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Image quality assessment model based on multi-feature fusion of energy Internet of Things

机译:基于能源互联网多特征融合的图像质量评估模型

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摘要

Image information may be distorted during acquisition, propagation, compression, and storage. Distortion is common in real life, but it affects the subjective experience after acquiring an image. In order to improve the subjective experience, it is necessary to properly evaluate the image quality. This paper discusses image quality assessment without reference. This paper proposes a new method for image quality assessment. In complex scenarios, we deploy multiple critical sensors. We use sensors to get the necessary factors in the environment. After acquiring the feature values, we fuse the acquired information. We propose a multi-feature fusion method based on the Internet of Things to evaluate images. After the information is merged, we get a fused image and use it as a reference image. We converted the no-reference image assessment into a full reference image assessment, and applied the corresponding image assessment method to obtain the corresponding assessment results. In the process of experimental verification, we compare the prediction results with the subjective assessment of the human eye. It can be seen that our method is close to subjective judgment.
机译:图像信息可以在采集,传播,压缩和存储期间失真。失真在现实生活中是常见的,但它影响了获取图像后的主观体验。为了提高主观体验,有必要适当地评估图像质量。本文讨论了图像质量评估而无需参考。本文提出了一种用于图像质量评估的新方法。在复杂的方案中,我们部署了多个关键传感器。我们使用传感器在环境中获得必要的因素。在获取特征值之后,我们融合了所获取的信息。我们提出了一种基于物联网来评估图像的多特征融合方法。信息合并后,我们得到融合图像并将其用作参考图像。我们将No参考图像评估转换为完整的参考图像评估,并应用了相应的图像评估方法以获得相应的评估结果。在实验验证过程中,我们将预测结果与人眼的主观评估进行比较。可以看出,我们的方法接近主观判断。

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