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Incorporating Gradient Direction for Assessing Multiple Distortions

机译:合并渐变方向以评估多个失真

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Quantifying the perceived quality of digital images matters when various artifacts cause unpleasant experiences for users of multimedia applications and TV viewers. With an automatic metric for image quality assessment, content providers can monitor what they share and network resources can be assigned in an optimized way. However, it is difficult to model the way humans perceive the quality of an image. Existence of multiple distortions in an image is another challenge, since it makes it more difficult to evaluate the severity of the artifacts in comparison to a situation where there is only one distortion in an image. In this paper, we have adopted the information provided by the direction of gradient vectors, in addition to the gradient magnitudes, so that we can have better performance in dealing with multiple distortions. Doing so, we were able to deliver a full-reference method with an acceptable performance and time complexity for multiply distorted images.
机译:当各种伪像对多媒体应用程序的用户和电视观众造成不愉快的体验时,量化数字图像的感知质量很重要。借助用于图像质量评估的自动指标,内容提供商可以监视他们共享的内容,并且可以以优化的方式分配网络资源。但是,很难模拟人类对图像质量的感知方式。图像中存在多个失真是另一个挑战,因为与图像中只有一个失真的情况相比,它使评估伪影的严重性更加困难。在本文中,我们除了采用了梯度幅度之外,还采用了由梯度矢量的方向提供的信息,以便在处理多重失真时具有更好的性能。这样做,我们能够为多重失真的图像提供具有可接受性能和时间复杂度的全参考方法。

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