Computer Graphics
TU Braunschweig

Simulating Visual Contrast Reduction during Night-time Glare Situations on Conventional Displays


Simulating Visual Contrast Reduction during Night-time Glare Situations on Conventional Displays

Bright glare in night-time situations strongly decreases human contrast perception.

Night-time simulations therefore require a way to realistically depict contrast perception of the user.

Due to the limited luminance of popular as well as specialized high dynamic range displays, physical adaptation of the human eye cannot yet be replicated physically correct in a simulation environment.

To overcome this limitation, we propose a method to emulate the adaptation in night-time glare situations using a perception-based model.

We implemented a post-processing tone mapping algorithm that simulates the corresponding contrast reduction effect for a night driving simulation with glares from oncoming vehicles headlights.

During glare tone mapping reduces image contrast in accordance with the incident veiling luminance.

As the glare expires the contrast starts to normalize smoothly over time.

The conversion of glare parameters and elapsed time into image contrast during the re-adaptation phase is based on extensive user studies carried out first in a controlled laboratory setup.

Additional user studies have then been conducted in field tests to ensure validity of the derived time-dependent tone mapping function and to verify transferability onto real-world traffic scenarios.


Author(s):Benjamin Meyer, Steve Grogorick, Mark Vollrath, Marcus Magnor
Year:2016
Month:July
Type:Article
Journal:ACM Transactions on Applied Perception Vol. 14
Project(s): Visual Fidelity Optimization of Displays  Simulating Visual Perception  ICG Dome 


@article{meyer2016tap,
  title = {Simulating Visual Contrast Reduction during Night-time Glare Situations on Conventional Displays},
  author = {Meyer, Benjamin and Grogorick, Steve and Vollrath, Mark and Magnor, Marcus},
  journal = {{ACM} Transactions on Applied Perception},
  volume = {14},
  number = {1},
  pages = {4:1--4:20},
  month = {Jul},
  year = {2016}
}

Authors