Perceptual Lightness Modeling for High-Dynamic-Range Imaging

Abstract : The human visual system (HVS) non-linearly processes light from the real world, allowing us to perceive detail over a wide range of illumination. Although models that describe this non-linearity are constructed based on psycho-visual experiments, they generally apply to a limited range of illumination and therefore may not fully explain the behavior of the HVS under more extreme illumination conditions. We propose a novel experimental protocol for measuring visual response to stimuli which does not require participant training, nor does it require the participants to be experts. Furthermore, the protocol can be applied to stimuli covering an extended luminance range. We argue that this protocol may be equally useful for measuring visual response in di fferent perceptual dimensions, such as hue and chroma. Based on the outcome of our experiment, we propose a new model describing lightness response over an extended luminance range. The model can be integrated with existing color appearance models or perceptual color spaces. To demonstrate the e ectiveness of our model in high dynamic range (HDR) applications, we evaluate its suitability for dynamic range expansion relative to existing solutions.
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Article dans une revue
ACM Transactions on Applied Perception, Association for Computing Machinery, 2017, 15 (1), pp.1 - 19. 〈10.1145/3086577〉
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Contributeur : Mohamed-Chaker Larabi <>
Soumis le : vendredi 7 avril 2017 - 15:31:01
Dernière modification le : mercredi 2 août 2017 - 20:48:29

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Mekides Assefa Abebe, Tania Pouli, Mohamed-Chaker Larabi, Erik Reinhard. Perceptual Lightness Modeling for High-Dynamic-Range Imaging. ACM Transactions on Applied Perception, Association for Computing Machinery, 2017, 15 (1), pp.1 - 19. 〈10.1145/3086577〉. 〈hal-01503791〉

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