Video distributed compressive sensing research based on correlation model

ZHAO Huimin; PEI Zhenzhen; CAI Zhengye; DAI Qingyun; WEI Wenguo; WANG Chen

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Video distributed compressive sensing research based on correlation model

更新时间：2023-12-11

- Video distributed compressive sensing research based on correlation model
- Acta Scientiarum Naturalium Universitatis SunYatseni Vol. 56, Issue 1, Pages: 36-40(2017)
- 作者机构：
  
  广东技术师范学院电子与信息学院//广州市数字内容处理及其安全性技术重点实验室,广东,广州,510665
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2017，
  
  Published Online：25 January 2017，
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ZHAO Huimin, PEI Zhenzhen, CAI Zhengye, et al. Video distributed compressive sensing research based on correlation model. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 56(1):36-40(2017)
DOI：

ZHAO Huimin, PEI Zhenzhen, CAI Zhengye, et al. Video distributed compressive sensing research based on correlation model. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 56(1):36-40(2017) DOI：

摘要

视频采集和重构需要进行大量的数据处理，且精度有限。为此，基于基追踪（Basis Pursuit

BP）原理，提出一种新的相关性模型视频分布式压缩感知算法。通过运用稀疏滤波器进行相关性建模，该算法在编译码端为分布式压缩视频感知建立了完整的实现结构，并且在保证高质量重建原始信号的前提下

可以减少测量值的数目。实验结果验证了提出模型下算法的有效性。

Abstract

Video sampling and reconstruction need to process a huge amount of data. In order to solve the problem

a novel video distributed compressive sensing based-BP (VDCS-BP) is proposed in the paper. Based on correlation model established by sparse filter

VDCS-BP can achieve distributed video sensing at encoder-decoder

and reduce numbers of measurement by DCS. Experimental results show that the VDCS-BP is effective.

关键词

分布式压缩感知视频相关性重构

Keywords

distributed compressive sensingvideocorrelationrecovery

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