基于surfacelet稀疏重构的视频修复

为提高视频竖线、划痕、文字等破损的修复质量,提出一种基于Surfacelet稀疏重构的视频修复算法。Surfacelet变换的具有多尺度、多方向且高效树状结构的三维稀疏变换特性,能有效捕捉视频中的奇异曲面。算法首先基于Surfacelet变换域构造破损视频信号的稀疏性全局优化的目标函数,然后采用松弛算法求解该目标函数来实现对破损视频的修复。该算法不需要复杂的分割、边缘检测等预处理,能提高视频的纹理和结构信息的修复效果。实验仿真结果表明本文算法的视频修复质量优于现有视频修复算法。

Video Inpainting Based on Sparse Reconstruction of Surfacelet

To improve the inpainting quality of the damaged videos with vertical line, scratch and characters, a video inpainting algorithm is proposed based on the sparse reconstruction of surfacelet in this paper. Since it has the three-dimensional sparse characteristics with multi-scales, multi-directions and efficient tree structure, the singular surface of a video can be captured effectively by the surfacelet transform. In the proposed scheme, the global optimization objective function of the original video is constructed based on surfacelet transform and solved using the relaxation algorithm to achieve the video inpainting. The proposed algorithm makes unnecessary the complex pretreatments such as segmentation, edge detection and so on, and improves the inpainting quality of texture and structure information in the video. Experimental results show that the inpainting quality of the proposed scheme is superior to that of the existing video inpainting algorithms.