Color appearance model incorporating contrast adaptation - implications for individual differences in color vision

Color appearance models use standard color matching functions to derive colorimetric information from spectral radiometric measurements of a visual environment, and they process that information to predict color perceptual attributes such as hue, chroma and lightness. That processing is usually done by equations with fixed numerical coefficients that were predetermined to yield optimal agreement for a given standard observer. Here we address the well-known fact that, among color-normal observers, there are significant differences of color matching functions. These cause disagreements between individuals as to whether certain colors match, an important effect that is often called observer metamerism. Yet how these individual sensitivity differences translate into differences in perceptual metrics is not fully addressed by many appearance models. It might seem that appearance could be predicted by substituting an individual's color matching functions into an otherwise-unchanged color appearance model, but this is problematic because the model's coefficients were not optimized for the new observer. Here we explore a solution guided by the idea that processes of adaptation in the visual system tend to compensate color perception for differences in cone responses and consequent color matching functions. For this purpose, we developed a simple color appearance model that uses only a few numerical coefficients, yet accurately predicts the perceptual attributes of Munsell samples under a selected standard lighting condition. We then added a feedback loop to automatically adjust the model coefficients, in response to switching between cone fundamentals simulating different observers and color matching functions. This adjustment is intended to model long term contrast adaptation in the vision system by maintaining average overall color contrast levels. Incorporating this adaptation principle into color appearance models could allow better assessments of displays and illumination systems, to help improve color appearances for most observers.