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A No Reference Image Quality Metric for Blur and Ringing Effect based on a Neural Weighting Scheme

机译:基于神经加权方案的模糊和振铃效果的无参考图像质量指标

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摘要

No Reference Image Quality Metrics proposed in the literature are generally developed for specific degradations, limiting thus their application. To overcome this limitation, we propose in this study a NR-IQM for ringing and blur distortions based on a neural weighting scheme. For a given image, we first estimate the level of blur and ringing degradations contained in an image using an Artificial Neural Networks (ANN) model. Then, the final index quality is given by combining blur and ringing measures by using the estimated weights through the learning process. The obtained results are promising.
机译:文献中提出的参考图像质量度量通常没有针对特定的退化而开发,因此限制了它们的应用。为了克服这一限制,我们在这项研究中提出了一种基于神经加权方案的NR-IQM,用于振铃和模糊失真。对于给定的图像,我们首先使用人工神经网络(ANN)模型估计图像中包含的模糊和振铃劣化的程度。然后,通过在学习过程中使用估计的权重,通过结合模糊和振铃措施来给出最终的索引质量。获得的结果是有希望的。

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