中文摘要：

基于高斯测量矩阵的一维压缩感知测量数据不仅能很好地保持稀疏信号的能量信息.也能够很好地继承稀疏信号的方向信息.但是在一维压缩感知模型中方向信息无法应用于稀疏信号的重构和检验.针对遥感影像中变化区域稀疏的特点提出了二维压缩感知模型.并利用能量和方向信息构建了基于二维压缩感知的稀疏信号重构算法（2DOMP）.理论分析和实验结果证明.2DOMP算法的信号重构能力更强.同时根据压缩感知恢复稀疏信号只需要很少测量数据的特性提出了定向遥感和定向变化检测的概念.

英文摘要：

One-dimensional compressive sensing measurement data based on Gaussian measurement matrix not only well retain sparse signal＇s energy, but also inherited sparse signal＇s direction information. However in the one-dimensional compression sensing model, direction information can not be applied to sparse signal reconstruction and examination. Two-dimensional compressive sensing model was proposed based on sparse features of change area in the remote sensing image. By use of energy and direction information, sparse signal reconstruction algorithm （2DOMP） was constructed based on two-dimensional compressed sensing. Theoretical analysis and experimental results demonstrated that signal re- construction ability of 2DOMP algorithm is stronger than other methods. Meanwhile, the concepts of directional remote sensing and directional change are put forward based on the fact that very little measurement data are required to recovery sparse signal by compressive sensing.