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Multi-level contrast filtering in image difference metrics

机译:图像差异指标中的多级对比度过滤

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In this paper, we present a new metric to estimate the perceived difference in contrast between an original image and a reproduction. This metric, named weighted-level framework Δ E E (WLF-DEE), implements a multilevel filtering based on the difference of Gaussians model proposed by Tadmor and Tolhurst (2000) and the new Euclidean color difference formula in log-compressed OSA-UCS space proposed by Oleari et al. (2009). Extensive tests and analysis are presented on four different categories belonging to the well-known Tampere Image Database and on two databases developed at our institution, providing different distortions directly related to color and contrast. Comparisons in performance with other state-of-the-art metrics are also pointed out. Results promote WLF-DEE as a new stable metric for estimating the perceived magnitude of contrast between an original and a reproduction.
机译:在本文中,我们提出了一种新的指标来估算原始图像和复制品之间对比度的感知差异。该度量名为加权级框架ΔEE(WLF-DEE),它基于对数压缩的OSA-UCS空间中Tadmor和Tolhurst(2000)提出的高斯模型的差异以及新的欧几里得色差公式,实现了多级过滤。由Oleari等人提出。 (2009)。在属于著名的坦佩雷图像数据库的四个不同类别上以及在我们机构开发的两个数据库上,进行了广泛的测试和分析,它们提供与颜色和对比度直接相关的不同失真。还指出了性能与其他最新指标的比较。结果促进WLF-DEE作为一种新的稳定指标,用于估计原件和复制品之间的对比度。

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