Retargeting approaches aim at providing a unified framework for image rendering in which both the intended scene luminance and the actual luminance of the display are taken into account. At the core of any color retargeting method, a color vision model and its inverse are employed. Such a color appearance model should be invertible and cover the entire luminance range of the human visual system. There are not many available models that meet these two conditions. Moreover, most of these models are developed based on psychophysical experiments over color patches, and many have never been used for complex images due to their complexity. In this article, a color retargeting approach based on the mesopic model of Shin et al. ["A color appearance model applicable in mesopic vision," Opt. Rev. 11, 272–278 (2004)] is developed to work with complex images. The authors propose an inverse model for complex images to compensate for color appearance changes on dimmed displays viewed in a dark environment. Their experimental results using both quantitative and qualitative evaluations show a discriminative improvement in the perceived color quality for mesopic vision. The proposed method can be incorporated into image retargeting techniques and display rendering mechanisms. © 2016 Society for Imaging Science and Technology.
Mehdi Rezagholizadeh, Tara Akhavan, Afsoon Soudi, Hannes Kaufmann, James J. Clark, "A Retargeting Approach for Mesopic Vision: Simulation and Compensation" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Color Imaging XXI: Displaying, Processing, Hardcopy, and Applications, 2016, https://doi.org/10.2352/ISSN.2470-1173.2016.20.COLOR-323