A Model of Local Adaptation

Peter Vangorp, Karol Myszkowski, Erich Graf, Rafal K Mantiuk

Research output: Contribution to journalArticle (journal)peer-review

26 Citations (Scopus)
340 Downloads (Pure)


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 languageEnglish
Article number166
JournalACM Transactions on Graphics
Issue number6
Early online date18 Oct 2015
Publication statusPublished - 1 Nov 2015
EventACM 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 20155 Nov 2015


  • perception
  • local adaptation
  • tone mapping
  • visual metric
  • high dynamic range
  • glare
  • Tone mapping
  • Glare
  • Local adaptation
  • Visual metric
  • Perception
  • High dynamic range


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