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| Paper: |
Image Reduction Pipeline for the Detection of Variable Sources in Highly Crowded Fields |
| Volume: |
295, Astronomical Data Analysis Software and Systems XII |
| Page: |
229 |
| Authors: |
Gössl, C. A.; Riffeser, A. |
| Abstract: |
We present a reduction pipeline for CCD (charge-coupled device) images which was built to search for variable sources in highly crowded fields such as the M 31 bulge. We describe all the steps of the standard reduction including per pixel error propagation: Bias correction, treatment of bad pixels, flatfielding, and filtering of cosmic ray events. We utilize a flux and PSF (point spread function) conserving alignment procedure and a signal-to-noise maximizing stacking method. We build difference images via image convolution with a technique called OIS (optimal image subtraction, Alard & Lupton 1998), proceed with PSF-fitting, relative photometry on all pixels and finally apply an automatic detection of variable sources. The complete per pixel error propagation allows us to give accurate errors for each measurement. |
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