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Video frame interpolation via optical flow estimation with image inpainting
International Journal of Intelligent Systems ( IF 7 ) Pub Date : 2020-09-04 , DOI: 10.1002/int.22285
Xiaozhang Liu 1 , Hui Liu 2, 3 , Yuxiu Lin 2, 3
Affiliation  

As we all know, video frame rate determines the quality of the video. The higher the frame rate, the smoother the movements in the picture, the clearer the information expressed, and the better the viewing experience for people. Video interpolation aims to increase the video frame rate by generating a new frame image using the relevant information between two consecutive frames, which is essential in the field of computer vision. The traditional motion compensation interpolation method will cause holes and overlaps in the reconstructed frame, and is easily affected by the quality of optical flow. Therefore, this paper proposes a video frame interpolation method via optical flow estimation with image inpainting. First, the optical flow between the input frames is estimated via combined local and global‐total variation (CLG‐TV) optical flow estimation model. Then, the intermediate frames are synthesized under the guidance of the optical flow. Finally, the nonlocal self‐similarity between the video frames is used to solve the optimization problem, to fix the pixel loss area in the interpolated frame. Quantitative and qualitative experimental results show that this method can effectively improve the quality of optical flow estimation, generate realistic and smooth video frames, and effectively increase the video frame rate.

中文翻译:

通过带有图像修复的光流估计进行视频帧插值

众所周知,视频帧率决定了视频的质量。帧率越高,画面运动越流畅,表达的信息越清晰,给人的观看体验也越好。视频插值旨在通过使用两个连续帧之间的相关信息生成新的帧图像来提高视频帧率,这在计算机视觉领域是必不可少的。传统的运动补偿插值方法会在重构帧中造成空洞和重叠,并且容易受到光流质量的影响。因此,本文提出了一种基于光流估计和图像修复的视频帧插值方法。第一的,输入帧之间的光流是通过组合局部和全局总变化(CLG-TV)光流估计模型来估计的。然后在光流的引导下合成中间帧。最后,利用视频帧之间的非局部自相似性来解决优化问题,修复插值帧中的像素丢失区域。定量和定性实验结果表明,该方法能够有效提高光流估计质量,生成逼真流畅的视频帧,有效提高视频帧率。修复插值帧中的像素丢失区域。定量和定性实验结果表明,该方法能够有效提高光流估计质量,生成逼真流畅的视频帧,有效提高视频帧率。修复插值帧中的像素丢失区域。定量和定性实验结果表明,该方法能够有效提高光流估计质量,生成逼真流畅的视频帧,有效提高视频帧率。
更新日期:2020-09-04
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