Ding, JulianShirley, PeterWang, BeibeiWilkie, Alexander2025-06-202025-06-202025978-3-03868-292-91727-3463https://doi.org/10.2312/sr.20251182https://diglib.eg.org/handle/10.2312/sr20251182Tone mapping operators (TMOs) are essential in digital graphics, enabling the conversion of high-dynamic-range (HDR) scenes to the limited dynamic range reproducible by display devices, while simultaneously preserving the perceived qualities of the scene. An important aspect of perceived scene fidelity is brightness: the perceived luminance at every position in the scene. We introduce DINOS, a neurally inspired brightness model combining the multi-scale architecture of several historical models with a divisive normalization structure suggested by experimental results from recent studies on neural responses in the human visual pathway. We then evaluate the brightness perception predicted by DINOS against several well-known brightness illusions, as well as human preferences from an existing study which quantitatively ranks 14 popular TMOs. Finally, we propose BRONTO: a brightness-optimized TMO that directly leverages DINOS to perform locally varying exposure. We demonstrate BRONTO's efficacy on a variety of HDR scenes and compare its performance against several other contemporary TMOs.Attribution 4.0 International LicenseCCS Concepts: Computing methodologies -> Perception; Image processing; Computer graphicsComputing methodologiesPerceptionImage processingComputer graphics10.2312/sr.2025118212 pages