Matsushita Yasuyuki, Ofek Eyal, Ge Weina, Tang Xiaoou, Shum Heung-Yeung
Microsoft Research Asia, 3/F, Beijing Sigma Center, No. 49, Zhichun Road, Hai Dian District, Beijing, China 100080.
IEEE Trans Pattern Anal Mach Intell. 2006 Jul;28(7):1150-63. doi: 10.1109/TPAMI.2006.141.
Video stabilization is an important video enhancement technology which aims at removing annoying shaky motion from videos. We propose a practical and robust approach of video stabilization that produces full-frame stabilized videos with good visual quality. While most previous methods end up with producing smaller size stabilized videos, our completion method can produce full-frame videos by naturally filling in missing image parts by locally aligning image data of neighboring frames. To achieve this, motion inpainting is proposed to enforce spatial and temporal consistency of the completion in both static and dynamic image areas. In addition, image quality in the stabilized video is enhanced with a new practical deblurring algorithm. Instead of estimating point spread functions, our method transfers and interpolates sharper image pixels of neighboring frames to increase the sharpness of the frame. The proposed video completion and deblurring methods enabled us to develop a complete video stabilizer which can naturally keep the original image quality in the stabilized videos. The effectiveness of our method is confirmed by extensive experiments over a wide variety of videos.
视频稳定化是一项重要的视频增强技术，旨在消除视频中恼人的抖动。我们提出了一种实用且强大的视频稳定化方法，该方法能够生成具有良好视觉质量的全帧稳定视频。虽然大多数先前的方法最终生成的稳定视频尺寸较小，但我们的完成方法可以通过局部对齐相邻帧的图像数据自然地填充缺失的图像部分来生成全帧视频。为了实现这一点，我们提出了运动图像修复技术，以在静态和动态图像区域中强制完成的图像在空间和时间上保持一致。此外，使用一种新的实用去模糊算法来提高稳定视频中的图像质量。我们的方法不是估计点扩散函数，而是转移和插值相邻帧的更清晰图像像素以提高帧的清晰度。所提出的视频完成和去模糊方法使我们能够开发出一种完整的视频稳定器，该稳定器能够在稳定视频中自然地保持原始图像质量。通过对各种视频进行广泛实验，证实了我们方法的有效性。
