HSL and HSV

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.^[1]

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.

The simplest definition is just the , i.e. average, of the three components, in the HSI model called intensity (fig. 12a). This is simply the projection of a point onto the neutral axis – the vertical height of a point in our tilted cube. The advantage is that, together with Euclidean-distance calculations of hue and chroma, this representation preserves distances and angles from the geometry of the RGB cube.^[23]^[25]
$I=\operatorname {avg} (R,G,B)={\tfrac {1}{3}}(R+G+B)$

arithmetic mean

In the HSV "hexcone" model, value is defined as the largest component of a color, our M above (fig. 12b). This places all three primaries, and also all of the "secondary colors" – cyan, yellow, and magenta – into a plane with white, forming a out of the RGB cube.^[10]
$V=\max(R,G,B)=M$

hexagonal pyramid

In the HSL "bi-hexcone" model, lightness is defined as the average of the largest and smallest color components (fig. 12c), i.e. the 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.^[11]
$L=\operatorname {mid} (R,G,B)={\tfrac {1}{2}}(M+m)$

mid-range

A more perceptually relevant alternative is to use , Y′, as a lightness dimension (fig. 12d). 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 Y′₇₀₉, digital NTSC uses Y′₆₀₁ according to Rec. 601 and some other primaries are also in use which result in different coefficients.^[26]^[J]
$Y'_{\text{601}}=0.299\cdot R+0.587\cdot G+0.114\cdot B$ (SDTV)

$Y'_{\text{240}}=0.212\cdot R+0.701\cdot G+0.087\cdot B$ (Adobe)

$Y'_{\text{709}}=0.2126\cdot R+0.7152\cdot G+0.0722\cdot B$ (HDTV)

$Y'_{\text{2020}}=0.2627\cdot R+0.6780\cdot G+0.0593\cdot B$ (UHDTV, HDR)

luma

TSL color space

Agoston, Max K. (2005). . London: Springer. pp. 300–306. ISBN 978-1-85233-818-3. Agoston's book contains a description of HSV and HSL, and algorithms in pseudocode for converting to each from RGB, and back again.

Computer Graphics and Geometric Modeling: Implementation and Algorithms

Cheng, Heng-Da; Jiang, Xihua; Sun, Angela; Wang, Jingli (2001). "Color image segmentation: Advances and prospects". Pattern Recognition. 34 (12): 2259. :2001PatRe..34.2259C. CiteSeerX 10.1.1.119.2886. doi:10.1016/S0031-3203(00)00149-7. S2CID 205904573. This computer vision literature review briefly summarizes research in color image segmentation, including that using HSV and HSI representations.

Bibcode

Fairchild, Mark D. (2005). (2nd ed.). Addison-Wesley. This book doesn't discuss HSL or HSV specifically, but is one of the most readable and precise resources about current color science.

Color Appearance Models

; et al. (1995). Computer Graphics: Principles and Practice (2nd ed.). Redwood City, CA: Addison-Wesley. ISBN 978-0-201-84840-3. The standard computer graphics textbook of the 1990s, this tome has a chapter full of algorithms for converting between color models, in C.

Foley, J. D.

Hanbury, Allan; Serra, Jean (December 2002). A 3D-polar Coordinate Colour Representation Suitable for Image Analysis. Vienna, Austria: Vienna University of Technology. {{}}: |work= ignored (help)

cite book

Hanbury, Allan (2008). (PDF). Pattern Recognition Letters. 29 (4): 494–500. Bibcode:2008PaReL..29..494H. CiteSeerX 10.1.1.211.6425. doi:10.1016/j.patrec.2007.11.002.

"Constructing cylindrical coordinate colour spaces"

Joblove, George H.; Greenberg, Donald (August 1978). (PDF). Computer Graphics. 12 (3): 20–25. doi:10.1145/965139.807362. Joblove and Greenberg's paper was the first describing the HSL model, which it compares to HSV.

"Color spaces for computer graphics"

Kuehni, Rolf G. (2003). Color Space and Its Divisions: Color Order from Antiquity to the present. New York: Wiley. 978-0-471-32670-0. This book only briefly mentions HSL and HSV, but is a comprehensive description of color order systems through history.

ISBN

Levkowitz, Haim; Herman, Gabor T. (1993). "GLHS: A Generalized Lightness, Hue and Saturation Color Model". . 55 (4): 271–285. doi:10.1006/cgip.1993.1019. This paper explains how both HSL and HSV, as well as other similar models, can be thought of as specific variants of a more general "GLHS" model. Levkowitz and Herman provide pseudocode for converting from RGB to GLHS and back.

CVGIP: Graphical Models and Image Processing

MacEvoy, Bruce (January 2010). . handprint.com.. Especially the sections about "Modern Color Models" and "Modern Color Theory". MacEvoy's extensive site about color science and paint mixing is one of the best resources on the web. On this page, he explains the color-making attributes, and the general goals and history of color order systems – including HSL and HSV – and their practical relevance to painters.

"Color Vision"

Poynton, Charles (1997). . poynton.com. This self-published frequently asked questions page, by digital video expert Charles Poynton, explains, among other things, why in his opinion these models "are useless for the specification of accurate color", and should be abandoned in favor of more psychometrically relevant models.

"Frequently Asked Questions About Color"

Poynton, Charles (2008). . poynton.com. Retrieved August 30, 2017.

"YUV and luminance considered harmful"

(August 1978). "Color gamut transform pairs". Computer Graphics. 12 (3): 12–19. doi:10.1145/965139.807361. This is the original paper describing the "hexcone" model, HSV. Smith was a researcher at NYIT's Computer Graphics Lab. He describes HSV's use in an early digital painting program.