用滤镜模型解释色觉差异，揭示年龄导致的黄斑变化影响
Modeling spectral filtering effects on color-matching functions: Implications for observer variability
- 通过计算推断滤镜特性，将无滤镜与有滤镜的色匹配函数关联
- 发现一个抑制短波的黄色滤镜可转换两组经典色匹配函数数据
- 支持年龄相关晶状体黄化是色觉差异主因，适合视觉建模研究者
本研究探究光谱滤镜对色匹配函数（CMFs）的影响及其对观察者变异建模的意义。我们对两名观察者在双分区视场下，分别进行有无光谱滤镜条件下的色匹配实验。采用新计算方法，估算了将无滤镜CMFs转换为有滤镜CMFs所需的滤镜透射率和变换矩阵。统计分析显示，估计值与实测滤镜特性在中心波长区域高度一致。将该方法应用于比较Stiles和Burch 1955（SB1955）平均观察者CMFs与先前发表的“ICVIO”平均观察者CMFs，发现一个‘黄色’（抑制短波）滤镜能有效实现两者间的转换。这一结果支持假设：两组数据差异源于年龄相关的晶状体黄化（ICVIO观察者平均年龄49岁，SB1955为30岁）。该方法仅需单一滤镜即可高效表征观察者变异，相比传统三函数方案减少实验开销，同时保持对个体色觉差异的准确刻画。
原文摘要 · Abstract (English)
This study investigates the impact of spectral filtering on color-matching functions (CMFs) and its implications for observer variability modeling. We conducted color matching experiments with two observers, both with and without a spectral filter in front of a bipartite field. Using a novel computational approach, we estimated the filter transmittance and transformation matrix necessary to convert unfiltered CMFs to filtered CMFs. Statistical analysis revealed good agreement between estimated and measured filter characteristics, particularly in central wavelength regions. Applying this methodology to compare between Stiles and Burch 1955 (SB1955) mean observer CMFs and our previously published "ICVIO" mean observer CMFs, we identified a "yellow" (short-wavelength suppressing) filter that effectively transforms between these datasets. This finding aligns with our hypothesis that observed differences between the CMF sets are attributable to age-related lens yellowing (average observer age: 49 years in ICVIO versus 30 years in SB1955). Our approach enables efficient representation of observer variability through a single filter rather than three separate functions, offering potentially reduced experimental overhead while maintaining accuracy in characterizing individual color vision differences.
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