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Simultaneous deblur and super-resolution technique for video sequence captured by hand-held video camera

机译:手持摄像机同时捕获视频序列的模糊和超分辨率技术

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Nowadays, video camera is commonly used everywhere and demand of retrieving a single shot from video sequence is increasing. Since resolution of video camera is usually lower than that of digital camera, simply cutting out a frame from a video sequence ends up with low quality. Further, because of the necessity of high fps on video camera, video data inevitably contains motion blur and it leads mis-registration between frames which is critical for multi-frame superresolution. In this paper, we propose a method to restore high-resolution image from a video sequence considering motion blur. Since the frame-rate of a video camera is high, motion of the object in successive frames is small, and thus, stable feature tracking during short sequences is possible even if there is a blur. Thus, we adopt a division/integration approach to realize robust tracking for long sequence. We also propose a simultaneous deblur and super-resolution technique using multiple images based on MAP estimation. Experimental results are shown to prove the strength of our method.
机译:如今,摄像机无处不在,从视频序列中检索单张照片的需求正在增加。由于摄像机的分辨率通常低于数字摄像机的分辨率,因此简单地从视频序列中切出一帧会导致质量降低。此外,由于在摄像机上需要高fps,因此视频数据不可避免地包含运动模糊,并且会导致帧之间的配准错误,这对于多帧超分辨率至关重要。在本文中,我们提出了一种考虑运动模糊从视频序列中恢复高分辨率图像的方法。由于摄像机的帧频高,因此对象在连续帧中的运动很小,因此即使出现模糊,也可以在短序列中进行稳定的特征跟踪。因此,我们采用除法/积分法来实现长序列的鲁棒跟踪。我们还提出了基于MAP估计的使用多个图像的同时去模糊和超分辨率技术。实验结果证明了我们方法的有效性。

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