Sky cloud detection has a significant application value in the meteorological field. The existing cloud detection methods mainly rely on the color difference between the sky background and the cloud layer in the sky image and are not reliable due to the variable and irregular characteristics of the cloud layer and different weather conditions. This paper proposes a cloud detection method based on all-sky polarization imaging. The core of the algorithm is the “normalized polarization degree difference index” (NPDDI). Instead of relying on the color difference information, this index identifies the difference between degree of polarization (DoPs) of the cloud sky and the clear sky radiation to achieve cloud recognition. The method is not only fast and straightforward in the algorithm, but also can detect the optical thickness of the cloud layer in a qualitative sense. The experimental results show a good cloud detection performance.
Our previous work has constructed a polarized light orientation determination (PLOD) artificial neural network. Although a PLOD network can determine the solar azimuth angle, it cannot determine the solar elevation angle. Therefore, this paper proposes an artificial neural network for polarized light solar position determination (PLSPD), which has two branches: the solar azimuth angle determination branch and the solar elevation angle determination branch. Since the solar elevation angle has no cyclic characteristics, and the angle range of the solar elevation angle is different from that of the solar azimuth angle, the solar elevation angle exponential function encoding is redesigned. In addition, compared with the PLOD, the PLSPD deletes a local full connection layer to simplify the network structure. The experimental results show that the PLSPD can determine not only the solar azimuth angle but also the solar elevation angle, and the solar azimuth angle determination accuracy of the PLSPD is higher than that of the PLOD.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.