A Retargeting Approach for Mesopic Vision: Simulation and Compensation
A Retargeting Approach for Mesopic Vision: Simulation and Compensation
复制标题
中间视觉的重定向方法：模拟和补偿
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
James J. Clark
中科院分区：
文献类型：
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作者：
Mehdi Rezagholizadeh;Tara Akhavan;A. Soudi;H. Kaufmann;James J. Clark
重定向方法旨在为图像渲染提供统一的框架，其中考虑了预期场景亮度和显示器的实际亮度。任何颜色重定向方法的核心都是采用颜色视觉模型及其逆模型。这样的颜色外观模型应该是可逆的并且覆盖人类视觉系统的整个亮度范围。满足这两个条件的可用模型并不多。此外，这些模型大多数都是基于色块的心理物理学实验而开发的，并且许多模型由于其复杂性而从未用于复杂图像。在这项研究中，基于 Shin 等人的中间视觉模型的颜色重定向方法。 [1] 是为处理复杂图像而开发的。我们提出了复杂图像的逆模型，以补偿在黑暗环境中观看的暗淡显示器上的颜色外观变化。我们使用定量和定性评估的实验结果表明，中间视觉的感知颜色质量有所改善。所提出的方法可以合并到图像重定向技术和显示渲染机制中。
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 which 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 research, a color retargeting approach based on the mesopic model of Shin et al. [1] is developed to work with complex images. We propose an inverse model for complex images to compensate for color appearance changes on dimmed displays viewed in dark environment. Our 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.
DOI：
10.1145/2504459.2504473
发表时间：
2013-07
期刊：
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影响因子：
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作者：
Gabriel Eilertsen;Jonas Unger;R. Wanat;Rafał K. Mantiuk
通讯作者：
Gabriel Eilertsen;Jonas Unger;R. Wanat;Rafał K. Mantiuk