评估图像中的色差测量

Benhur Ortiz Jaramillo, A. Kumcu, W. Philips
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引用次数: 16

摘要

CIEDE2000色差公式是比较两种均匀颜色样本的最著名和最广泛使用的方法,因为它与人类的感知非常吻合。然而,该公式应用于图像时不可靠,其空间扩展与原公式相比改善不大。因此,研究者们提出了许多测量自然场景彩色图像色差(cd)的方法。然而,这些现有的方法还没有经过严格的比较。因此,在这项工作中,我们回顾和评估CD测量,目的是回答这个问题,最先进的CD测量在多大程度上符合人类对图像CD的感知?为了回答这个问题,我们在公共图像质量数据库中审查和评估了八种最先进的CD测量方法。我们发现CIEDE2000及其空间扩展和仅可注意的CD测量在计算被黑电平移位和颜色量化算法扭曲的图像CD时表现良好(相关系数大于0.8)。然而,在本研究中测试的CD测量方法中,没有一种能很好地识别出各种颜色相关失真的CD,例如,大多数测试的CD测量方法显示出低于0.65的相关性。
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Evaluating color difference measures in images
The most well known and widely used method for comparing two homogeneous color samples is the CIEDE2000 color difference formula because of its strong agreement with human perception. However, the formula is unreliable when applied over images and its spatial extensions have shown little improvement compared with the original formula. Hence, researchers have proposed many methods intending to measure color differences (CDs) in natural scene color images. However, these existing methods have not yet been rigorously compared. Therefore, in this work we review and evaluate CD measures with the purpose of answering the question to what extent do state-of-the-art CD measures agree with human perception of CDs in images? To answer the question, we have reviewed and evaluated eight state-of-the-art CD measures on a public image quality database. We found that the CIEDE2000, its spatial extension and the just noticeable CD measure perform well in computing CDs in images distorted by black level shift and color quantization algorithms (correlation higher than 0.8). However, none of the tested CD measures perform well on identifying CDs for the variety of color related distortions tested in this work, e.g., most of the tested CD measures showed a correlation lower than 0.65.
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