针对雾霾天气条件下目标对比度下降问题, 研制成功了一套多光参量测量成像系统。通过多光参量成像的系统级辐射响应模型及模型参数分离式标定, 实现雾霾天气情况下的多种场景目标成像实验观测。结果显示: 楼房玻璃反射光中的偏振分量相对较强, 通过线偏振、圆偏振、偏振角图像, 可以清晰地分辨玻璃窗结构; 普通的强度信息很难辨别雾霾天气下的路口车辆, 在线偏振及偏振角图像中能够看到车辆, 但是掺杂了树木的偏振信息, 车辆信息较模糊; 在圆偏振信息图像中, 树木的圆偏振信息较少, 车辆目标对比度提高20%。

A multi-optical parametric imaging system is introduced and established in order to improve the contrast of object in fog and haze weather. A few targets in multiple scenes are observed in fog and haze weather based on system-level radiation response model for multi-optical parametric imaging and separated calibration of model parameters.Results show that the buildings windows can be distinguished clear in the images of linear polarization, circular polarization and polarizing angle because of the strong reflected polarization light of the glass. The vehicles in intersection can be hardly seen in the intensity image, and it is fuzzy in degree of linear polarization and angle of polarization images because of the doped polarization information of trees near in fog. The circular polarization image raises the contrast of the vehicles by 20% because the circle polarization of the trees is less in the fog.