Color appearance models are usually based on equations with fixed numerical coefficients that were predetermined to yield optimal agreement for a selected standard observer. Here we address the well-known fact that, among color-normal observers, there are significant differences of cone fundamentals, which often cause observer metamerism. This is not fully addressed by many appearance models. It might seem that observer metamerism could be accurately predicted by substituting an individual's color matching functions into an otherwise-unchanged color appearance model, but this is not assured because the model's coefficients were not designed for the new observer. Here we explore a solution related to how the visual system tends to compensate for changes in color information arising from variations cone fundamentals. 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 adjust the model coefficients automatically, in response to switching between the cone fundamentals for different observers. This feature is intended to model long term contrast adaptation in the vision system by maintaining the average long-term levels of color contrast. 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.

中文翻译：

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结合对比度适应的颜色外观模型——对色觉个体差异的影响

颜色外观模型通常基于具有固定数值系数的方程，这些方程预先确定以产生选定标准观察者的最佳一致性。在这里，我们解决了一个众所周知的事实，即在颜色正常的观察者中，锥体基本面存在显着差异，这通常会导致观察者同色异谱。许多外观模型没有完全解决这个问题。看起来观察者同色异谱可以通过将个人的颜色匹配函数替换为其他不变的颜色外观模型来准确预测，但这并不能保证，因为模型的系数不是为新观察者设计的。在这里，我们探索了一种解决方案，该解决方案与视觉系统如何倾向于补偿由变化锥体基础引起的颜色信息变化有关。以此目的，我们开发了一个简单的颜色外观模型，该模型仅使用几个数值系数，但在选定的标准照明条件下准确地预测了 Munsell 样本的感知属性。然后，我们添加了一个反馈循环来自动调整模型系数，以响应不同观察者的锥体基础之间的切换。此功能旨在通过保持颜色对比度的平均长期水平来模拟视觉系统中的长期对比度适应。将这种适应原则纳入颜色外观模型可以更好地评估显示器和照明系统，以帮助改善大多数观察者的颜色外观。在选定的标准照明条件下准确预测 Munsell 样本的感知属性。然后，我们添加了一个反馈循环来自动调整模型系数，以响应不同观察者的锥体基础之间的切换。此功能旨在通过保持颜色对比度的平均长期水平来模拟视觉系统中的长期对比度适应。将这种适应原则纳入颜色外观模型可以更好地评估显示器和照明系统，以帮助改善大多数观察者的颜色外观。在选定的标准照明条件下准确预测 Munsell 样本的感知属性。然后，我们添加了一个反馈循环来自动调整模型系数，以响应不同观察者的锥体基础之间的切换。此功能旨在通过保持颜色对比度的平均长期水平来模拟视觉系统中的长期对比度适应。将这种适应原则纳入颜色外观模型可以更好地评估显示器和照明系统，以帮助改善大多数观察者的颜色外观。此功能旨在通过保持颜色对比度的平均长期水平来模拟视觉系统中的长期对比度适应。将这种适应原则纳入颜色外观模型可以更好地评估显示器和照明系统，以帮助改善大多数观察者的颜色外观。此功能旨在通过保持颜色对比度的平均长期水平来模拟视觉系统中的长期对比度适应。将这种适应原则纳入颜色外观模型可以更好地评估显示器和照明系统，以帮助改善大多数观察者的颜色外观。