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Blind Deconvolution Method Using Omnidirectional Gabor Filter-Based Edge Information

机译:基于全向Gabor滤波器边缘信息的盲反卷积方法

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摘要

In the previous blind deconvolution methods, de- blurred images can be obtained by using the edge or pixel information. However, the existing edge- based methods did not take the advantage of edge information in ommi-directions, but only used horizontal and vertical edges when recovering the de-blurred images. This limitation lowers the quality of the recovered images. This paper proposes a method which utilizes edges in different directions to recover the true sharp image. We also provide a statistical table score to show how many directions are enough to recover a high quality true sharp image. In order to grade the quality of the deblurring image, we introduce a measurement, namely Haar defocus score that takes advantage of the Haar-Wavelet transform. The experimental results prove that the proposed method obtains a high quality deblurred image with respect to both the Haar defocus score and the Peak Signal to Noise Ratio.
机译:在先前的盲解卷积方法中,可以通过使用边缘或像素信息来获得去模糊图像。然而,现有的基于边缘的方法没有利用全方向的边缘信息,而是在恢复去模糊图像时仅使用水平和垂直边缘。此限制降低了恢复图像的质量。本文提出了一种利用不同方向的边缘恢复真实清晰图像的方法。我们还提供统计表格分数,以显示多少方向足以恢复高质量的真实清晰图像。为了对去模糊图像的质量进行分级,我们引入了一种测量方法,即利用Haar-Wavelet变换的Haar散焦分数。实验结果证明,该方法相对于Haar散焦分数和峰值信噪比均获得了高质量的去模糊图像。

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