A Hue Correction Scheme Based on Constant-Hue Plane for Color Image Enhancement
A Hue Correction Scheme Based on Constant-Hue Plane for Color Image Enhancement
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DOI：
10.1109/apsipaasc47483.2019.9023061
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发表时间：
2019-11
期刊：
影响因子：
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通讯作者：
Yuma Kinoshita;Kouki Seo;H. Kiya
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文献类型：
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作者：
Yuma Kinoshita;Kouki Seo;H. Kiya
本文提出了一种在RGB色彩空间中基于恒色调平面的色彩校正方案，用于彩色图像的增强。人们已经提出了许多保持色调的图像增强方法。虽然这些方法可以保留色调，但这些方法不能应用于基于深度学习的最先进的增强方法。因此，本文推广了一种基于常色相平面的色相保持方法。这种推广导出了新的色相校正方案。在该方案中，任何现有的图像增强方法都可以用于增强图像，包括基于深度学习的图像增强方法。由增强引起的色相失真，然后通过将增强图像的最大饱和颜色替换为相应输入图像的最大饱和颜色来消除。实验结果表明，该方案可以有效地抑制两种颜色增强方法引起的色调失真，其中包括基于深度学习的颜色增强方法。此外，客观质量评价表明，该方案可以保持图像增强方法的性能。
In this paper, we propose a novel hue correction scheme based on constant-hue plane in the RGB color space for color image enhancement. A number of hue-preserving image enhancement methods have already been proposed. Although these methods can preserve hue, these methods cannot be applied to the state-of-the-art enhancement methods such as deep-learning based ones. We therefore generalize a hue-preserving method based on the constant-hue plane in this paper. This generalization derives our novel hue correction scheme. In the proposed scheme, any existing image enhancement method including deep-learning based ones can be used to enhance images. The hue distortion due to the enhancement is then removed by replacing the maximally saturated colors of an enhanced image with those of the corresponding input one. Experimental results show that the proposed scheme is effective to suppress the hue distortion due to two color enhancement methods including a deep-learning based one. Furthermore, objective quality evaluations demonstrate that the proposed scheme can maintain the performance of image enhancement methods.