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.
ACCESS THE FULL ARTICLE
Li Tian, Yanchun Shen, Weiqi Jin, Guozhong Zhao, Yi Cai, "Processing and fusion for human body terahertz dual-band passive image," Proc. SPIE 10030, Infrared, Millimeter-Wave, and Terahertz Technologies IV, 100302P (3 November 2016);