通信学报2017，Vol.38Issue(12)：1-9,9.DOI:10.11959/j.issn.1000-436x.2017297
基于多参考帧假设优化的压缩感知重构算法
Reconstruction algorithm based on multi-reference frames hypothesis optimization for compressive sensing
摘要
Abstract
In multi-hypothesis based distributed compressed video sensing systems,the quality of the multi-hypothesis set has important influence on the reconstruction performance of decoder.However,the acquiring of the hypothesis set has not been concerned in existing works.A reconstruction algorithm based on multi-reference frames hypothesis optimiza-tion(MRHO)was proposed.This algorithm expanded the selection of hypothesis vectors by increasing the number of reference frames.The quality of the prediction set was improved by hypotheses optimization selection under the same size with the original hypothesis set.Simulation results show that the proposed MRHO algorithm effectively improves the reconstructed quality of the distributed compressed video sensing scheme.关键词
压缩感知/分布式压缩视频感知/多假设集合优选/多参考帧选择Key words
compressed sensing/distributed compressive video sensing/multi-hypothesis set optimization/multi-reference frames selection分类
信息技术与安全科学引用本文复制引用
阔永红,王薷泉,陈健..基于多参考帧假设优化的压缩感知重构算法[J].通信学报,2017,38(12):1-9,9.基金项目
国家自然科学基金资助项目(No.61771366) （No.61771366）
"111"计划基金资助项目(No.B08038)The National Natural Science Foundation of China (No.61771366),The "111" Project (No.B08038) （No.B08038）
