Grid Warping Postprocessing for Linear Motion Blur in Images

A. Nasonov, Yakov Pchelintsev, A. Krylov
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引用次数: 1

Abstract

The paper presents a method for linear motion blur and out-of-focus blur suppression in photographic images. Conventional image deconvolution algorithms usually have a regularization parameter that specifies a trade-off between incomplete blur removal and high probability of artifacts like ringing and noise. The idea of the proposed image deblurring method is to apply grid warping approach to improve image sharpness after conventional image deconvolution algorithms used with strong regularization. Grid warping algorithm moves pixels in edge neighborhood area towards the edges making them sharper without introducing artifacts like ringing and noise. The proposed method is expected to have the same sharpness but decreased risk of artifacts compared to standalone image deconvolution. In order to validate the proposed scheme, we have applied it to artificially blurred images and images with real blur, with different levels of noise and blur radii, directions and lengths.
网格翘曲后处理的线性运动模糊图像
提出了一种抑制摄影图像中线性运动模糊和失焦模糊的方法。传统的图像反卷积算法通常有一个正则化参数,该参数指定了在不完全模糊去除和高概率伪影(如振铃和噪声)之间的权衡。提出的图像去模糊方法的思想是在传统的图像反卷积算法使用强正则化后,采用网格扭曲的方法来提高图像的清晰度。网格扭曲算法将边缘邻域的像素向边缘移动,使其更清晰,而不会引入振铃和噪声等伪影。与独立图像反卷积相比,所提出的方法有望具有相同的清晰度,但降低了伪影的风险。为了验证所提出的方案,我们将其应用于人工模糊图像和真实模糊图像,具有不同程度的噪声和模糊半径,方向和长度。
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