摘要
针对现有视频压缩感知多假设预测残差重构方法重构精度不高的问题,提出一种基于结构特征先验约束两阶段重构的多假设预测视频压缩感知方法。该方法从相似图像块非局部相似性和梯度稀疏性出发,将第一阶段多假设预测重构后的当前帧直接作为第二阶段重构的初始重构帧,利用低秩正则化和全变差正则化再次进行重构,其中低秩正则化矩阵是通过欧氏距离感知哈希算法获取的图像相似块集合,同时包含帧内和帧间的相似图像块,充分利用帧内帧间的结构相似性,有效提高重构性能,为后续残差重构打下基础。仿真实验表明,所提两阶段重构算法较现有几种优秀重构算法更好地保留了视频帧的细节,并具有更高的重构精度。
To solve the problem that the accuracy of existing multi-hypothesis prediction methods for compressed video sensing is not high,a multi-hypothesis prediction method based on structural feature priori constrained two-phase reconstruction is proposed.Starting from the non-local similarity and the gradient sparsity of the similar image blocks,the current frame reconstructed by the multi-hypothesis prediction is directly used as the initial frame of the second phase reconstruction.The low rank regularization and the total variation regularization are utilized to perform the second phase reconstruction,wherein the low rank regularization matrix includes the similar blocks of intra-frames and inter-frames,fully utilizing the structural similarity between intra-frames,and improving reconstruction performance effectively,laying the foundation for the subsequent reconstruction of residuals.Simulation experiments show that the proposed two-stage reconstruction algorithm preserves the details of video frames better and has a higher reconstruction accuracy than several excellent reconstruction algorithms.
作者
刘歌
芮国胜
田文飚
LIU Ge;RUI Guosheng;TIAN Wenbiao(Signal and Information Processing Provincial Key Laboratory in Shandong, Naval Aviation University, Yantai 264001, China)
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2020年第11期2441-2449,共9页
Systems Engineering and Electronics
基金
国家自然科学基金(41606117,41476089,61671016)资助课题。
关键词
视频压缩感知
多假设预测
结构先验
低秩性
全变差
video compressed sensing
multi-hypothesis prediction
structure prior
low rank
total variation
作者简介
刘歌(1991-),女,博士研究生,主要研究方向为压缩感知、蒸发波导反演。E-mail:yyliuge@sina.com;芮国胜(1968-),男,教授,博士研究生导师,博士,主要研究方向为压缩感知、现代滤波理论。E-mail:ruigs@vip.sina.com;田文飚(1987-),男,副教授,博士,主要研究方向为压缩感知、蒸发波导反演。E-mail:twbi5si@gmail.com。
