Polarization-based material classification technique using passive millimeter-wave polarimetric imagery

• DOI: 10.1364/ao.55.008690
• Publication Date: 2016-10-19T20:38:30Z
• Authors: Fei Hu; Yayun Cheng; Liangqi Gui; Liang Wu; Xinyi Zhang; Xiaohui Peng; Jinlong Su
• Keywords: Extremely high frequency; Discriminator

The polarization properties of thermal millimeter-wave emission capture inherent information objects, e.g., material composition, shape, and surface features. In this paper, a polarization-based material-classification technique using passive polarimetric imagery is presented. Linear ratio (LPR) created to be new feature discriminator that sensitive type remove the reflected ambient radiation effect. LPR characteristics several common natural artificial materials are investigated by theoretical experimental analysis. Based on priori about characteristics, optimal range incident angle classification criterion discussed. Simulation measurement results indicate presented effective for distinguishing between metals dielectrics. This suggests possible applications outdoor metal target detection in open scenes.