Infrared polarization imaging has demonstrated significant advantages in target detection and recognition in natural environments. While there have been numerous research achievements on medium-wave/long-wave infrared polarization in a single band, there is a lack of related conclusions on the characteristics of wide spectral two-color infrared polarization imaging. To address this gap, this article employs a theoretical model in infrared polarization imaging to investigate the influence of temperature, incident angle, and refractive index on polarization degree and polarization angle. These findings have been substantiated through discussions on experimental results. We conducted a comparative analysis between intensity imaging and polarization imaging within the framework of traditional single-band infrared imaging. We then delineated the benefits of dual-color infrared polarization imaging. Finally, we harnessed image registration fusion algorithms to amalgamate multiple-band images. Our findings demonstrate that this fusion technique not only enables penetration through water mist but also enhances target visibility, providing theoretical support for all-weather target detection and identification.

This paper addresses the objectives in a complex context: the polarization mathematical and physical model of the basic components of the target/background is constructed by simulation modeling. The image fusion experiment is carried out based on a two-dimensional wavelet transformation. A high-resolution polarization imaging instrument was developed, and static experiments were carried out with polarization, infrared, and visible cameras. The result shows that using polarization imaging detection technology to detect physical evidence targets in complex backgrounds can effectively improve target contrast. It can enrich the target information, improve image quality, and improve target detection accuracy.