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An analytical model of the influence of cone sensitivity and numerosity on the Rayleigh match

机译:圆锥灵敏度和数字对瑞利匹配影响的分析模型

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The Rayleigh match is defined by the range of mixtures of red and green lights that appear the same as an intensity-adjustable monochromatic yellow light. The perceptual match indicates that the red-green mixture and the yellow light have evoked the same respective cone absorptions in the L-and M-cone pathways. Going beyond the existing models, the Poisson noise in cone absorptions is proposed to make the matching proportion of red-green mixtures span a finite range because any mixture in that range evokes cone absorptions that do not differ from those by a yellow light by more than the variations in the absorption noise. We derive a mathematical formula linking the match midpoint or match range with the sensitivities and numerosities of the two cones. The noise-free, exact, matching point, close to the midpoint of the matching range, depends only on the L-and M-cone sensitivities to each of the red, green, and yellow lights [these sensitivities, in turn, depend on the preferred wavelengths (lambda(max)) and optical densities of the cone pigments and the properties of prereceptoral light filtering]. Meanwhile, the matching range depends on both these cone sensitivities and the relative numerosity of the L and M cones. The model predicts that, in normal trichromats, all other things being equal, the match range is smallest when the ratio r between L and M cone densities is r = R-1/2 with R as the ratio between the sensitivities of the L and M cones to the yellow light, i.e., when L and M cones are similarly abundant in typical cases, and, as r departs from R-1/2, the match range increases. For example, when one cone type is 10 times more numerous, the match range increases two-to threefold, depending on the sensitivities of the cones. Testing these model predictions requires either a large data set to identify the effect of one factor (e.g., cone numerosity) while averaging out the effects of the other factors (e.g., cone sensitivities) or for all factors to be known. A corollary of this prediction is that, because they are more likely than usual to have L:M cone ratios skewed, the matching ranges of normal female trichromats who are carriers of dichromacy (but not anomalous trichromacy) are likely to have a larger matching range than usual, particularly for the deutan carriers. In addition, the model predicts that, in strong tetrachromats (whose four dimensions of color are preserved post-receptorally), either the Rayleigh matching is impossible or the matching range is typically smaller than usual. (C) 2016 Optical Society of America
机译:瑞利匹配由看起来与强度可调节单色黄光相同的红色和绿色光的混合范围定义。感知匹配表明,红绿色混合物和黄光在L-和M-圆锥路径中引起了相同的视锥吸收。超越现有模型,提出了锥吸收中的泊松噪声,以使红绿色混合物的匹配比例在有限范围内,因为该范围内的任何混合物所引起的锥吸收与黄光的锥吸收之间的差异不超过吸收噪声的变化。我们导出一个数学公式,将匹配中点或匹配范围与两个圆锥的灵敏度和数量联系起来。接近匹配范围中点的无噪声,精确的匹配点仅取决于对红,绿和黄光的L和M圆锥敏感度(这些敏感度又取决于锥状颜料的最佳波长(λ(max))和光学密度以及受体前滤光的特性]。同时,匹配范围取决于这些圆锥体的灵敏度以及L和M圆锥体的相对数量。该模型预测,在所有其他条件相同的情况下,在正常三色度下,当L和M视锥密度之间的比r为r = R-1 / 2时,匹配范围最小,其中R为L和L的灵敏度之间的比。 M锥呈黄光,即在典型情况下L和M锥同样丰富,并且当r偏离R-1 / 2时,匹配范围增大。例如,当一个圆锥体类型的数量多10倍时,匹配范围将增加2到3倍,具体取决于圆锥体的灵敏度。测试这些模型预测需要庞大的数据集以识别一个因素(例如,锥体数量)的影响,同时平均其他因素(例如,锥体灵敏度)的影响,或者需要知道所有因素。该预测的推论是,由于它们比通常更倾向于使L:M锥比发生偏差,因此,作为二色性(而非异常三色性)携带者的正常雌性三色性的匹配范围可能具有较大的匹配范围。比平时要多,尤其是对于deutan航母。另外,该模型预测,在强四色体(其四个颜色的颜色在受体后保留)中,瑞利匹配是不可能的,或者匹配范围通常小于通常的范围。 (C)2016美国眼镜学会

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