基于帧循环网络的视频超分辨率技术  

Video super-resolution based on frame recurrent network

作　　者：刘佳[1] 安鹤男[1] 李蔚 张昌林 涂志伟 Liu Jia;An Henan;Li Wei;Zhang Changlin;Tu Zhiwei(College of Electronics and Information Engineering,Shenzhen University,Shenzhen 518061,China)

机构地区：[1]深圳大学电子与信息工程学院,广东深圳518061

出　　处：《电子技术应用》2020年第9期43-46,共4页Application of Electronic Technique

摘　　要：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.

关 键 词：视频 超分辨 深度学习 

分 类 号：TN919.8[电子电信—通信与信息系统] TP183[电子电信—信息与通信工程]