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Defocused Image Restoration as an Inverse Problem by Network Inversion

机译:Defocused Image Retoration作为网络反演的逆问题

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Recently, the necessity to solve an inverse problem has increased in the various fields. The solution for the inverse problem by the neural network, which is called the network inversion technique, was proposed. On the other hand, the image restoration problem for recovering the degraded image to the original one is so important that a number of methods have been proposed. The image restoration can be defined as a kind of inverse problem of the image degradation process. Therefore, we introduce the network inversion method to solve the image restoration as an inverse problem. In this study, we perform the simulation of the image restoration by the network inversion. To compare the effect quantitatively, we evaluate the restored image by the ratio of the spatial-frequencies.
机译:最近,解决逆问题的必要性在各种领域增加。提出了神经网络的反问题的解决方案,该方法被称为网络反演技术。另一方面,用于将降级图像恢复到原始图像的图像恢复问题非常重要,即已经提出了许多方法。图像恢复可以被定义为图像劣化过程的一种逆问题。因此,我们介绍了网络反演方法,以解决图像恢复作为逆问题。在这项研究中,我们通过网络反演执行图像恢复的模拟。为了定量比较效果,我们通过空间频率的比率评估恢复的图像。

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