Saturation adjustment method based on human vision with YCbCr color model characteristics and luminance changes

Jen-Shiun Chiang, Chih-Hsien Hsia, Hao-Wei Peng, Chun-Hung Lien, Hsin-Ting Li
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引用次数: 11

Abstract

This paper proposes a saturation adjustment method based on human vision with YCbCr color model characteristics and luminance changes. In the traditional color adjustment approach, people tried to separately adjust the luminance and saturation. However, this approach makes the color over-saturate very easily and makes the image look unnatural. In this work, we try to use the concept of exposure compensation to simulate the brightness changes and to find the relationship among luminance, saturation, and hue. The simulation indicates that saturation changes with the change of luminance and the simulation also shows there are certain relationships between color variation model and YCbCr color model. Together with all these symptoms, we also include the human vision characteristics to propose a new saturation method to enhance the vision effect of an image. The experimental results show that the proposed approach can make the image have better vivid and contrast. Most important of all, unlike the over-saturation caused by the conventional approach, our approach prevents over-saturation and further makes the adjusted image look natural.
基于人眼视觉的YCbCr色彩模型特征和亮度变化的饱和度调整方法
提出了一种基于人眼视觉的基于YCbCr色彩模型特征和亮度变化的饱和度调整方法。在传统的色彩调整方法中,人们试图分别调整亮度和饱和度。然而,这种方法很容易使颜色过饱和,使图像看起来不自然。在这项工作中,我们尝试使用曝光补偿的概念来模拟亮度的变化,并找到亮度,饱和度和色调之间的关系。仿真结果表明,饱和度随亮度的变化而变化,颜色变化模型与YCbCr颜色模型之间存在一定的关系。结合这些症状,我们还结合人类视觉的特点,提出了一种新的饱和度方法来增强图像的视觉效果。实验结果表明,该方法能使图像具有更好的逼真度和对比度。最重要的是,与传统方法引起的过度饱和不同,我们的方法可以防止过度饱和,并进一步使调整后的图像看起来自然。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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