SAR Imagery Compressing and Reconstruction Method Based on Compressed Sensing

In this paper,a new SAR imagery compressing and reconstruction method based on Compressed Sensing(CS) is proposed.The detailed step and flow chart of the method are shown based on CS theory and SAR imagery characters.In the method,the SAR imagery can be carved up to several sub-imageries firstly.What′s more,Discrete Wavelet Transform(DWT) can be utilized to make SAR imagery sparse.And then the random Gauss matrix after approximate Orthogonal-matrix and Right-matrix(QR) decomposition can be employed to complete the low-dimension measurement and the SAR imagery compressing for sparse results.In this paper,a modified Orthogonal Matching Pursuit(OMP) algorithm is proposed.On condition of the same reconstruction precision,the convergency speed is enhanced by using the proposed modified OMP algorithm compared with the original OMP algorithm.Furthermore,some processing such as inverse DWT and so on can be engaged to achieve the final reconstructed SAR imagery.Simulation results prove the effectiveness and feasibility of proposed SAR imagery compressing and reconstruction method.