Sparse Sampling Based Image Compression And Collection Scheme For Wireless Multimedia Sensor Networks

Wireless Multimedia Sensor Networks(WMSNs)introduce multimedia information such as image,audio and video,on the basis of traditional Wireless Sensor Networks.They enable higher precision monitoring,so that users can understand the objects more intuitively and deeply.WMSNs have broad application prospects,but they also face many restrictions and challenges,such as network energy consumption,node performance and storage memory size.It is the key to the further development and application of WMSNs to solve these problems effectively.In this thesis,based on the characteristics of WMSNs,a distributed image compression and collection scheme based on sparse sampling in Fourier domain is proposed by introducing a multi-node collaborative network framework and compressed sensing technology.This scheme divides the nodes in the network into different roles according to their functions.It realizes adaptive compression sampling and transmission of an image in blocks in Fourier domain by multi-node cooperation,and finally realizes the reconstruction of the image in the base station.Simulation results show that,under the premise of ensuring the image reconstruction quality,the proposed scheme can greatly reduce the energy consumption of the image acquisition node,effectively balance the energy consumption among the nodes in the network,and prolong the life cycle of the whole network.On this basis,a distributed image compression and collection simulation system is designed and implemented by Matlab-GUI programming.This system can build a multimedia sensor network according to the number of clusters and nodes set by the user,and simulate the process of sampling,compression and reconstruction of images completely.Through the simulation system,the effectiveness of the proposed scheme is further verified.