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An enlargement method of digital images based on Laplacian pyramid representation without edge-effect

机译:基于无边缘效应的拉普拉斯金字塔表示的数字图像放大方法

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摘要

It is necessary to predict unknown higher-frequency components which are lost by sampling for enlarging digital images. Based on Laplacian pyramid representation, the prediction of unknown higher-frequency components is equivalent to the prediction of an unknown high-resolution Laplacian image. Greenspan et. al., proposed the image enlarging method based on this Laplacian pyramid representation. This method has two free parameters and Takahashi et. al., found suitable these two parameters by seven natural digital images. However, the artifacts are appeared near the step-edge regions of the enlarging result with two parameters. In this paper, we derive suitable two parameters for the step edge signal. We show the step edge type signal is detected by using the two layers of Laplacian images. Thus, we can detect the step edge signal regions into the processed image and we apply the two parameters for the step-edge signal at these regions. Excellent enlarging images without artifacts near the edges are obtained by the novel method.
机译:有必要预测未知的高频成分,这些成分会因采样而丢失,以放大数字图像。基于拉普拉斯金字塔表示,未知的高频分量的预测等效于未知的高分辨率拉普拉斯图像的预测。格林斯潘等等人提出了基于这种拉普拉斯金字塔表示的图像放大方法。该方法有两个自由参数,高桥等。等人,通过七个自然数字图像找到适合这两个参数。但是,伪影出现在具有两个参数的放大结果的阶跃边缘区域附近。在本文中,我们为阶跃边缘信号推导了合适的两个参数。我们展示了通过使用两层拉普拉斯图像检测到台阶边缘类型的信号。因此,我们可以将阶梯边缘信号区域检测到处理后的图像中,并在这些区域为阶梯边缘信号应用两个参数。通过新颖的方法可以获得在边缘附近没有伪影的出色放大图像。

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