Abstract
Second-generation connectivity opened the path to the use of mask images to freely define connectivity among the image components. In theory, any image could be treated as a mask image that defines a certain connectivity. This creates a new problem in terms of which image to use. In this paper, clustering masks suitable for the analysis of astronomical images are discussed. The connectivity defined by such masks must be capable of preserving faint structures like the filaments that link merging galaxies while separating neighboring stars. In this way, the actual morphology of the objects of interest is kept. This is useful for proper segmentation. We show that viscous mathematical morphology operators have a superior performance and create appropriate connectivity masks that can deal with the characteristic features of astronomical images.
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Moschini, U., Trager, S.C., Wilkinson, M.H.F. (2013). Mask Connectivity by Viscous Closings: Linking Merging Galaxies without Merging Double Stars. In: Hendriks, C.L.L., Borgefors, G., Strand, R. (eds) Mathematical Morphology and Its Applications to Signal and Image Processing. ISMM 2013. Lecture Notes in Computer Science, vol 7883. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38294-9_41
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DOI: https://doi.org/10.1007/978-3-642-38294-9_41
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