HCL color space

HCL (Hue-Chroma-Luminance) is a commonly used alternative name for the L*C*h(uv) color space, also known as the cylindrical representation or polar CIELUV. It is a color space model designed to accord with human perception of color. HCL has been adopted by information visualization practitioners to present data without the bias implicit in using varying saturation.[1][2]

Overview

HCL is designed to address deficiencies in other models such as HSL and HSV (Hue-Saturation-Lightness and Hue-Saturation-Value). As the names imply, saturation is part of these models. Saturation is intended to measure the intensity of colorfulness, but different colors appear to the eye to have different intensity, even when they have the same saturation value according to HSL or HSV.

HCL uses the LUV model defined by the International Commission on Illumination (CIE) in 1976, translated into polar coordinates. LUV is designed to be perceptually uniform, but the uv coordinates are not very intuitive. HCL preserves the L (luminance) axis of Luv, but transforms uv to polar coordinates, where the distance from zero is the chroma (an alternative measure of colorfulness), and the phase (angle) is our familiar hue. The older Munsell color system is based on different mathematics, but has some similarity to HCL.

Implementations

d3.js Data Driven Documents JavaScript library

HCL colorspace for the R statistical programming language

Other uses of HCL acronym

The terms hue, chroma and luminance or lightness can, of course, be used in other contexts. Thus a discussion of HCL may not refer specifically to polar CIELUV.

The chroma.js JavaScript library uses HCL to refer to the cylindrical representation of the CIE Lab color space, not LUV. Lab is very widely used for relective (e.g. print) work, but LUV is often preferred[3] for additive (transmitted) color, such as on computer displays.

The same HCL acronym has been used for a different color model developed by M. Sarifuddin and Rokia Missaoui at the Université du Québec en Outaouais (UQO) and first published in 2005.[4] The Sarifuddin and Missaoui model has been criticized by some commentators.[5][6]

References

  1. Ihaka R. "Colour for Presentation Graphics.".
  2. Zeileis, Achim; Hornik, Kurt. "Choosing Color Palettes for Statistical Graphics". Vienna University of Economics and Business. Retrieved 2015-10-20.
  3. Ihaka, op. cit.
  4. M. Sarifuddin and Rokia Missaoui, A New Perceptually Uniform Color Space with Associated Color Similarity Measure for Content-Based Image and Video Retrieval
  5. Tatarize blog post
  6. Discussion on StackOverflow
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