Ringing Artifact Reduction in Blind Image Deblurring and Denoising Problems by Regularization Methods

V. B. Surya Prasath, Arindama Singh
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引用次数: 13

Abstract

Image deblurring and denoising are the main steps in early vision problems. A common problem in deblurring is the ringing artifacts created by trying to restore the unknown point spread function (PSF). The random noise present makes this task even harder. Variational blind deconvolution methods add a smoothness term for the PSF as well as for the unknown image. These methods can amplify the outliers correspond to noisy pixels. To remedy these problems we propose the addition of a first order reaction term which penalizes the deviation in gradients. This reduces the ringing artifact in blind image deconvolution. Numerical results show the effectiveness of this additional term in various blind and semi-blind image deblurring and denoising problems.
基于正则化方法的盲图像去模糊降噪问题中的环形伪影降低
图像去模糊和去噪是早期视力问题的主要步骤。在去模糊中一个常见的问题是试图恢复未知的点扩散函数(PSF)时产生的环形伪影。随机噪声的存在使得这项任务更加困难。变分盲反卷积方法为PSF和未知图像增加了平滑项。这些方法可以放大噪声像素对应的离群值。为了纠正这些问题,我们提出增加一阶反应项来惩罚梯度的偏差。这减少了盲图像反褶积中的环形伪影。数值结果表明,该附加项在各种盲和半盲图像去模糊和去噪问题中是有效的。
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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