Automatic segmentation of solar granulations based on Morphology technique

Granulation segmentation of the solar photosphere is important step to obtain correct morphometric measures. In this paper, we present a novel method, using morphological technique, for granules segmentation in the solar photosphere. Firstly, a morphological filtering, employing opening-by-reconstruction and closing-by-reconstruction, is used to eliminate image noise. Secondly, Otsu technique is implemented to obtain an adaptive threshold. We use hole filling technique to fill the hole in the granular region. Finally, the Sobel edge-segmentation operator is utilized to extract the boundary of granules. It showed that the proposed method yields more accurate segmentation results than the watershed method, implying that it can be to further analyze such as granular evolution or statistical properties.