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Object detection in multi-epoch data
Authors:G. Jogesh Babu   A. Mahabal   S.G. Djorgovski  R. Williams  
Affiliation:aDepartment of Statistics, 326 Joab L. Thomas Building, The Pennsylvania State University, University Park, PA 16802-2111, USA;bDivision of Physics, Mathematics, and Astronomy, California Institute of Technology Pasadena, CA 91125, USA;cCenter for Advanced Computing Research, California Institute of Technology Pasadena, CA 91125, USA
Abstract:In astronomy multiple images are frequently obtained at the same position of the sky for follow-up coaddition as it helps one go deeper and look for fainter objects. With large scale panchromatic synoptic surveys becoming more common, image co-addition has become even more necessary as new observations start to get compared with coadded fiducial sky in real time. The standard coaddition techniques have included straight averages, variance weighted averages, medians etc. A more sophisticated nonlinear response chi-square method is also used when it is known that the data are background noise limited and the point spread function is homogenized in all channels. A more robust object detection technique capable of detecting faint sources, even those not seen at all epochs which will normally be smoothed out in traditional methods, is described. The analysis at each pixel level is based on a formula similar to Mahalanobis distance.
Keywords:Mahalanobis distance   Chi-square   Faint source detection   Coaddition   Gaussian noise
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