Radiometric calibration is of critical importance for information quantification of imaging polarimeters. In this paper, an integral sphere which had been traced to cryogenic radiometer was used as transfer standard in our calibration facility. The linearity, uniformity, stability of our imaging polarimeter were calibrated. The combined uncertainty in the responsivity of an imaging polarimeter was about 7.5%. At last, technical proposals of reducing uncertainty budget were briefly discussed.
It is an important subject in information scout, battlefield surveillance and automatic target recognition to detect interesting objects from complicated background. Compared with intensity detection, polarization detection has its advantage in identifying some camouflage targets. Usually, in the studies of target polarization detection, circular polarization property is usually neglected because of its small value. But in particular conditions, the circular polarization property of target will be used to accomplish object detection with their obviously different value. In this study, a single reflectance model of Mueller matrix is established, and based on Fresnel's law, circular polarization property of object is analyzed which is obvious while linear polarization property is obscure in particular condition. It is available to use the circular polarization component to detect target.
Polarization imaging provides abundant information of object, i.e. surface roughness, texture, physical and chemical characters. Independently, intensity and polarimetric features give incomplete representations of an object of interest. These representations are complementary, and it is expected that the combination of complementary information will reduce false alarms, improve confidence in target identification, and improve the quality of the scene description. Polarization parameter images include the degree of polarization, the angle of polarization, azimuth angle etc. There are not only strong correlations between polarization parameter images, but also different characters, which gives image fusion challenges, namely, how to find the optimal polarization parameter image to take part in image fusion with intensity image. This paper presents a polarization image fusion method based on choquet fuzzy integral. Using this algorithm the best polarization parameter image and intensity image are fused, and the fusion result is evaluated. The experiments show that this method could automatically select the best polarization parameter images from multi-polarization parameters image, the resulting images can yield more detail and higher contrast, and can reduce the noise effectively. It is conducive to the subsequent target detection.
According to problems of the intensity imaging target detection on water surface in foggy weather such as the indistinction of the target and greatly loss of the target detail, a target detection method based on the target polarization characteristics for water surface target in foggy weather is proposed in this paper. To validate the method’s effectiveness, the indoor experiment is performed by using the simulation environment in foggy weather and the outdoor experiment is performed by using the water surface real fog environment. A lot of different intensity images and polarization images are got and then analysed and compared. The experimental results demonstrate that the polarization imaging detection can effectively obtain the polarization information of targets on water surface, and we can detect the water surface targets in foggy weather by polarization information retrieving and the target information restoring.