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Improvement of the image enlargement method based on the Laplacian pyramid representation

机译:基于拉普拉斯金字塔表示的图像放大方法的改进

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Summary form only given. It is necessary to predict unknown higher-frequency components that are lost by sampling for enlarging digital images. Based on the Laplacian pyramid representation, the prediction of unknown higher-frequency components is equivalent to the prediction of a known higher-resolution Laplacian image. We have proposed the higher resolution method based on the Laplacian pyramid representation. However, the Laplacian pyramid representation was considered for image compression. Thus, we think that the bandwidth of the Gaussian filter for image compression is not optimal for digital image enlargement. In this paper, we proposed a new enlargement method for digital images with the variable bandwidth of Gaussian filter.
机译:仅提供摘要表格。为了放大数字图像,有必要预测由于采样而丢失的未知高频分量。基于拉普拉斯金字塔表示,未知的高频分量的预测等效于已知的高分辨率拉普拉斯图像的预测。我们提出了一种基于拉普拉斯金字塔表示的高分辨率方法。但是,考虑使用拉普拉斯金字塔表示法进行图像压缩。因此,我们认为用于图像压缩的高斯滤波器的带宽对于数字图像放大不是最佳的。在本文中,我们提出了一种具有可变高斯滤波器带宽的数字图像放大新方法。

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