Abstract：Affected by the atmospheric pollution,the moonlight and the zodiac light,the night-sky cloud images vary greatly. The conventional threshold methods which only utilize pixel gray value as well as the neighborhood information are difficult to segment the image accurately because of their uneven backgrounds. In this paper,two prior features of cloud images are observed from the statistical analysis,and a prior threshold surface based cloud segmentation algorithm is presented. After reliable background regions are extracted according to the prior features,an adaptive threshold surface can be obtained by polynomial fitting on the background regions,and the values of the threshold surface are between the clouds and backgrounds. Thus the cloud can be segmented from the background. The experimental results show that the proposed algorithm is more feasible and effective compared with other existing algorithms. Moreover,it produces fine results on the cloud images of light influence.
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2013, Vol. 26 
