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A simple motion deblurring method by two continuous images

机译:两个连续图像的简单运动脱模方法

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摘要

Restoring blurred images to clear images is a challenging problem. Most previous methods only analyzed the single image. However, for motion blurring, this method missed the key trajectory description process. Based on the essence of motion blur, our research combined the continuous frame image information in video to estimate the motion track, the SIFT algorithm was proposed for the first time to match the feature points of the target in the continuous frame image. The accurate motion blur angle and motion blur distance were obtained by combining the matching information to obtain an accurate PSF. Finally, the Wiener filtering algorithm combined with PSF was used for deblurring. Experiments showed that the proposed method can improve the image sharpness after restoration compared with the previous algorithms.
机译:恢复模糊图像以清除图像是一个具有挑战性的问题。 最先前的方法仅分析单个图像。 然而,对于运动模糊,该方法错过了关键轨迹描述过程。 基于运动模糊的本质,我们的研究将连续帧图像信息组合在视频中估计运动轨道,首次提出了SIFT算法,以匹配连续帧图像中的目标的特征点。 通过组合匹配信息获得精确的PSF来获得精确的运动模糊角度和运动模糊距离。 最后,使用与PSF相结合的维纳滤波算法用于去束缚。 实验表明,与先前算法相比,该方法可以在恢复后改善图像清晰度。

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