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%\section{2D-model fitting}
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%\section{2D-model fitting}
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%\subsection{Star/galaxy separation}
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%\subsection{Star/galaxy separation}
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%With the local \index{PSF} PSF and a noise \index{mode} model in hand, one can easily derive an optimum
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%With the local \index{PSF} PSF and a noise \index{mode} model in hand, one can easily derive an optimum
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%star/galaxy classifier. The problem was first addressed by \cite{sebok:1979}
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%star/galaxy classifier. The problem was first addressed by \cite{sebok:1979}
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and \cite{valdes:1982}. If detections can be classified as either a star
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%and \cite{valdes:1982}. If detections can be classified as either a star
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%(s) or a galaxy (g), then the {\em a posteriori} probability for having a
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%(s) or a galaxy (g), then the {\em a posteriori} probability for having a
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%star, given the observed vector of pixel values $\vec{I}$ is given by the Bayes
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%star, given the observed vector of pixel values $\vec{I}$ is given by the Bayes
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%theorem:
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%theorem:
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%\begin{equation}
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%\begin{equation}
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%P(s|\vec{I}) = \frac{P(\vec{I}|s)P(s)}{P(\vec{I}|s)P(s)+p(\vec{I}|g)P(g)},
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%P(s|\vec{I}) = \frac{P(\vec{I}|s)P(s)}{P(\vec{I}|s)P(s)+p(\vec{I}|g)P(g)},
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