在压缩感知理论的基础上，分析了单点探测计算成像系统的整体结构、相关观测矩阵的设计和图像重构算法，并针对相关算法进行了Matlab仿真。仿真实验结果表明，压缩感知用于单点探测计算成像可以在减少采样的同时还能清晰复原图像。在实验室内搭建了远距离对外成像系统样机，并在室内利用平行光源进行了成像实验。实验结果表明，该成像系统具有较好的空间分辨率。还对单点探测计算成像进行了更进一步的扩展，通过在成像系统后面搭建色散光路，建立起了计算成像光谱仪的系统结构，分析了压缩感知用于计算成像光谱仪的可行性，并对计算成像光谱仪进行了理论分析。

Based on the theory of compressive sensing, the overall structure system of the single-pixel detection computational imaging, the design of the observation matrix and image reconstruction algorithm are analysed, and correlation algorithm is simulated by Matlab. Simulation results show that compressive sensing used to single-pixel detection computational imaging can reduce the sampling and can clearly reconstruct image. In addition, a long-range external imaging system prototype is built in the laboratory, and the imaging experiment is conducted in the indoors using parallel light source. The experimental results show that the imaging system has better spatial resolution. The single-pixel detection computational imaging is extended further by building dispersion optical path in the imaging system, the system structure of computational imaging spectrometer is established, the feasibility of which compressive sensing is used to the computational imaging spectrometer is analyzed, and the computational imaging spectrometer is analyzed in theory.