基于帧循环网络的视频超分辨率技术

Video super-resolution based on frame recurrent network

对比于单张图像超分辨,视频图像超分辨率技术需要对输入的连续时间序列图像进行融合、对齐等处理。基于帧循环的视频超分辨率网络共分为三部分:(1)帧序列对齐网络提取图像特征,并将邻居帧对齐到中心帧;(2)帧融合网络将对齐完成的帧进行融合,使用邻居帧的信息补充中心帧信息;(3)超分辨网络将融合完成的图像放大,得到最终的高清图像。实验表明,与现有算法相比,基于帧循环网络的视频超分辨率技术产生图像更为锐利,质量更高。

Compared with single image super-resolution,video super-resolution needs to align and fuse time series images.This frame-recurrent-based video super-resolution network consists of three parts:(1)The frame sequence alignment network extracts the image features and aligns the neighbor frames to the center frame;(2)The frame fusion network fuses the aligned frames and supplements the center frame information with the neighbor frame information;(3)The super-resolution network enlarges the fused image to obtain the final high-definition image.Experiments show that,compared with existing algorithms,video super-resolution technology based on frame loop network produces sharper images and higher quality.