Blind Deconvolution Method Using Omnidirectional Gabor Filter-Based Edge Information

T. Do, X. Cui, Thi Hai Binh Nguyen, Hakil Kim, Van Huan Nguyen
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引用次数: 1

Abstract

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.
基于全向Gabor滤波器边缘信息的盲反卷积方法
在以往的盲反卷积方法中,可以利用图像的边缘或像素信息得到去模糊图像。然而,现有的基于边缘的方法在恢复去模糊图像时,没有充分利用全方向的边缘信息,而是只利用水平和垂直边缘。这个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来恢复真实清晰图像的方法。我们还提供了一个统计表分数,以显示多少个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,我们引入了一种利用Haar小波变换的测量方法,即Haar离焦分数。实验结果表明,无论哈尔离焦分数还是峰值信噪比,该方法都能获得高质量的去模糊图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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