基于压缩感知与能量聚合视觉传感器数据传输系统

邓晓军; 李玉龙; 满君丰; 欧阳旻

doi:10.13873/J.1000-9787(2015)06-0092-04

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基于压缩感知与能量聚合视觉传感器数据传输系统

设计与制造 | 更新时间：2025-09-11

- 基于压缩感知与能量聚合视觉传感器数据传输系统
- Vision sensor data transmission system based on compressed sensing and energy aggregation
- 传感器与微系统 2015年34卷第6期页码：92-95
- 作者机构：
  
  湖南工业大学计算机与通信学院
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目（61350011）;湖南省自然科学基金资助项目（2015JJ2046,2014JJ2115）;湖南省教育厅资助科研项目（12C0068）
- DOI：10.13873/J.1000-9787(2015)06-0092-04
  中图分类号： TN919.8;TP212
- 纸质出版：2015
- 稿件说明：
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[1]邓晓军,李玉龙,满君丰,欧阳旻.基于压缩感知与能量聚合视觉传感器数据传输系统[J].传感器与微系统,2015,34(06):92-95.

DENG Xiao-jun, LI Yu-long, MAN Jun-feng, et al. Vision sensor data transmission system based on compressed sensing and energy aggregation[J]. 2015, 34(6): 92-95.
[1]邓晓军,李玉龙,满君丰,欧阳旻.基于压缩感知与能量聚合视觉传感器数据传输系统[J].传感器与微系统,2015,34(06):92-95. DOI： 10.13873/J.1000-9787(2015)06-0092-04.

DENG Xiao-jun, LI Yu-long, MAN Jun-feng, et al. Vision sensor data transmission system based on compressed sensing and energy aggregation[J]. 2015, 34(6): 92-95. DOI： 10.13873/J.1000-9787(2015)06-0092-04.

摘要

为了保证视频数据的快速传输

并进行有效压缩

从而提升视频数据的传输质量

提出一种基于压缩感知与能量聚合的视觉传感器数据传输技术。该技术在提升视频数据传输率和压缩率的基础上

针对视觉传感器的高能耗问题

采用能量融合技术和能量约束方法来减少能量消耗

并采用了视觉传感器失真和功耗模型、视频数据传输模型

以及能量聚合模型进行分析。实验仿真数据结果表明:在提升视频数据的传输速率、压缩率

以及减少网络总体能量消耗上

提出的视觉传感器数据传输技术取得了较好的效果。

Abstract

In order to ensure rapid transmission of video datas

and the effective compression

so as to enhance the quality of video data transmission

a vision sensor data transmission technology based on compressed sensing and energy aggregation is proposed. On the basis of enhancing video data transmission rate as well as compression ratio

aiming at problem of high energy consumption of vision sensor

this technology use energy fusion and energy restrain method to reduce energy consumption

and use vision sensor distortion and power consumption model

video data transmission models

and energy aggregation model for analysis. The simulation results show that the proposed vision sensor data transmission technology achieves good effect on enhancing transmission rate and compression rate of video data and reduce overall network energy consumption.

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references

视觉传感器网络兼顾区域覆盖的目标多重覆盖 [J]. 向辉,彭力,刘刚,唐从飞. 计算机应用研究 . 2012(09)

Dictionary learning based reconstruction for distributed compressed video sensing [J] . Haixiao Liu,Bin Song,Hao Qin,Zhiliang Qiu. Journal of Visual Communication and Image Representation . 2013 (8)

Compressive light field photography using overcomplete dictionaries and optimized projections [J] . Kshitij Marwah,Gordon Wetzstein,Yosuke Bando,Ramesh Raskar. ACM Transactions on Graphics （TOG） . 2013 (4)

Dynamic Resource Allocation for Compressive-Sensing-Based Wireless Visual Sensor Networks with Energy Harvesting [J] . Lei You,Xin Su,Yu Tong Han. Applied Mechanics and Materials . 2013 (303)

Based on Compression Sensing of Video Coding in Robot Servo System [J] . Lei Jiang,Xiao Zhang Zhang,Yu Jie Bai,Chang Liang Tang. Applied Mechanics and Materials . 2013 (241)

Association of Moving Objects Across Visual Sensor Networks [J] . Muhammad J. Mirza,Nadeem Anjum. Journal of Multimedia . 2012 (1)

Distributed target localization using a progressive certainty map in visual sensor networks [J] . Mahmut Karakaya,Hairong Qi. Ad Hoc Networks . 2010 (4)

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