A Retargeting Approach for Mesopic Vision: Simulation and Compensation

Retargeting approaches aim at providing a uni ed framework for image rendering inwhich both the intended scene luminance and the actual luminance of the display are takeninto account. At the core of any color retargeting method, a color vision model and itsinverse are employed. Such a color appearance model should be invertible and cover theentire luminance range of the human visual system. There are not many available modelswhich meet these two conditions. Moreover, most of these models are developed based onpsychophysical experiments over color patches, and many have never been used for compleximages due to their complexity. In this research, a color retargeting approach based on themesopic model of Shin et al. [1] is developed to work with complex images. We propose aninverse model for complex images to compensate for color appearance changes on dimmeddisplays viewed in dark environment. Our experimental results using both quantitative andqualitative evaluations show a discriminative improvement in the perceived color quality formesopic vision. The proposed method can be incorporated into image retargeting techniquesand display rendering mechanisms.