Laboratory of Adaptive Lighting Systems and Visual Processing, Department of Electrical Engineering and Information Technology, Technical University of Darmstadt, 64289, Darmstadt, Germany.
ERCO GmbH, 58507, Lüdenscheid, Germany.
Sci Rep. 2023 Sep 4;13(1):14542. doi: 10.1038/s41598-023-41084-7.
In 1924, the CIE published and standardized the photopic luminous efficiency function. Based on the standardized curve, luminous flux in lumens, luminance in cd/m[Formula: see text], and illuminance in lux are determined by an integral of the curve and the incident light spectra in photometers and are considered physical brightness. However, human brightness perception is not only weighted by this simple determination, but is a more complicated combination of all L-cones, M-cones, S-cones, rods and later ipRGCs, which was partly described by the equivalent brightness of Fotios et al. with the correction factor [Formula: see text]. Recently, new research has demonstrated the role of ipRGCs in human light perception. However, it is still unclear how these signal components of the human visual system are involved in the overall human brightness perception. In this work, human brightness perception under photopic conditions was investigated by visual experiments with 28 subjects under 25 different light spectra. In this way, the contributions of the signal components can be investigated. An optimization process was then performed on the resulting database. The results show that not only the [Formula: see text] component, but also the S-cones and ipRGC play a role, although it is smaller. Thus, the visually scaled brightness model based on the database optimization was constructed using not only illuminance but also S-cones and ipRGC with [Formula: see text] of 0.9554 and RMSE of 4.7802. These results are much better than the brightness model after Fotios et al. using only S-cones ([Formula: see text] = 0.8161, RMSE = 9.7123) and the traditional model without S-cones and ipRGC ([Formula: see text] = 0.8121, RMSE = 9.8171).
1924 年,国际照明委员会(CIE)发布并标准化了明视觉光效函数。基于标准化曲线,光度计中积分曲线与入射光光谱可确定光通量(流明)、亮度(坎德拉每平方米)和照度(勒克斯),这些被认为是物理亮度。然而,人类的亮度感知不仅受此简单测定加权,还受所有 L- cones、M- cones、S- cones、rod 和后来的 ipRGCs 的复杂组合加权,这部分由 Fotios 等人用修正因子 [Formula: see text]描述的等效亮度描述。最近,新的研究表明 ipRGCs 在人类光感知中的作用。然而,人类视觉系统的这些信号成分如何参与整体人类亮度感知仍不清楚。在这项工作中,通过 28 名受试者在 25 种不同光谱下的视觉实验研究了明视觉条件下的人类亮度感知,从而可以研究信号成分的贡献。然后对得到的数据库进行优化处理。结果表明,不仅 [Formula: see text] 分量,而且 S- cones 和 ipRGC 也起作用,尽管作用较小。因此,使用数据库优化构建了基于视觉比例的亮度模型,该模型不仅使用照度,还使用 S- cones 和 ipRGC,其 [Formula: see text] 为 0.9554,RMSE 为 4.7802。这些结果明显优于仅使用 S- cones 的 Fotios 等人的亮度模型 [Formula: see text] = 0.8161,RMSE = 9.7123)和不包括 S- cones 和 ipRGC 的传统模型 [Formula: see text] = 0.8121,RMSE = 9.8171)。