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Free Content A Retargeting Approach for Mesopic Vision: Simulation and Compensation

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Abstract

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.
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Document Type: Research Article

Publication date: January 1, 2016

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  • The Journal of Imaging Science and Technology (JIST) is dedicated to the advancement of imaging science knowledge, the practical applications of such knowledge, and how imaging science relates to other fields of study. The pages of this journal are open to reports of new theoretical or experimental results, and to comprehensive reviews. Only original manuscripts that have not been previously published, nor currently submitted for publication elsewhere, should be submitted.

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