Visual maladaptation in contrast domain

In this work we simulate the effect of the human eye’s maladaptation to visual perception over time through a supra–threshold contrast perception model that comprises adaptation mechanisms. Specifically, we attempt to visualize maladapted vision on a display device. Given the scene luminance, the model computes a measure of perceived multi–scale contrast by taking into account spatially and temporally varying contrast sensitivity in a maladapted state, which is then processed by the inverse model and mapped to a desired display’s luminance assuming perfect adaptation. Our system simulates the effect of maladaptation locally, and models the shifting of peak spatial frequency sensitivity in maladapted vision in addition to the uniform decrease in contrast sensitivity among all frequencies. Through our GPU implementation we demonstrate the visibility loss of scene details due to maladaptation over time at an interactive speed.