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COMPARISON OF LUMINANCE BASED METRICS IN DIFFERENT LIGHTING CONDITIONS

机译:不同照明条件下亮度基于度量的比较

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In this study, we evaluate established and newly developed metrics for predicting glare using data from three different research studies. The evaluation covers two different targets: 1. How well the user's perception of glare magnitude correlates to the prediction of the glare metrics? 2. How well do the glare metrics describe the subjects' disturbance by glare? We applied Spearman correlations, logistic regressions and an accuracy evaluation, based on an ROC-analysis. The results show that five of the twelve investigated metrics are failing at least one of the statistical tests. The other seven metrics CGI, modified DGI, DGP, Ev, average Luminance of the image L_(avg), UGP and UGR are passing all statistical tests. DGP, CGI, DGI_mod and UGP have largest AUC and might be slightly more robust. The accuracy of the predictions of afore mentioned seven metrics for the disturbance by glare lies in the range of 75-83% and does not confirm findings from other studies stating a poor performance of existing glare metrics.
机译:在这项研究中,我们评估了使用来自三种不同研究研究的数据预测眩光的已建立和新开发的度量。评估涵盖了两个不同的目标:1。用户对眩光幅度的看法有何相关性与眩光度量的预测相关? 2.眩光指标如何通过眩光描述受试者的干扰?基于ROC分析,我们应用Spearman相关性,逻辑回归和准确性评估。结果表明,十二个调查的指标中的五个失败了至少一个统计测试。另外七个度量CGI,修改的DGI,DGP,EV,图像L_(AVG)的平均亮度,UGP和UGR通过所有统计测试。 DGP,CGI,DGI_MOD和UGP具有最大的AUC,可能稍微强大。预测上述预测的准确性提到了眩光的紊乱的七个指标位于75-83%的范围内,并且不会确认其他研究的结果,该研究表明存在持久的眩光度量。

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