The Munsell color system is a color space that specifies colors based on three properties: hue, value (lightness), and chroma (color purity). Developed by Albert H. Munsell in the early 20th century, it is one of the first systematic color spaces. While the Munsell system is widely used and provides many benefits, it also has some limitations.
Lack of Perceptual Uniformity
One major disadvantage of the Munsell system is that it is not perceptually uniform. This means that a given distance in Munsell space does not directly correlate to perceived color difference. For example, a shift in hue of 5 units can look dramatically different than a shift of 5 units in value or chroma. This makes it difficult to quantitatively specify color tolerance or difference limits using Munsell coordinates.
Munsell’s uneven spacing of hue steps is partly to blame for the lack of perceptual uniformity. Steps between hues are not equidistant visually. For example, there is a larger perceptual difference between Yellow and Green than there is between Red and Yellow. But in Munsell’s defined hue circles, these steps are equidistant. This results in visual distortions of the color space.
Difficulty Communicating Tolerances
The lack of perceptual uniformity also makes it difficult to consistently communicate color tolerances or specifications. Saying a color should be within +/- 5 hue steps in Munsell could lead to wildly varying amounts of visible difference depending on the starting hue. The irregularities make it hard to quantify difference limits across the space in a meaningful way.
This becomes especially problematic for industries like product manufacturing where colors must meet strict specifications. Companies often set color tolerances defined in Munsell units. But the uneven nature of the space means meeting these specs does not always guarantee a match visually. Communicating color quality or tolerance in production becomes challenging.
Limitations for Digital Applications
While the Munsell system originated as a physical collection of painted color swatches, color specification today often involves digital software applications. But the Munsell color space has some limitations when it comes to digital representation.
One is that the Munsell system does not have a defined white point for standard viewing conditions. This means that neutral colors can vary when encoding Munsell coordinates digitally. The white point affects all other color values. So without a reference, accurate reproduction is difficult.
Also, the Munsell space is not rigorously defined mathematically. This can lead to small variations when converting to and from Munsell coordinates in software. So even if two applications both use Munsell,colors may not match perfectly between them.
Ambiguity in Dark Colors
The Munsell system runs into some ambiguity in defining very dark colors with low value and chroma. It can be difficult to assign firm hue designations to dark neutrals and near-blacks. Often, there is noticeable hue variation when viewing these dark colors under different illuminants.
So two dark neutral samples with slight differences in apparent hue can end up being designated the same Munsell value/chroma coordinates. This makes precise specification difficult. It also means that manufactured colors meant to match dark Munsell coordinates may show noticeable variation under lighting changes.
Age of Munsell Samples
An inherent limitation of physical color order systems like Munsell is fading or changing of printed samples over time. As the original Munsell book of swatches ages, the colors degrade. This means that new editions must be printed periodically to maintain accuracy.
But even new printings can have noticeable variation from previous editions. One lab study found average color differences between new and old editions to be up to 4.3 ΔE* units, enough to be clearly visible. So depending on which Munsell edition is used as a reference, there can be significant color deviations.
Limited Gamut
The range or gamut of colors available in the Munsell Book of Color is relatively limited compared to the visible spectrum. Recent studies indicate the Munsell gamut covers only 77% of visible colors under common illuminants. This is far below wider gamut systems like CIE LAB (100% coverage) or even sRGB (over 90%).
Many vivid saturated colors, especially in the blue-violet range, fall outside the Munsell gamut. Specifying these colors is only possible by extrapolating beyond the reference samples. This leads to inaccuracies and ambiguity when trying to communicate exact shades.
Concerns Over Neutral Grays
Another sampling limitation is that Munsell’s gray scale along the neutral axis is relatively sparse. There are few samples representing low chroma grays. This can make interpolation between neutral reference points unreliable. The result is that neutral grays in Munsell space often do not correlate well to true achromatic colors.
This also means Munsell has difficulty accurately representing gray color tolerances. A supposedly neutral range of grays defined in Munsell units may still contain visibly non-neutral samples. So care must be taken when trying to specify neutral/grayscale colors in Munsell terms.
Lack of Standard Observer
Unlike more recent color systems, Munsell does not precisely define a standard observer for measurements. The parameters of the observer (such as field of view) are left unspecified. But the observer can impact things like perceived lightness and chroma. So this creates some ambiguity when specifying colors in Munsell space.
Later color order systems like CIELAB are based around a 2-degree standard observer. Munsell’s lack of a defined observer opens the door to inconsistencies and errors during measurement and communication.
Difficulty Accurately Measuring Samples
Physical measurement and digital conversion introduce uncertainties in representing Munsell colors. Measuring the Munsell swatches involves visual color matching and interpolation by a human operator. Studies show high variability between different operators assigning Munsell coordinates.
Digitizing the swatches also introduces potential errors in things like lighting, calibration, and gamut mapping. Going from the physical Munsell book to a digital format is inherently imprecise. All of these factors decrease the reliability of measurements.
Lack of Device Independence
When using the Munsell system for digital color control, there is the potential for device-dependent color shifts. Unlike a strictly numeric system like CIELAB, Munsell relies on visual comparisons to physical swatches. This ties it to the specific illuminant and medium of those swatches.
So when converting Munsell coordinates to different devices like monitors or printers, visual shifts occur that simple gamut mapping cannot correct. This makes consistent color control across different mediums difficult compared to device-independent systems.
Not as Perceptually Intuitive as Natural Color Systems
One of the goals of the Munsell system was to order colors in a perceptually logical way. But modern research has shown that alternative color models like the Natural Color System (NCS) more closely align to visual intuition. The NCS system is based directly on how humans visually perceive color similarity and difference.
By comparison, the irregularities of Munsell space seem somewhat unintuitive and arbitrary. For example, hue steps are wider between yellow and green than other hues. Values are also spaced non-linearly, making lightness relationships confusing. More uniform and perceptually aligned systems like NCS are often viewed as superior.
Lack of Opponent Color Dimensions
Unlike some more recent color models, Munsell does not define visual opponent color dimensions like red/green and yellow/blue. Research shows the visual system encodes color into these opponent channels. But in Munsell space, hues are arranged in a circle without opponent structure.
This lack of opponent mapping makes Munsell less intuitive from a visual processing perspective. Specifying colors in terms of perceptual opponency (like NCS and DIN99) allows for more natural color difference scaling and visual alignments.
Indirect Chromaticity Definitions
Munsell chromaticity coordinates are defined indirectly by interpolating between Munsell space samples. This leads to some ambiguity compared to color systems like CIELAB that directly quantify chromaticity in 2-dimensional color opponent space.
Indirect chromaticity also requires estimating Munsell coordinates of imaginary samples outside the gamut surface. This process relies on visual extrapolation and introduces perceptual non-uniformities. A more explicitly defined chromaticity plane could improve gamut mapping and color difference metrics.
Conclusion
Despite its longevity and widespread use, the Munsell color system has some limitations that impact its utility in modern color control applications. Lack of perceptual uniformity, indirect chromaticity definitions, concerns over neutral grays, and other factors outlined here present challenges.
However, Munsell’s orderly arrangement of colors did establish the foundation for more advanced color models. Many newer systems aim to improve upon the principles first put forth by Munsell over 100 years ago. His pioneering influence is still felt across the field of color science.
