A model of local adaptation
ACM Transactions on Graphics
ACM SIGGRAPH Asia 2015
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Vangorp, P., Myszkowski, K., Graf, E., & Mantiuk, R. (2015). A model of local adaptation. ACM Transactions on Graphics, 34 (6. 166), 1-13. https://doi.org/10.1145/2816795.2818086
The visual system constantly adapts to different luminance levels when viewing natural scenes. The state of visual adaptation is the key parameter in many visual models. While the time-course of such adaptation is well understood, there is little known about the spatial pooling that drives the adaptation signal. In this work we propose a new empirical model of local adaptation, that predicts how the adaptation signal is integrated in the retina. The model is based on psychophysical measurements on a high dynamic range (HDR) display. We employ a novel approach to model discovery, in which the experimental stimuli are optimized to find the most predictive model. The model can be used to predict the steady state of adaptation, but also conservative estimates of the visibility (detection) thresholds in complex images. We demonstrate the utility of the model in several applications, such as perceptual error bounds for physically based rendering, determining the backlight resolution for HDR displays, measuring the maximum visible dynamic range in natural scenes, simulation of afterimages, and gaze-dependent tone mapping.
This work was partly supported by High Performance Computing Wales, Wales’ national supercomputing service (hpcwales.co.uk), and by the Fraunhofer and the Max Planck cooperation program within the framework of the German pact for research and innovation (PFI).
External DOI: https://doi.org/10.1145/2816795.2818086
This record's URL: https://www.repository.cam.ac.uk/handle/1810/262670