无线传感器网络中基于压缩感知的静止图像压缩方案研究

The Research on Compressive Sensing Based Still Image Compression in Wireless Sensor Network

受功耗、成本和无线传输环境的限制,无线传感器网络中采集图像的节点并不适合采用传统静止图像压缩标准JPEG、JPEG2000。为了适应无线传感器网络的"轻编码、重解码"的特点,提出了一种基于压缩感知(Compressive Sensing,CS)的静止图像压缩方案。该方案在编码端进行分块测量,分块测量次数根据图像的边缘信息自适应地分配;在解码端则利用分块观测数据进行整帧重建。仿真实验表明,与已有的基于CS的图像压缩方案相比,该方案可有效地降低CS测量成本,并可在重建时消除图像的边缘模糊与块效应现象。

The traditional still image compression standard JPEG and JPEG2000 are not appropriate for a camera sensor in the wireless sensor network since it is limited by the power consumption, costs and wire- less transmission environment. In order to meet the ＂light encoding and heavy decoding＂ characteristic of the wireless sensor network, this paper proposes a novel still image compression scheme based on the compressive sensing （CS） . The scheme measures each image block at the eneoder and adaptively assign the number of measurement for each block in terms of their edge information. At the decoder, the scheme uses the measurements of each block to reconstruct the whole image. Simulation results show that the pro- posed scheme can effectively reduce the cost of CS measuring in comparison with the existing CS based image compression schemes, and it can also remove edge blurs and blocking artifacts in the reconstructed image.