Currently, rapid progress in display technology and optical simulation software has enabled the visualization of lighting design, which can provide abundant visual information. However, renderings only allow designers to subjectively judge whether the lighting layout and optical parameters are reasonable. So we want to combine the rendered images and photometric data in the process of optical simulations to define an evaluation indicator of spatial brightness, which can quantify the perceived brightness of the simulated scene. An image assessment experiment based on a display was conducted to investigate the relationship between spatial brightness and calculated image metrics of indoor lit environments. Participants evaluated spatial brightness perception of 39 images of indoor lit environments simulated with SPEOS simulation software on the screen. Four metrics (Log-median luminance, RAMMG contrast, correlated color temperature(CCT) and 60°circular area) were used to characterize participants’ spatial brightness scores, and the relevant prediction equation was proposed. The application of the RAMMG contrast to spatial brightness prediction has a good performance. The image-based assessment method developed in this study has a high Pearson’s correlation coefficient (=0.932) with the actual visual assessment, which is reliable and convenient. The proposed model performs better compared with other prediction methods available.

中文翻译：

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基于图像度量的室内光环境亮度预测模型

目前，显示技术和光学模拟软件的快速进步使得照明设计可视化，可以提供丰富的视觉信息。然而效果图只能让设计师主观判断灯光布局和光学参数是否合理。因此我们希望结合光学模拟过程中的渲染图像和光度数据来定义一个空间亮度的评价指标，可以量化模拟场景的感知亮度。进行了基于显示器的图像评估实验，以研究空间亮度与室内照明环境的计算图像指标之间的关系。参与者评估了使用 SPEOS 模拟软件在屏幕上模拟的 39 张室内照明环境图像的空间亮度感知。使用四个指标（对数中值亮度、RAMMG对比度、相关色温（CCT）和60°圆面积）来表征参与者的空间亮度得分，并提出了相关的预测方程。 RAMMG对比度应用于空间亮度预测具有良好的性能。本研究开发的基于图像的评估方法与实际视觉评估具有较高的Pearson相关系数（=0.932），可靠且方便。与其他可用的预测方法相比，所提出的模型表现更好。