The study, published in the Optica Publishing Group journal Optics Express, addresses a blind spot in the standard machinery of lighting science. Conventional color-quality metrics — the tools engineers use to certify whether a lamp renders colors faithfully — rest on a mathematical model of human color vision built around a standard observer whose ocular media transmit light the way a young adult’s eye does. A spectral power distribution that scores perfectly on such a metric may still deliver a distorted signal to an eighty-year-old retina, because the yellowed lens attenuates the short-wavelength end of the spectrum before it ever reaches the cone photoreceptors. As research team leader Qi Dai of Fudan University explained, the lens inside the eye gradually yellows and absorbs more short-wavelength light as people age, which can make similar colors harder to discriminate. The team’s goal, Dai said, was to use new knowledge about how vision changes with age to guide the design of white light that measurably helps older adults distinguish colors while retaining conventional lighting color-quality requirements.

The model works by estimating how easily a person of a given age can tell apart similar colors under a specific illuminant. It takes three inputs and combines them: the spectral power distribution of the light source, the spectral reflectance properties of the colored surfaces being viewed — that is, which wavelengths each object bounces back — and the sensitivities of the eye’s three cone types, adjusted for age. Those cone sensitivities, typically labeled L, M, and S for long, medium, and short wavelengths, feed the model with an age-corrected description of what signals the retina actually receives. When the S cones, which respond to blue light, are starved by a yellowing lens, the differences between their responses to two similar colors shrink, and with them the observer’s ability to see the two objects as distinct. By quantifying that loss computationally, the model can compare candidate light sources not by how bright or white they appear, but by how much color-separating information they preserve for an older visual system.

With the model in hand, the researchers turned it loose on an enormous design space. They evaluated 11,541 possible light spectra, each of which satisfied the standard requirements for white-light chromaticity and color rendering near a color temperature of 5000 kelvin — a neutral, daylight-like white comparable to the standardized D50 reference illuminant used in the color industry. The result was striking: spectra that would be visually indistinguishable by conventional metrics could differ substantially in how well they were predicted to support color discrimination in older adults. Two physically different white lights, both certified as high-quality, both matching at the same color temperature, could nonetheless deliver meaningfully different visual worlds to an aged observer. That gap between conventional quality metrics and age-adjusted performance is precisely the space the new model is designed to exploit.

From that analysis, the team selected two candidate spectra. The first, designated P1, was optimized purely to maximize color discrimination for older eyes. The second, P2, was engineered as a compromise, balancing improved color discrimination against the requirement that familiar object colors still look natural — a critical constraint, because a light that exaggerated or shifted hues would undermine confidence in tasks such as choosing clothing or judging food. For a modeled eighty-five-year-old observer, the P1 spectrum was predicted to recover about 49 percent of the age-related loss in color discrimination, while P2 recovered about 36 percent. Those are substantial recoveries given that both spectra look, on paper and to a younger viewer, like perfectly ordinary neutral-white light.

Simulation, however, is only as good as its predictions, so the team took the spectra into the laboratory. Thirty-four adult volunteers, all aged seventy or above, performed a color-sorting test under three lighting conditions: the P1 spectrum, the P2 spectrum, and an LED-simulated D50 daylight reference. Crucially, the researchers held the practical variables constant across all three conditions — the illuminance, meaning the amount of light falling on the task, and the color temperature were nearly identical in each case. This meant that any difference in performance could be attributed not to brightness or apparent warmth, but to the fine structure of the spectra themselves, the specific mixture of wavelengths each source delivered.

The results confirmed the model’s promise. Both optimized spectra significantly improved performance on the color-sorting test compared with the simulated daylight reference. The improvement was not a subtle statistical artifact confined to averages: at the individual level, 26 of the 34 participants — 76.5 percent — showed better color discrimination under the P1 spectrum, and 22 of 34, or 64.7 percent, improved under P2. For a population in which age-related color vision decline is the norm rather than the exception, a lighting change invisible to conventional metrics produced clear, measurable gains for the majority of older users tested.

The practical implications reach well beyond the laboratory. Dai noted that lighting designed with aging eyes in mind could help older adults remain confident and independent while performing everyday tasks such as reading labels, sorting medications, judging food, or choosing clothing. In a family home or a care facility, such lighting could support older users while retaining the characteristics needed for general use. Because both optimized spectra met conventional criteria for white-light chromaticity and color rendering, they can be installed in spaces shared by people of different ages without younger residents experiencing anything unusual — familiar colors under familiar-looking white light. Dai added that the findings suggest the model could be used to design everyday lighting that makes it easier for older adults to see colors while keeping familiar object colors looking natural, and that since the spectra also satisfy standard white-light and color-rendering requirements, they could serve mixed-age environments directly.

The approach is not limited to lighting. Dai pointed out that the same framework could in principle be extended to capture how displays — the screens of phones, computers, and televisions — appear to older viewers, or to other groups with known differences in spectral sensitivity, although doing so would require dedicated modeling and human testing to validate. Meanwhile, OPPLE Lighting is already working to translate the findings into practical commercial lighting products, moving the research from the journal toward real fixtures. The researchers themselves are careful to note the boundaries of the current evidence: before wider adoption, additional studies should evaluate the approach in everyday settings and at other commonly used illuminances and color temperatures, and testing with people across a wider range of ages, including younger users, would provide valuable information for lighting destined for shared spaces. Even so, the study establishes something the lighting industry has lacked: a practical, validated link between describing how aging vision actually works and designing illumination that supports it. As populations age worldwide, the finding that a well-chosen mixture of wavelengths — invisible to standard metrics, imperceptible to the young — can return nearly half of what time takes from older eyes may reshape how bedrooms, kitchens, hospitals, and care homes are lit.

Subject of Research: Age-adjusted computational modeling of white-light spectra to improve color discrimination in older adults

Article Title: New model informs lighting design that works better for aging eyes

Article References: New model informs lighting design that works better for aging eyes. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: aging vision, color discrimination, lighting design, lens yellowing, spectral power distribution, color rendering, Optics Express, LED lighting, cone sensitivities, D50 illuminant, Fudan University, older adults

To understand the problem, it helps to look at how displays create color in the first place. Every television, monitor, and cinema projector builds its images from three primary light sources: red, green, and blue. By mixing these primaries in different proportions, the device can reproduce a broad spectrum of colors. On older displays, the primary emissions were relatively broad in their spectral output, which meant that even though individual viewers differed in their color vision, those differences tended to average out and the colors looked broadly similar to most people. The technology was, in a sense, forgiving of human variability.

Modern wide-gamut displays are far less forgiving. To achieve more vivid and saturated colors, manufacturers have turned to narrowband primary sources, which emit light concentrated in a very tight band of wavelengths. This produces a larger color gamut, meaning the display can show a wider range of colors, but it also amplifies the consequences of individual differences in color vision. When the light sources are narrow, small shifts in a viewer’s visual sensitivity translate into noticeable shifts in perceived color. Two people watching the same calibrated screen may therefore see subtly, and sometimes not so subtly, different images.

Andy Rider of the Institute of Ophthalmology at University College London, one of the researchers behind the new model, framed the challenge in terms of the people who make the content. The people who produce films and television shows want their work to look the same whatever device it is being viewed on, a goal that is complicated both by differences in people’s color vision and by outdated calibration methods. The new model takes into account individual variability in color vision and can be used to determine how best to adjust the three primary colors of a specific display to provide the best viewing experience for as many people as possible.

At the heart of the research is a physiological model of human color vision that captures how perception actually differs between individuals. One of the variations the researchers modeled is deuteranomaly, a common form of red-green color vision deficiency that affects roughly one in twenty men. In the model, this condition is represented by shifting the wavelengths detected by the eye’s cone cells, the photoreceptors responsible for color vision. By simulating how those shifted sensitivities interact with the narrowband light emitted by modern displays, the model can predict where colors will appear mismatched for affected viewers.

The model also accounts for changes in the eye’s lens. The lens filters out a portion of short-wavelength light before it reaches the retina, and the amount of that filtering varies both with age and from person to person. By varying the short-wavelength filtering in their simulations, the researchers could represent how the same display might appear to a younger viewer compared with an older one, or to two people of the same age whose lenses differ naturally. These physiological parameters, combined with the spectral properties of the display primaries, form the basis of the model’s predictions.

A crucial part of the work involves bridging two worlds that rarely meet: the physiology of vision and the engineering of display calibration. Rider explained that the researchers combined their realistic model of human color vision with displays that are usually calibrated and analyzed in a more engineering-based framework. Calibration is normally performed with instruments such as photometers and colorimeters, which measure light output but poorly simulate its effect on human vision. The new model helps improve those simulations, offering a way to predict not just what light a display emits but what a range of actual human observers will perceive.

To test the model’s usefulness, the researchers applied it to sixteen different displays, including consumer televisions, professional monitors used in film production, and cinema projectors. The analysis revealed that some displays exhibit much larger color discrepancies between observers than others. In other words, the choice of display technology and primary spectra directly determines how much a given screen’s colors will diverge across a population of viewers. This finding gives manufacturers a concrete, quantitative tool for evaluating whether a particular design will deliver consistent color to a broad audience or only to a narrow slice of it.

The model also yielded a practical insight about which parts of the display spectrum matter most for which viewers. The spectrum of the blue primary light strongly influences how displays are seen by people of different ages, because of its interaction with the lens’s short-wavelength filtering. Meanwhile, the spectra of the red and green primaries are what drive mismatches for people with different kinds of red-green color vision deficiency. This separation suggests a clear path forward: by changing the spectra of the primary light sources, engineers could reduce the mismatches seen by different observers without sacrificing the wide color gamut that makes modern displays appealing.

The implications extend beyond screens. Rider noted that although the research focused on displays, the modeling approach can also be used to examine similar color discrepancies, such as those arising from energy-efficient LED lighting compared with traditional incandescent lightbulbs, or in other color applications where dyes and pigments change how objects reflect or absorb light. Any situation in which a light source’s spectrum interacts with the variability of human vision could benefit from the same analysis, from architectural lighting to printed materials and signaling systems.

The researchers are careful to note the limits of the current work. Their model is based on a physiological framework of color vision that draws on their own research, but the model’s predictions have not yet been verified with real human observers. Validation is the next step, and the team plans to use what they learn to guide the development of displays that produce a wide gamut of vivid colors with better color consistency across viewers. One possibility they raise is the use of more than three primary light sources in a display, which would allow finer adjustments to produce accurate colors for a wider range of people.

The underlying tension the research exposes is one that has been building in the display industry for years. Calibration standards in common use today were developed about a hundred years ago and, as Rider pointed out, do not align with normal color vision. This can make modern displays look wrong even when they have been calibrated to look the same, because the standard observer on which calibration is based does not represent the real diversity of human eyes. A century-old reference, designed for a different era of light sources, is now being asked to govern screens whose narrowband primaries were unimaginable when it was created.

What makes this research notable is that it turns a vague complaint, that colors look different on different screens or to different people, into a quantifiable, physiologically grounded problem with an engineering solution. By simulating how narrowband red, green, and blue primaries interact with shifted cone sensitivities and age-related lens filtering, the model identifies exactly where and why color reproduction goes wrong, and points to adjustments in primary spectra as the fix. If validated with human observers, the approach could influence the next generation of televisions, professional monitors, and cinema projectors, bringing the industry closer to the ideal that filmmakers have always pursued: a film that looks the same, in every color, for everyone watching.

Subject of Research: Individual differences in human color vision and their effect on modern wide-gamut display color perception

Article Title: New research reveals why modern display colors can look different to different people

Article References: New research reveals why modern display colors can look different to different people. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: color vision, display technology, wide color gamut, deuteranomaly, cone cells, display calibration, narrowband primaries, Optics Express, University College London, color perception, lens filtering, computational modeling