Observers use a wide range of color names, including white, to describe monochromatic flashes with a retinal size comparable to that of a single cone. We model such data as a consequence of information loss arising from trichromatic sampling. The model starts with the simulated responses of the individual L, M, and S cones actually present in the cone mosaic and uses these to reconstruct the L-, M-, and S-cone signals that were present at every image location. We incorporate the optics and the mosaic topography of individual observers, as well as the spatio-chromatic statistics of natural images. We simulated the experiment of H. Hofer, B. Singer, & D. R. Williams (2005) and predicted the color name on each simulated trial from the average chromaticity of the spot reconstructed by our model. Broad features of the data across observers emerged naturally as a consequence of the measured individual variation in the relative numbers of L, M, and S cones. The model`s output is also consistent with the appearance of larger spots and of sinusoidal contrast modulations. Finally, the model makes testable predictions for future experiments that study how color naming varies with the fine structure of the retinal mosaic.
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机译：观察者使用各种各样的颜色名称（包括白色）来描述具有与单个圆锥体相当的视网膜大小的单色闪光。我们将这些数据建模为三色采样导致信息丢失的结果。该模型从实际存在于圆锥体镶嵌中的各个L，M和S圆锥体的模拟响应开始，并使用这些响应来重构出现在每个图像位置的L，M和S圆锥体信号。我们结合了各个观察者的光学特性和镶嵌地形，以及自然图像的时空色差统计信息。我们模拟了H. Hofer，B。Singer和D. R. Williams（2005）的实验，并从我们模型重建的斑点的平均色度中预测了每个模拟试验的颜色名称。由于测量到的L，M和S圆锥的相对数量的个体差异，自然而然地出现了跨观察者的数据的广泛特征。该模型的输出还与较大斑点和正弦对比度调制的外观一致。最后，该模型为将来的实验提供了可检验的预测，这些实验研究了色彩命名如何随视网膜马赛克的精细结构而变化。
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