To deal with a terahertz (THz) super-resolution (SR) algorithm based on a convolutional neural network (CNN) without standard training datasets, a complex "zero-shot" SR (CZSSR) reconstruction algorithm is proposed according to the internal image statistics with a five-layer complex CNN model. Instead of relying on pre-training, the proposed method is of sound self-adaptability. Compared with real ZSSR, the peak SNR of CZSSR rose by about 0.94 dB, MSE decreased by 0.042, and SSIM increased by about 40% for the SR result of the measured data. The results show that the CZSSR method can solve the low-resolution problem of a THz imaging system and the shortage of datasets in THz SR based on CNN. Therefore, this research is of great significance for application in the fields of medical imaging and non-destructive detection.