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首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >A No-Reference Image Quality Comprehensive Assessment Method
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A No-Reference Image Quality Comprehensive Assessment Method

机译:一个无参考图像质量综合评估方法

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摘要

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.
机译:在图像质量综合评估的研究现状的基础上,本文提出了一个禁区图像质量综合评估功能模型。首先,将图像质量分类为对比度,清晰度和信噪比(SNR),并研究并分析了每个评估指数的相互关系;其次,综合评估模型中的权重是在仅改变对比度,清晰度和SNR时进行了研究。最后,在分别研究各种失真的基础上,并考虑到不同类型的图像失真,我们研究了如何在综合图像质量评估中确定每个指标的权重。结果表明,本文提出的无参考图像质量综合评估功能模型可以更好地拟合人类视觉感知,并且它与差异平均意见评分(DMOS)具有良好的相关性。相关系数(CC)达到0.8331,Spearman等级顺序相关系数(SROCC)达到0.8206,平均绝对误差(MAE)仅为0.0920,根均方误差(RMSE)仅为0.1122,异常比率(或)仅为0.0365。本文提出的方法可以应用于光电测量设备电视系统,并对不参考电视图像提供准确可靠的质量评估。

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