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Algorithms for Cloud Segmentation with Ground-based Camera Images

This paper deals with the detection and segmentation of clouds on high-dynamic-range (HDR) images of the sky as well as the calculation of the position of the sun at any time of the year. In order to predict the movement of clouds and the radiation of the sun for a short period of time, the clouds thickness and position have to be known as precisely as possible [1, 2]. Consequently, the segmentation algorithm has to provide satisfactory results regardless of different weather, illumination and climatic conditions [3]. The principle of the segmentation is based on the classification of each pixel as a cloud or as a sky. This classification is usually based on threshold methods, since these are relatively fast to implement and show a low computational burden [4, 5].