Processing and fusion for human body terahertz dual-band passive image

Compared with microwave, THz has higher resolution, and compared with infrared, THz has better penetrability. Human body radiate THz also, its photon energy is low, it is harmless to human body. So THz has great potential applications in the body searching system. Dual-band images may contain different information for the same scene, so THz dual-band imaging have been a significant research subject of THz technology. Base on the dual-band THz passive imaging system which is composed of a 94GHz and a 250GHz cell detector, this paper researched the preprocessing and fusion algorithm for THz dual-band images. Firstly, THz images have such problems: large noise, low SNR, low contrast, low details. Secondly, the stability problem of the optical mechanical scanning system makes the images less repetitive, obvious stripes and low definition. Aiming at these situations, this paper used the BM3D de-noising algorithm to filter noise and correct the scanning problem. Furthermore, translation, rotation and scaling exist between the two images, after registered by the intensity-base registration algorithm, and enhanced by the adaptive histogram equalization algorithm, the images are fused by image fusion algorithm based on wavelet. This effectively reduced the image noise, scan distortion and matching error, improved the details, enhanced the contrast. It is helpful to improve the detection efficiency of hidden objects too. Method in this paper has a substantial effect for improving the dual-band THz passive imaging system's performance and promoting technology practical.