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ANALYSIS OF CLOUDINESS BY SEGMENTATION AND MONITORING OF SATELLITE MAP IMAGES

Roman Melnyk, Yurii Kalychak, Roman Kvit

Abstract


The algorithm of the dynamic threshold segmentation of images using clipping plane in a three-dimensional XYZ image space is proposed. To build the clipping plane of the dynamic threshold the precession and nutation angles as the base threshold values are found. The developed algorithm is applied to the satellite map images to get cloudiness intensity. The satellite map images are transformed by segmentation and inversion. The segmented and inverted images are scanned to receive the distributed cumulative histograms. By the help of so-called cloudiness meter the statistical data is processed for calculation and monitoring of cloudiness in Ukraine. The formulas to create an image of the distributed cumulative histogram are considered. Formulas to reconstruct images of the rotated satellite map images are proposed. The satellite weather map images were taken from the Wunderground services. The clustering algorithm is used to classify the regions of Ukraine by cloudiness intensity, which were created distributed cumulative images. The clustering algorithm is based on the agglomerative procedure.

Keywords


segmentation; intensity; image threshold; XYZ-space; clipping plane; optimization; rotation angles; clustering; pixel; cumulative histogram; classification; inversion.

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