Automatic Segmentation of Granules of the Solar Photosphere Using Morphological Reconstruction and Watershed Transform

The solar surface is covered by granulations. Segmenting granular elements are playing an important role in analyzing granules motions and evolutions. In this paper, we present a novel method, using morphological reconstruction and watershed transform, to segment granules in the solar photosphere. First a morphological filtering of opening-by-reconstruction and closing-by-reconstruction is used to eliminate image noise. Next, the Otsu technique is implemented to obtain an adaptive threshold. Finally, we computed the watershed transform of the distance transform of the internal marker image to obtain optimal segmentation results. The proposed segmentation method is evaluated utilizing their area and their shape. Our method yields more accurate segmentation results than the watershed method, implying that it can be to further analyze such as granular evolution or their statistical properties.