Color appearance model

Acolor appearance model(CAM) is a mathematical model that seeks to describe theperceptualaspects of humancolor 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 contrast, acolor modeldefines acoordinate spaceto describe colors, such as theRGBandCMYKcolor models.)

Auniform color space(UCS) is a color model that seeks to make the color-making attributes perceptually uniform, i.e. identical spatial distance between two colors equals identical amount of perceived color difference. A CAM under a fixed viewing condition results in a UCS; a UCS with a modeling of variable viewing conditions results in a CAM. A UCS without such modelling can still be used as a rudimentary CAM.

Background

Color appearance

Further information:Color perception

Colororiginates in the mind of the observer; “objectively”, there is only thespectral power distributionof the light that meets the eye. In this sense,anycolor perception is subjective. However, successful attempts have been made to map the spectral power distribution of light to human sensory response in a quantifiable way. In 1931, usingpsychophysicalmeasurements, theInternational Commission on Illumination (CIE)created theXYZ color spacewhich successfully models human color vision on this basic sensory level.

However, the XYZ color model presupposes specific viewing conditions (such as the retinal locus of stimulation, the luminance level of the light that meets the eye, the background behind the observed object, and the luminance level of the surrounding light). Only if all these conditions stay constant will two identical stimuli with thereby identical XYZtristimulusvalues create an identicalcolor appearancefor a human observer. If some conditions change in one case, two identical stimuli with thereby identical XYZ tristimulus values will createdifferentcolor appearances (and vice versa: two different stimuli with thereby different XYZ tristimulus values might create anidenticalcolor appearance).

Therefore, if viewing conditions vary, the XYZ color model is not sufficient, and a color appearance model is required to model human color perception.

Color appearance parameters

The basic challenge for any color appearance model is that human color perception does not work in terms of XYZ tristimulus values, but in terms ofappearance parameters(hue,lightness,brightness,chroma, colorfulness and saturation). So any color appearance model needs to provide transformations (which factor in viewing conditions) from the XYZ tristimulus values to these appearance parameters (at least hue, lightness and chroma).

Color appearance phenomena

This section describes some of the color appearance phenomena that color appearance models try to deal with.

Chromatic adaptation

Chromatic adaptation describes the ability of human color perception to abstract from thewhite point(orcolor temperature) of the illuminating light source when observing a reflective object. For the human eye, a piece of white paper looks white no matter whether the illumination is blueish or yellowish. This is the most basic and most important of all color appearance phenomena, and therefore achromatic adaptation transform(CAT) that tries to emulate this behavior is a central component of any color appearance model.

This allows for an easy distinction between simple tristimulus-based color models and color appearance models. A simple tristimulus-based color model ignores the white point of the illuminant when it describes the surface color of an illuminated object; if the white point of the illuminant changes, so does the color of the surface as reported by the simple tristimulus-based color model. In contrast, a color appearance model takes the white point of the illuminant into account (which is why a color appearance model requires this value for its calculations); if the white point of the illuminant changes, the color of the surface as reported by the color appearance model remains the same.

Chromatic adaptation is a prime example for the case that two different stimuli with thereby different XYZ tristimulus values create anidenticalcolorappearance.If the color temperature of the illuminating light source changes, so do the spectral power distribution and thereby the XYZ tristimulus values of the light reflected from the white paper; the colorappearance,however, stays the same (white).

Hue appearance

Several effects change the perception of hue by a human observer:

• Bezold–Brücke hue shift:The hue of monochromatic light changes withluminance.
• Abney effect:The hue of monochromatic light changes with the addition of white light (which would be expected color-neutral).

Contrast appearance

Bartleson–Breneman effect

Several effects change the perception ofcontrastby a human observer:

• Stevens effect:Contrast increases with luminance.
• Bartleson–Breneman effect:Image contrast (of emissive images such as images on an LCD display) increases with the luminance of surround lighting.

Colorfulness appearance

Further information:Colorfulness § In color appearance models

There is an effect which changes the perception of colorfulness by a human observer:

• Hunt effect:Colorfulness increases with luminance.

Brightness appearance

There is an effect which changes the perception of brightness by a human observer:

• Helmholtz–Kohlrausch effect:Brightness increases with saturation. Not modeled by CIECAM02.
• Contrast appearance effects (see above), modeled by CIECAM02.

Spatial phenomena

Spatial phenomena only affect colors at a specific location of an image, because the human brain interprets this location in a specific contextual way (e.g. as a shadow instead of gray color). These phenomena are also known asoptical illusions.Because of their contextuality, they are especially hard to model; color appearance models that try to do this are referred to asimage color appearance models (iCAM).

Color appearance models

Since the color appearance parameters and color appearance phenomena are numerous and the task is complex, there is no single color appearance model that is universally applied; instead, various models are used.

This section lists some of the color appearance models in use. The chromatic adaptation transforms for some of these models are listed inLMS color space.

CIELAB

In 1976, theCIEset out to replace the many existing, incompatible color difference models by a new, universal model for color difference. They tried to achieve this goal by creating aperceptually uniformcolor space (UCS), i.e. a color space where identical spatial distance between two colors equals identical amount of perceived color difference. Though they succeeded only partially, they thereby created theCIELAB ( “L*a*b*” )color space which had all the necessary features to become the first color appearance model. While CIELAB is a very rudimentary color appearance model, it is one of the most widely used because it has become one of the building blocks ofcolor managementwithICC profiles.Therefore, it is basically omnipresent in digital imaging.

One of the limitations of CIELAB is that it does not offer a full-fledged chromatic adaptation in that it performs thevon Kries transformmethod directly in the XYZ color space (often referred to as “wrong von Kries transform” ), instead of changing into theLMS color spacefirst for more precise results. ICC profiles circumvent this shortcoming by using theBradford transformation matrixto the LMS color space (which had first appeared in theLLAB color appearance model) in conjunction with CIELAB.

Due to the "wrong" transform, CIELAB is known to perform poorly when a non-reference white point is used, making it a poor CAM even for its limited inputs. The wrong transform also seems responsible for its irregular blue hue, which bends towards purple as L changes, making it also a non-perfect UCS.

Nayatani et al. model

The Nayatani et al. color appearance model focuses on illumination engineering and the color rendering properties of light sources.

Hunt model

The Hunt color appearance model focuses on color image reproduction (its creator worked in theKodak Research Laboratories). Development already started in the 1980s and by 1995 the model had become very complex (including features no other color appearance model offers, such as incorporatingrod cellresponses) and allowed to predict a wide range of visual phenomena. It had a very significant impact onCIECAM02,but because of its complexity the Hunt model itself is difficult to use.

RLAB

RLAB tries to improve upon the significant limitations ofCIELABwith a focus on image reproduction. It performs well for this task and is simple to use, but not comprehensive enough for other applications.

Unlike CIELAB, RLAB uses a proper von Kries step. It also allows for tuning the degree of adaptation by allowing a customizedDvalue. "Discounting-the-illuminant" can still be used by using a fixed value of 1.0.

LLAB

LLAB is similar toRLAB,also tries to stay simple, but additionally tries to be more comprehensive than RLAB. In the end, it traded some simplicity for comprehensiveness, but was still not fully comprehensive. SinceCIECAM97swas published soon thereafter, LLAB never gained widespread usage.

CIECAM97s

After starting the evolution of color appearance models withCIELAB,in 1997, the CIE wanted to follow up itself with a comprehensive color appearance model. The result was CIECAM97s, which was comprehensive, but also complex and partly difficult to use. It gained widespread acceptance as a standard color appearance model untilCIECAM02was published.

IPT

Ebner and Fairchild addressed the issue of non-constant lines of hue in their color space dubbedIPT.The IPT color space convertsD65-adaptedXYZdata (XD65, YD65, ZD65) to long-medium-short cone response data (LMS) using an adapted form of the Hunt–Pointer–Estevez matrix (M_HPE(D65)).

The IPT color appearance model excels at providing a formulation for hue where a constant hue value equals a constant perceived hue independent of the values of lightness and chroma (which is the general ideal for any color appearance model, but hard to achieve). It is therefore well-suited forgamut mappingimplementations.

ICtCp

ITU-R BT.2100 includes a color space calledICtCp,which improves the original IPT by exploring higher dynamic range and larger colour gamuts.ICtCp can be transformed into an approximately uniform color space by scaling Ct by 0.5. This transformed color space is the basis of the Rec. 2124 wide gamut color difference metric ΔE_ITP.

CIECAM02

After the success ofCIECAM97s,the CIE developedCIECAM02as its successor and published it in 2002. It performs better and is simpler at the same time. Apart from the rudimentaryCIELABmodel, CIECAM02 comes closest to an internationally agreed upon “standard” for a (comprehensive) color appearance model.

Both CIECAM02 and CIECAM16 have some undesirable numerical properties when implemented to the letter of the specification.

iCAM06

iCAM06is animage color appearance model.As such, it does not treat each pixel of an image independently, but in the context of the complete image. This allows it to incorporate spatial color appearance parameters like contrast, which makes it well-suited forHDRimages. It is also a first step to deal withspatial appearance phenomena.

CAM16

The CAM16 is a successor of CIECAM02 with various fixes and improvements. It also comes with a color space called CAM16-UCS. It is published by a CIE workgroup, but is not CIE standard.CIECAM16 standard was released in 2022 and is slightly different.

CAM16 is used in theMaterial Designcolor system in a cylindrical version called "HCT" (hue, chroma, tone). The hue and chroma values are identical to CAM16. The "tone" value is CIELAB L*.

OKLab

A 2020 UCS designed for normal dynamic range color. Same structure as CIELAB, but fitted with improved data (CAM16 output for lightness and chroma; IPT data for hue). Meant to be easy to implement and use (especially from sRGB), just like CIELAB and IPT were, but with improvements to uniformity.

As of September 2023, it is part of theCSS colorlevel 4 draftand it is supported by recent versions of all major browsers.

Other models

OSA-UCS

A 1947 UCS with generally good properties and a conversion from CIEXYZ defined in 1974. The conversion to CIEXYZ, however, has no closed-form expression, making it hard to use in practice.

SRLAB2

A 2009 modification of CIELAB in the spirit of RLAB (with discounting-the-illuminant). Uses CIECAM02 chromatic adaptation matrix to fix the blue hue issue.

JzAzBz

A 2017 UCS designed for HDR color. Has J (lightness) and two chromaticities.

XYB

A family of UCS used inGuetzliandJPEG XL,with a main goal in compression. Better uniformity than CIELAB.

References

• Fairchild, Mark D. (2013).Color Appearance Models.Wiley-IS&T Series in Imaging Science and Technology (3 ed.). Hoboken:John Wiley & Sons.ISBN978-1-119-96703-3.