为提高被动式人体太赫兹成像系统所获取图像的目标分辨力，采用反卷积方法处理图像，提出了一种被动式太赫兹图像重构算法。从系统的基本成像原理出发，分析了导致图像退化的主要原因；在对原始太赫兹图像进行去噪预处理后，采用高斯型点扩展函数进行图像反卷积重构，提高图像的分辨率,用灰度变换方法提高图像的对比度。应用本算法重构原始人体太赫兹图像，获得了清晰度和目标分辨力明显改善的处理效果。实验结果表明，本算法能有效提高被动式人体太赫兹成像系统的图像质量，有利于观察者快速准确地发现被检测者隐藏在衣服内的违禁品，增强了系统的实用性。

In order to improve the object identification capacity of our passive human terahertz imaging system, a passive terahertz image reconstruction algorithm is put forward using deconvolution method. First the main reasons of image degradation are analyzed according to the basic imaging principle of the system. Then the original terahertz images are de-noised as preprocessing course. Afterwards the images are reconstructed by deconvolution method using Gaussian point spread function, so the image resolution is improved. Their grayscales are corrected. The original human terahertz images are processed and resulting images with higher definition and better object identification capability are obtained. Experimental results show that the proposed algorithm is able to effectively improve the image quality of our passive human terahertz imaging system. It can help the observers detect the contrabands hidden in the clothes of imaging subjects more quickly and accurately, which consequently strengthens the practicability of our imaging system.