A Divisive Normalization Brightness Model for Tone Mapping

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dc.contributor.authorDing, Julianen_US
dc.contributor.authorShirley, Peteren_US
dc.contributor.editorWang, Beibeien_US
dc.contributor.editorWilkie, Alexanderen_US
dc.date.accessioned2025-06-20T07:48:55Z
dc.date.available2025-06-20T07:48:55Z
dc.date.issued2025
dc.description.abstractTone 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.en_US
dc.description.sectionheadersLight and Brightness
dc.description.seriesinformationEurographics Symposium on Rendering
dc.identifier.doi10.2312/sr.20251182
dc.identifier.isbn978-3-03868-292-9
dc.identifier.issn1727-3463
dc.identifier.pages12 pages
dc.identifier.urihttps://doi.org/10.2312/sr.20251182
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/sr20251182
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies -> Perception; Image processing; Computer graphics
dc.subjectComputing methodologies
dc.subjectPerception
dc.subjectImage processing
dc.subjectComputer graphics
dc.titleA Divisive Normalization Brightness Model for Tone Mappingen_US
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