On the basis of the research status of image quality comprehensive assessment, a no-reference image quality comprehensive assessment function model is proposed in this paper. First, the image quality is classified as contrast, sharpness, and signal-to-noise ratio (SNR), and the interrelation of each assessment index is researched and analyzed; second, the weights in the comprehensive assessment model are studied when only contrast, sharpness, and SNR are changed. Finally, on the basis of studying each kind of distortion separately, and considering the different types of image distortion, we studied how to determine the weights of each index in the comprehensive image quality assessment. The results show that the no-reference image quality comprehensive assessment function model proposed in this paper can better fit human visual perception, and it has a good correlation with Difference Mean Opinion Score (DMOS). Correlation Coefficient (CC) reached 0.8331, Spearman Rank Order Correlation Coefficient (SROCC) reached 0.8206, Mean Absolute Error (MAE) was only 0.0920, Root Mean Square Error (RMSE) was only 0.1122, Outlier Ratio (OR) was only 0.0365. The method proposed in this paper can be applied to photoelectric measurement equipment television system and give an accurate and reliable quality assessment to no reference television images.

中文翻译：

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一种无参考图像质量综合评价方法

本文根据图像质量综合评价的研究现状，提出了一种无参考的图像质量综合评价函数模型。首先，将图像质量分为对比度、锐度和信噪比（SNR），研究分析各评价指标的相互关系；其次，研究了仅改变对比度、锐度和信噪比时综合评估模型中的权重。最后，在分别研究各类畸变的基础上，考虑图像畸变的不同类型，研究了如何确定综合图像质量评价中各指标的权重。结果表明，本文提出的无参考图像质量综合评价函数模型能够更好地拟合人类视觉感知，并且它与差异平均意见得分（DMOS）有很好的相关性。相关系数（CC）达到0.8331，斯皮尔曼秩次相关系数（SROCC）达到0.8206，平均绝对误差（MAE）只有0.0920，均方根误差（RMSE）只有0.1122，离群比（OR）只有0.0365。本文提出的方法可以应用于光电测量设备电视系统，对无参考电视图像进行准确可靠的质量评估。