Schedule by Session

Blending of galaxies with foreground stars and other galaxies leads to systematic errors in photometry measurements. Along with low surface brightness wings, these make accurate photometry of resolved galaxy images a major challenge. This talk will present recent work towards using a Bayesian approach to this deblending problem. By using the Bayesian evidence to compare competing models of a galaxy profile, it is possible to provide a more robust method for fitting. This will aid with calculating morphological parameters and performing deblending on upcoming deep and wide telescopes such as the Large Synoptic Survey Telescope.