualizations". Bulletin of the American Meteorological Society. 96 (2): 203–216. Bibcode:2015BAMS...96..203S. doi:10.1175/BAMS-D-13-00155.1. hdl: 10419/101098 .
  4. 1 2 Zeileis, Achim; Fisher, Jason C.; Hornik, Kurt; Ihaka, Ross; McWhite, Claire D.; Murrell, Paul; Stauffer, Reto; Wilke, Claus O. (2020). "colorspace: A Toolbox for Manipulating and Assessing Colors and Palettes". Journal of Statistical Software. 96 (1): 1–49. arXiv: 1903.06490 . doi: 10.18637/jss.v096.i01 . S2CID   80628405.
  5. 1 2 Sarifuddin, M. & Missaoui, Rokia (2005). A New Perceptually Uniform Color Space with Associated Color Similarity Measure for Content-Based Image and Video Retrieval (PDF). Multimedia Information Retrieval Workshop, 28th Annual ACM SIGIR Conference. S2CID   17570716. Archived from the original (PDF) on 2019-02-20.. Abstract/long-form corrected report
  6. Material Design 3: Defining colors with hue, chroma, and tone (HCT)
  7. James O'Leary (2022-02-17). "The Science of Color & Design". Material Design Blog.
  8. 1 2 3 4 Fairchild (2005), pp. 83–93
  9. Paschos, G. (2001). "Perceptually Uniform Color Spaces for Color Texture Analysis: An Empirical Evaluation". IEEE Transactions on Image Processing. 10 (6): 932–937. Bibcode:2001ITIP...10..932P. doi:10.1109/83.923289.
  10. McLellan, M. R.; Lind, L. R.; Kime, R. W. (1995). "Hue Angle Determinations and Statistical Analysis for Multiquadrant Hunter L,a,b Data". Journal of Food Quality. 18 (3): 235–240. doi: 10.1111/j.1745-4557.1995.tb00377.x .
  11. tatarize. "HCL color to RGB and backward". Stack Overflow.
  12. Tatarize (4 September 2012). "HCL: a new Color Space for a pack of lies". Ssnot!. Retrieved 22 May 2019.
  13. "algorithm - HCL color to RGB and backward". Stack Overflow. Retrieved 2020-12-08.
  14. 1 2 "colorspace: A Toolbox for Manipulating and Assessing Colors and Palettes". The Comprehensive R Archive Network. 23 January 2023.
  15. 1 2 "Welcome to python-colorspace's documentation!". Read the Docs.
  16. "HCL Wizard".
  17. "Scientific colour maps". Fabio Crameri.
  18. "ac-colors". GitHub.
  19. "Chroma.js". GitHub.
  20. "colorio". PyPI.