中文摘要：

为了获得研究对象内部结构更多的信息，需要采用超声射频信号，因此超声信号包络成像的应用十分广泛。但超声图像的采样过程耗时长，数据存储量大，在实际应用中会出现诸多问题。根据压缩传感理论，对原始信号或原始图像采集较少的采样信息，也可较逼真地恢复原始信号或者原始图像。为解决稀疏信号求解过程中所涉及的凸问题，提出了基于压缩感知理论及OMP的超声图像重建算法。该算法基于超声图像的稀疏特性，研究超声测量值、迭代次数及量化步长对超声图像重建质量的影响。理论分析与实验结果表明，所提出的超声图像重建算法是有效的。在不同的测量矩阵下，随着测量值的逐渐增加，重建图像的质量改善明显；当迭代次数增加，且量化步长合适，则重建图像的峰值信噪比（PSNR）越高，重建图像的质量也越好。

英文摘要：

To acquire much information of internal structure of research object, the ultrasonic RF signal is used, so the ultrasonic signal en- velope imaging technology has wide application. However, there are some inconvenience in the application because of its large data stor- age and high time consuming in sampling. According to the compressed sampling theorem, the original signal or image could be more realistic to reconstruct by acquisition of fewer sampling data. In order to solve the convex problems involved in the process of sparse signal solving, an algorithm of ultrasonic image reconstruction based on CS theory and OMP algorithm has been proposed, which considers the effects of the measured value,the number of iterations and the quantization step size on the quality of ultrasound image reconstruction based on compressing sensing theorem. Theoretical analysis and experimental results show that the proposed algorithm for ultrasound image reconstruction is effective. Under the conditions of various measurement matrices, the quality of the reconstructed image is better with the gradual increase of the measured value, and when the number of iterations is increased and the quantization step is appropriate, the PSNR of the reconstructed image is higher,the quality of it is greater.