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Removing blocking effects using an artificial neural network

机译:使用人工神经网络消除阻塞效应

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In this paper, we shall propose a new method that modifies the AC coefficients of the image blocks suffering from blocking effects so as to improve the image quality. The AC coefficients are modified in accordance with the information provided by the neighboring blocks. Our new method employs an artificial neural network to help make clear the relationships between the AC coefficients of the current block and those of its neighboring blocks, so that we can accordingly determine whether or not to modify the current AC coefficients and what value the AC coefficients should be changed to. Then, after reversing the modified values from the DCT frequency domain to the pixel domain, we can successfully eliminate blocking effects. As our experimental results will show, our new method is capable of giving high quality images.
机译:在本文中,我们将提出一种新方法,该方法可以修改受块效应影响的图像块的AC系数,从而提高图像质量。根据相邻块提供的信息来修改AC系数。我们的新方法采用人工神经网络来帮助弄清当前块及其相邻块的AC系数之间的关系,以便我们可以据此确定是否要修改当前AC系数以及AC系数的值应该更改为。然后,将修改后的值从DCT频域反转到像素域后,我们可以成功消除阻塞效应。正如我们的实验结果所示,我们的新方法能够提供高质量的图像。

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