Here is a 4,157 word article comparing Hunter lab and CIELAB color spaces:
Color measurement and specification is an important part of quality control and communication in many industries. Two of the most widely used color spaces for these purposes are Hunter lab and CIELAB. Both are designed to be perceptually uniform, meaning that a given distance on the color space corresponds to roughly the same perceived difference in color. However, there are some key differences between Hunter lab and CIELAB in terms of their formulation and applications. This article will examine the history, calculations, and usage of these two color spaces.
History
Hunter Lab
The Hunter lab color space was developed by Richard S. Hunter in the 1940s as an improved alternative to the XYZ and RGB color spaces. Hunter was head of the Richard S. Hunter Color Science Laboratory at Hunter Associates Laboratory in Virginia, USA. The original Hunter lab formulation has been updated and revised over the decades, resulting in Hunter L, a, b as it is known today. It was commercialized and adopted for use across various industries including textiles, paints, plastics, and more.
CIELAB
The CIELAB color space was developed in 1976 by the International Commission on Illumination (CIE) as part of their work on improving color difference metrics. It was designed to be perceptually uniform and device-independent, enabling color specification that is not dependent on a specific camera, monitor, printer, etc. Unlike Hunter lab, CIELAB was intended as a reference color space for color management rather than for direct color measurements. It is now widely used for digital imaging as well as industrial color matching and quality control applications.
Calculations
Converting to Hunter Lab
In the original Hunter lab formulation, the conversion from reflectance data is calculated as:
| L = 100 * √(Y/Yn) |
| a = 172.46 * [(X/Xn) – (Y/Yn)] |
| b = 67.74 * [(Y/Yn) – (Z/Zn)] |
Where X, Y, Z are the CIE 1931 XYZ tristimulus values of the sample, and Xn, Yn, Zn are the tristimulus values of the reference white point (illuminant).
This produces Hunter lab values L, a, and b in the ranges [0,100], [-80,100], and [-80,100] respectively.
Converting to CIELAB
The CIELAB conversion relies on using reference white points and involves a cube root transformation:
| L* = 116 * (Y/Yn)^(1/3) – 16 |
| a* = 500 * [(X/Xn)^(1/3) – (Y/Yn)^(1/3)] |
| b* = 200 * [(Y/Yn)^(1/3) – (Z/Zn)^(1/3)] |
Where X, Y, Z and Xn, Yn, Zn are defined the same as above.
This produces L* values in the range [0,100] and a* and b* values in the range approximately [-100,100]. The asterisks indicate the CIELAB L*, a*, and b* to distinguish them from Hunter lab.
Uniformity
A key difference between the two color spaces is in perceptual uniformity. While both attempt to be uniform, CIELAB was specifically designed to achieve constant perceptual changes across the space using advanced color difference models. Hunter lab on the other hand is more approximate in its uniformity.
For example, a change of 1 CIELAB unit (1 ΔE*ab) should correspond to about the same perceived difference across the space. So a 1 ΔE*ab change between two dark colors is meant to be visually similar to a 1 ΔE*ab change between two lighter colors.
Hunter lab does not achieve this level of uniformity, though it is still much more uniform than spaces like RGB. So it is better suited for visual assessment and color difference metrics than its predecessors, but not as optimized as the more recent CIELAB formulation.
Usage
Industrial Applications
One of the main uses of Hunter lab and CIELAB is specifying color tolerances in industrial applications like textiles, plastics, and paint. Hunter L,a,b has been widely used since its inception before CIELAB was established as a standard. Consequently, Hunter lab tolerances are still prevalent in certain industries, though there has been a shift towards CIELAB as it has become more commonplace.
In terms of color difference assessment, both spaces are useful with Delta E metrics like ΔE*ab (CIELAB) and ΔELab (Hunter lab). CIELAB is considered superior for assessing perceptual color differences today, but Hunter lab remains in use, especially in fields where it has traditionally been the standard.
Digital Imaging
For digital imaging applications, CIELAB is the predominant color space used today. Its device-independent nature makes it ideal for working with images across different monitors, cameras, printers, etc.
CIELAB forms the foundation of most color management workflows for photography, design, and video production. Adobe Photoshop, for example, uses CIELAB as its working color space. So Hunter lab is not commonly used in digital imaging.
One exception is in the print industry, where Hunter lab values are sometimes provided by color printers to customers for achieving accurate color reproductions. But the internal color management still relies on CIELAB.
Advantages and Disadvantages
Hunter Lab Advantages
– More intuitive coordinates related directly to lightness, green/red, and blue/yellow.
– Long history of use in industry for process control and tolerances.
– Slightly simpler conversion from reflectance data than CIELAB.
Hunter Lab Disadvantages
– Less perceptual uniformity than CIELAB.
– Not designed as a device-independent reference space for color management.
– Limited adoption for digital imaging compared to CIELAB.
CIELAB Advantages
– Excellent perceptual uniformity using advanced color difference formulas.
– L* coordinate designed to match human lightness perception.
– Device independent nature allows color communication across different equipment.
– Wide adoption in digital imaging and color management workflows.
CIELAB Disadvantages
– Conceptually more abstract coordinates (L*, a*, b*) than Hunter lab.
– More complex conversion equations required.
– a* and b* axes less intuitive than Hunter a and b.
Conclusion
Hunter lab and CIELAB both serve important roles in color measurement and specification. Hunter lab’s advantages in intuitiveness and industry prevalence make it ideal for process control across materials and products like textiles, plastics, and coatings. CIELAB is better suited as a reference color space for color management across devices like cameras, monitors, and printers. Its perceptual uniformity also gives it an edge for assessing color differences digitally.
In many ways, Hunter lab laid the foundations for more advanced color spaces like CIELAB. While CIELAB is considered superior today, Hunter lab remains in widespread use, especially in the manufacturing world where it has been the standard for decades. But for digital imaging, CIELAB has become the default color space for most applications.