This paper proposes two new non-reference image quality metrics that can be adopted by the state-of-the-art image/video denoising algorithms for auto-denoising. The first metric is proposed based on the assumption that the noise should be independent of the original image. A direct measurement of this dependence is, however, impractical due to the relatively low accuracy of existing denoising method. The proposed metric thus tackles the homogeneous regions and highly-structured regions separately. Nevertheless, this metric is only stable when the noise level is relatively low. Most denoising algorithms reduce noise by (weighted) averaging repeated noisy measurements. As a result, another metric is proposed for high-level noise based on the fact that more noisy measurements will be required when the noise level increases. The number of measurements before converging is thus related to the quality of noisy images. Our patch-matching based metric proposes to iteratively find and add noisy image measurements for averaging until there is no visible difference between two successively averaged images. Both metrics are evaluated on LIVE2 (Sheikh et al. in LIVE image quality assessment database release 2: 2013) and TID2013 (Ponomarenko et al. in Color image database tid2013: Peculiarities and preliminary results: 2005) data sets using standard Spearman and Kendall rank-order correlation coefficients (ROCC), showing that they subjectively outperforms current state-of-the-art no-reference metrics. Quantitative evaluation w.r.t. different level of synthetic noisy images also demonstrates consistently higher performance over state-of-the-art non-reference metrics when used for image denoising.

中文翻译：

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图像自动去噪的无参考图像质量评估

本文提出了两种新的非参考图像质量指标，可用于最先进的图像/视频去噪算法进行自动去噪。第一个度量是基于噪声应该独立于原始图像的假设提出的。然而，由于现有去噪方法的准确性相对较低，因此直接测量这种依赖性是不切实际的。因此，所提出的度量分别处理同质区域和高度结构化的区域。然而，该指标仅在噪声水平相对较低时才稳定。大多数去噪算法通过（加权）平均重复的噪声测量来降低噪声。因此，基于当噪声水平增加时将需要更多噪声测量这一事实，针对高水平噪声提出了另一种度量。因此，收敛前的测量次数与噪声图像的质量有关。我们基于补丁匹配的度量建议迭代地查找并添加噪声图像测量值以进行平均，直到两个连续平均的图像之间没有明显差异。使用标准 Spearman 和 Kendall 等级在 LIVE2（Sheikh 等人在 LIVE 图像质量评估数据库第 2 版：2013 年）和 TID2013（Ponomarenko 等人在彩色图像数据库 tid2013：特性和初步结果：2005 年）数据集上评估这两个指标阶相关系数 (ROCC)，表明它们主观上优于当前最先进的无参考指标。定量评价wrt