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Exploration of Multi-Node Collaborative Image Acquisition and Compression Techniques for Wireless Multimedia Sensor Networks

机译:用于无线多媒体传感器网络的多节点协作图像采集和压缩技术的探讨

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摘要

Aiming at saving energy and maximizing the network life cycle, the multi-node cooperative image acquisition and compression technology in Wireless Multimedia Sensor Networks(WMSNs) is studied deeply. The Minimum Energy Image Collection (MEIC) problem for multiple target domains in a certain period of time in the monitoring area is proposed, the integer linear programming for Minimum Energy Image Collection (MEIC) problem is described and proved to be NP complete; then combined with the features of image acquisition of camera node, the Local Camera Coordinative Energy-saving Strategy (LCCES) is proposed, and the performance of the Local Camera Coordinative Energy-saving Strategy (LCCES) is evaluated through a lot of simulation experiments; finally, the LBT-based Multi-node Cooperative Image Compression Scheme (LBT-MCIC) is proposed. The results show that this strategy can effectively reduce the number of active camera nodes in the process of image acquisition, thus reducing the energy consumption of image acquisition. At the same time, it also plays a role in balancing the energy consumption of camera nodes in the network, effectively solves the problem of high cost of common nodes in the image transmission scheme of two-hop cluster structure and has the characteristics of low computational complexity and high quality of reconstructed image.
机译:旨在节省能源并最大化网络生命周期,深入研究无线多媒体传感器网络(WMSNS)中的多节点协同图像采集和压缩技术。提出了在监测区域中的一定时间段内的多个目标域的最小能量图像收集(MEIC)问题,描述了最小能量图像收集(MEIC)问题的整数线性规划,并证明了NP完成;然后结合相机节点的图像采集的特征,提出了本地摄像机协调节能策略(LCCE),并通过大量的模拟实验评估了本地相机协调节能策略(LCCE)的性能;最后,提出了基于LBT的多节点协同图像压缩方案(LBT-MCIC)。结果表明,该策略可以有效地减少图像采集过程中的有源相机节点的数量,从而降低了图像采集的能量消耗。同时,它还在平衡网络中的相机节点的能量消耗方面发挥作用,有效地解决了两跳集群结构的图像传输方案中的共同节点的高成本问题,并且具有低计算的特征复杂性和高质量的重建图像。

著录项

  • 作者

    Fangzhou He;

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  • 年度 2019
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  • 原文格式 PDF
  • 正文语种 eng
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