基于分布式压缩感知的煤矿井下图像采集方法研究

Research on an Underground Coal Mine Image Collection Method Based on Distributed Compressed Sensing

煤矿井下无线传感器网络存在着能量受限的问题,需要研究高效的数据压缩采集方法解决此问题。分布式压缩感知是一种高效的数据压缩采集方法。提出基于分布式压缩感知的煤矿井下图像压缩采集方法,将图像按列划分为多个图像块,对每个图像块单独压缩编码,在服务器上利用信号内相关性和信号间相关性联合解码。实验结果表明,在相同压缩率下,新方法与传统的压缩感知相比能够获得更好的图像质量,恢复图像所需的时间更少,实时性更强。

Underground coal mine wireless sensor network is facing the problem of limited energy.It is urgent to study efficient data compression and collection methods to solve this problem.Distributed compressed sensing is an efficient data compression and collection method.An underground coal mine image compression and collection method based on distributed compressed sensing is proposed.The image is divided into multiple image blocks by column,and each image block is compressed and encoded separately.Then they are jointly recovered in the server by utilizing intra-signal correlation and inter-signal correlation.The experimental results show that,under the same compression rate,the method in this paper can obtain better image quality than compressed sensing,and it takes less time to restore the image and has stronger real-time performance.