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. Consequently, the segmentation algorithm has to provide satisfactory results regardless of different weather, illumination and climatic conditions. 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. In order to predict if and when the sun will be covered by clouds, the position of the sun on the images has to be determined. For this purpose, the zenith and azimuth angles of the sun are determined and converted into XY coordinates.
The need to measure basic aerosol parameters has increased dramatically in the last decade. This is due mainly to their harmful effect on the environment and on public health. Legislation requires that particle emissions and ambient levels, workplace particle concentrations and exposure to them are measured to confirm that the defined limits are met and the public is not exposed to harmful concentrations of aerosols.