Enhancement effect of terahertz wave security inspection images by combining large threshold value mean filtering with Canny algorithm

Owing to its non-damage property and noninvasive detection, terahertz waves have broad application prospects in the field of human safety detection. However, due to the limitation of the resolution of the terahertz wave itself and the interference of the external environment, the passive terahertz human safety imaging system obtains the initial terahertz wave human body image with high noise, resulting in poor image contrast, blurred boundaries and cannot be directly recognized by the machine. How to improve the image quality and resolution of terahertz human body and hidden objects has become a key problem in terahertz human safety imaging research. In this paper, we employed a passive terahertz wave human body security inspection imaging system to image the human body and hidden objects. An algorithm combining mean filtering of large threshold values with canny is proposed to improve the quality of the passive terahertz wave human security inspection image. The image is denoising through large threshold values mean filtering, and the Canny algorithm is used to obtain the clear edge of the human body and hidden objects, and retain and highlight the terahertz image details of the human body and hidden objects. The experimental results show that the combination of large threshold values mean filtering and Canny algorithm has a good noise reduction effect on terahertz images, which will let the images have clear details and high contrast, and make them suitable for passive terahertz human body security imaging system.