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Exploiting Color Strength to Improve Color Correction

机译:利用色彩强度改善色彩校正

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Color information is an important feature for many vision algorithms including color correction, image retrieval and tracking. In this paper, we study the limitations of color measurement accuracy and explore how this information can be used to improve the performance of color correction. In particular, we show that a strong correlation exists between the error in hue measurements on one hand and saturation and intensity on the other hand. We introduce the notion of color strength, which is a combination of saturation and intensity information to determine when hue information in a scene is reliable. We verify the predictive capability of this model on two different datasets with ground truth color information. Further, we show how color strength information can be used to significantly improve color correction accuracy for the 11K real-world SFU gray ball dataset.
机译:颜色信息是许多视觉算法的重要功能,包括颜色校正,图像检索和跟踪。在本文中,我们研究了色彩测量精度的局限性,并探讨了如何使用此信息来改善色彩校正的性能。特别是,我们表明一方面色调测量的误差与另一方面饱和度和强度之间存在很强的相关性。我们引入色彩强度的概念,该色彩强度是饱和度和强度信息的组合,用于确定场景中的色相信息何时可靠。我们用地面真实颜色信息验证了该模型对两个不同数据集的预测能力。此外,我们展示了如何使用色彩强度信息来显着提高11K现实世界SFU灰色球数据集的色彩校正精度。

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