Complex-valued convolutional neural network (CVCNN) have better performance than real-valued neural networks in the field of terahertz imaging. In this paper, a complex-valued neural network is innovatively applied to the terahertz image classification task in a vector network analyser (VNA) imaging system. The complex-valued CNN (CVCNN) processing framework for terahertz image classification is proposed. Terahertz image datasets are constructed using MINIST handwritten datasets and PSF which was measured from our transmission system. Compared to CNN, CVCNN has a better accuracy rate, and it is significantly less vulnerable to overfitting. Phase information can be used well at the same time, which is impossible for the CNN. The method of training data generation is given, and some specific implementation details are given. The superiority of the method in this paper is verified by using simulated and measured data obtained from a 200Ghz image system.

Terahertz imaging technology is widely used in nondestructive testing (NDT), human security inspection, far-field imaging systems, and so on. Improving image resolution is always a topic of discussion. For visible image and image super-resolution, the convolutional neural network (CNN) has achieved a better improvement effect than the traditional algorithm. Compared to optics, it is quite feasible to gain both the amplitude and phase information in THz imaging, the Complex-valued convolutional neural network (CV-CNN) is better suited for the field of terahertz imaging than the real-valued neural network. In this paper, A lightweight complex-valued neural network is constructed which enhances terahertz imaging in a vector network analyzer (VNA) imaging system. Compared to CNN, CV-CNN has a better peak signal-to-noise ratio (PSNR) and structural similarity (SSIM), and it is significantly less vulnerable to overfitting. Phase information can be used well at the same time, which is impossible for CNN. The network is trained using the MNIST dataset and verified by using simulated and measured data obtained from a 200Ghz imager.