Automatic Identification and Extraction of Clouds from Astronomical Images Based on Support Vector Machinetwo

For the time-domain astronomical research, the optical telescopes with a small and medium aperture can get a huge amount of data through automatic sky surveying. A certain proportion of automatically acquired data are interfered by clouds, which makes it very difficult to automatically extract the dim objects and make photometry. Therefore, it is necessary to identify and extract clouds from these images as the index figures for a reference in the subsequent information extraction. In this paper, an astronomical image selection system based on the support vector machine is proposed, which sets the gray value inconsistency and texture difference as the reference to select the images interfered by clouds. Based on the classification results, by through the histogram transformation and feature selection, the index figures of clouds can be further extracted. The experimental results show that our method can achieve the real-time selection of astronomical images with a classification accuracy better than 98%. By the histogram transformation and feature selection the index figure of clouds can be preliminarily extracted as the references for the photometry and dim object extraction.