【摘要】 由于无线传感器网络(WSN)资源极其有限,本文提出了一种新型的分布式三维小波图像压缩(3DWIC)算法,用来节省环境监测时通信所消耗的能量。无线传感器网络用于环境监测时,节点所采集的图像常常具有变化少、相关性强等特点,故引入了简单的变化检测算法(LCDA)和位置估计/补偿算法(PE&CA),用较低的代价来检测并压缩图像的活跃区域,消除各节点所采集的图像之间的信息冗余,节省无线传输能耗。仿真结果表明,该算法在保证图像重构质量的前提下节省了大量能量。更多还原

【Abstract】 A novel distributed 3D wavelet image compression(3DWIC)algorithm was developed to reduce the energy consumption in wireless sensor networks(WSN)for environment surveillance,where each of the sensors has limited power.Since surveillance image sequences in WSN are often characterized by low motion and high correlation,the low-complexity change detection algorithm(LCDA)and position estimation and compensation algorithm(PE&CA)were employed to detect and compress interested regions,remove the redundancy of the images collected by each sensor and save energy consumption in wireless transmission.The simulation results show that these approaches achieve significant energy saving without sacrificing the quality of the image reconstruction.更多还原