Abstract
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.
Original language | English |
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Article number | 166 |
Journal | ACM Transactions on Graphics |
Volume | 34 |
Issue number | 6 |
Early online date | 18 Oct 2015 |
DOIs | |
Publication status | Published - 1 Nov 2015 |
Event | ACM SIGGRAPH Asia 2015: 8th ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia - Kobe Convention Center, Kobe, Japan Duration: 2 Nov 2015 → 5 Nov 2015 https://sa2015.siggraph.org/en/ |
Keywords
- perception
- local adaptation
- tone mapping
- visual metric
- high dynamic range
- glare
- Tone mapping
- Glare
- Local adaptation
- Visual metric
- Perception
- High dynamic range