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Video Inpainting for Vintage Film with Continuous Large Damaged Regions

机译:连续损坏区域较大的老式电影的视频修补

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The vintage films may contain large regions of damaged content which is hard to be restored. To solve this problem, we proposed an video inpainting algorithm depended on the optimization of a global, patch-based functional. Our method is divided into three steps. Firstly, we use color transfer to normalize the average intensity of each frame. Then, we take a non-local patch-based approach to search the nearest neighbor of the damaged region using their information to reconstruct the occlusion. Finally, to those unsatisfactory results due to the lack of information we use the deep neural network interpolation algorithm to achieve a coherent effect. The proposed method has been tested on different types of vintage film sequences and proved to be effective.
机译:老式胶片可能包含损坏内容的大区域,难以修复。为了解决这个问题,我们提出了一种视频修补算法,该算法依赖于基于补丁的全局功能的优化。我们的方法分为三个步骤。首先,我们使用颜色转移对每帧的平均强度进行归一化。然后,我们采用基于非局部补丁的方法,使用其信息搜索受损区域的最近邻居,以重建遮挡。最后,对于由于信息不足而导致的令人满意的结果,我们使用深度神经网络插值算法来实现连贯的效果。所提出的方法已经在不同类型的老式电影序列上进行了测试,并被证明是有效的。

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