图像的相似性对超分辨率重建具有重要作用,但是单幅图像不能提供足够的相似信息。提出一种基于相似性约束的视频超分辨率重建算法,针对需要重建的视频帧,通过光流场的初始运动估计和精细的块匹配,搜索到视频序列中具有相似的信息;然后利用相似信息不断修正迭代反投影中的重建误差。实验结果表明本文算法能够增加图像细节,并且可以消除边缘出现的人造效应,获得清晰的图像边缘。

The similarity of one image plays an important role in super-resolution reconstruction. However, a single image can not provide sufficient similarity information. Therefore, a video super-resolution reconstruction algorithm based on similarity constraints is proposed. Making initial motion estimation with flow field and fine block matching, the similar information, which can be used to modify the reconstruction error in iterative process of iterative back projection, will be extracted from video sequences. The experimental results show that the proposed algorithm has improve a the image details, moreover, it can remove the artifacts and obtain clear and sharp edges in visual perception.