September 2024
Volume 24, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2024
Can we improve luminance? Online and lab experiments
Author Affiliations
  • Shuchen Guan
    Justus-Liebig Universität, Gießen
  • Robert Ennis
    Justus-Liebig Universität, Gießen
  • Karl Gegenfurtner
    Justus-Liebig Universität, Gießen
Journal of Vision September 2024, Vol.24, 998. doi:https://doi.org/10.1167/jov.24.10.998
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      Shuchen Guan, Robert Ennis, Karl Gegenfurtner; Can we improve luminance? Online and lab experiments. Journal of Vision 2024;24(10):998. https://doi.org/10.1167/jov.24.10.998.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Luminance has served as the standard measure for light intensity for 100 years. Nevertheless, it has long been known that it has substantial flaws in predicting the perceived intensity of lights with different spectral distributions. Here, we wanted to evaluate potential improvements in the weighting of the cone inputs for heterochromatic brightness perception. To reach a large number of observers, we made measurements in the lab and online, using the same observers. We presented 144 patches encompassing 12 hues and 12 intensities in RGB space. Each trial involved 12 patches varying in both hue and intensity, and 43 observers ranked them based on their perceived brightness in 66 trials. Observers completed the experiment online on personal displays and in a well-controlled lab environment on an OLED. They also brought their personal displays to the lab for calibration. In the lab session, testing observers with a calibrated sRGB display revealed that luminance predicted 76.3% of observer rankings correctly. Radiance predicted more accurately (78.5%), and a non-linear weighted maxRGB model performed best (84.2%). The optimal weights fitted to RGB were [0.40, 0.45, 0.15]. Compared to Vlambda, the contributions of L- and S-cones were increased for heterochromatic brightness. The test-retest reliability, measured with a subset of 20 observers, was 83.9% in these lab-based experiments. For the home session, we first investigated stimuli consistency across displays. The patches presented on the lab OLED had a consistency ranging from 90% to 97% across all predictors on observers' displays based on the calibration data. Intra-observer response consistency across online and lab sessions was 80.8%, inter-observer consistency was 77.6%. Again, the maximum-weighted RGB model consistently outperformed luminance. We conclude that luminance systematically underestimates the contributions of L- and S-cones to heterochromatic brightness. Our results also indicate that online color experiments may be feasible for certain paradigms.

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