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文章针对传统太赫兹时域光谱成像技术存在的扫描时间长以及数据存储量大等问题，提出了一种基于压缩感知理论的空间欠采样太赫兹时域光谱成像方法。首先通过扫描电机获得目标非等间隔欠采样信号，然后利用压缩感知方法来重构缺失像素点的太赫兹信息。实验结果显示，当压缩比为0.5时，所重构的太赫兹信号与全采样条件下的信号相关性可达99.95%。通过对压缩重建图像的显示分析，时域图像中的缓变区域和频谱成像中的低频信号恢复效果较好。该方法为快速太赫兹光谱成像提供了一种有效的技术手段。“,”Terahertz time domain spectroscopy has been widely used in both spectral analysis and imaging applications. Existing terahertz time domain spectroscopy imaging systems usually suffered the low scanningspeed and huge data storage. To solve this problem, an efficient terahertz imaging method based on the compressed sensing theory was presented in this paper. By controlling the scanning motor to perform a non-equal interval sampling of the target, a group of under-sampled terahertz signal can be obtained. Based on the under-sampled signal, the compressed sensing algorithm is applied to reconstruct the complete terahertz image. The results show that, when the compression ratio is 0.5, the correlation coefficient between the reconstructed terahertz signal and the fully sampled THz signal can reach 99.95%. By analyzing the reconstructed terahertz image, the image areas with smooth intensity changing or low frequency component in frequency domain can be well recovered. The proposed method provides a practical means for efficient terahertz imaging applications.