A low-loss terahertz (THz) hollow-core pipe waveguide constructed of plastic material is demonstrated. The structure is designed to be especially effective in transmitting THz waves of 110 GHz, which has important applications in communications, imaging, and sensing. Guiding of the electromagnetic wave is based on the principle of antiresonant reflection. Through careful theoretical analyses and systematic modeling and simulation, followed by a thorough experimental investigation, we show that the proposed structure can successfully transmit THz waves with low attenuation. Furthermore, when the structures of the pipe waveguides are varied for optimization, we find that cladding thickness and the refractive index under antiresonant conditions as well as the core diameter are important physical parameters in designing the low-loss THz waveguide. Considering not just attenuation loss but such factors as volume, weight, and flexibility of the tube waveguide, along with other practical issues such as cost, we arrive at an optimal design of the pipe waveguide, which has an inner diameter of 35 mm and cladding thickness of 5 mm. Teflon is chosen as the material for a guiding 110-GHz THz wave. The attenuation constant is determined by the simulation to be as low as 0.0228 m−1. However, due to nonuniformity of the waveguide wall thickness and random small bending of the waveguide, as well as moisture content in the air filling the pipe core, all of which strongly impede propagation in the waveguide, the experimentally measured attenuation loss (3.65 m−1) of the waveguide is much more significant than the theoretical prediction, with the latter serving as a design benchmark under perfect conditions.
This paper reports on our study of algorithms of stripe noise detection and removal in THz image processing. Based
on an analysis of the frequency spectrogram of images with stripe noises, we propose a new algorithm for stripe noise
detection and removal. Our experimental results show that the algorithm can effectively ascertain the existence of stripe
noises. Furthermore, it can remove stripe noises while preserving the original image details as much as possible.
Compared with other traditional de-noising algorithms, such as Mean filter and Gauss filter, the new algorithm is more
effective and convenient for detecting and subsequent removing of stripe noises.