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首页> 外文期刊>Vision Research: An International Journal in Visual Science >Simultaneous color constancy: how surface color perception varies with the illuminant.
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Simultaneous color constancy: how surface color perception varies with the illuminant.

机译：同时颜色恒定性：表面颜色感知如何随光源变化。

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摘要

In two experiments simultaneous color constancy was measured using simulations of illuminated surfaces presented on a CRT monitor. Subjects saw two identical Mondrians side-by-side: one Mondrian rendered under a standard illuminant, the other rendered under one of several test illuminants. The matching field was adjusted under the test illuminant so that it (a) had the same hue, saturation, and brightness (appearance match) or (b) looked as if it were cut from the same piece of paper (surface match) as a test surface under the standard illuminant. Matches were set for three different surface collections. The surface matches showed a much higher level of constancy than the appearance matches. The adjustment in the surface matches was nearly complete in the L and M cone data, and deviations from perfect constancy were mainly due to failures in the adjustment of the S cone signals. Besides this difference in amount of adjustment, the appearance and surface matches showed two major similarities. First, both types of matches were well described by simple parametric models. In particular, a model based on the notion of von Kries adjustment provided a good, although not perfect, description of the data. Second, for both types of matches the illuminant adjustment was largely independent of the surface collection in the image. The two types of matches thus differed only quantitatively, there was no qualitative difference between them.
机译：在两个实验中，使用CRT监视器上显示的照明表面的模拟来测量同时的颜色恒定性。受试者并排看到两个相同的蒙德里安：一个蒙德里安在标准光源下渲染，另一个在几个测试光源之一下渲染。在测试光源下调整匹配场，以使其（a）具有相同的色相，饱和度和亮度（外观匹配），或（b）看起来好像是从同一张纸上切下的（表面匹配）。在标准光源下的测试表面。为三个不同的表面集合设置了匹配项。表面火柴比外观火柴显示出更高的恒定度。在L和M锥数据中，表面匹配的调整几乎已完成，与完美恒定性的偏差主要是由于S锥信号的调整失败。除了调整量的这种差异之外，外观和表面匹配项还显示出两个主要相似之处。首先，两种匹配类型都可以通过简单的参数模型很好地描述。尤其是，基于von Kries调整概念的模型提供了很好的数据描述，尽管并不完美。其次，对于这两种类型的匹配，光源调整在很大程度上与图像中的表面收集无关。因此，这两种类型的匹配仅在数量上有所不同，它们之间没有质的差异。

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