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| Paper: |
Quantitative Evaluation of Source Detection Strategies in Astronomical Images |
| Volume: |
461, Astronomical Data Analysis Software and Systems XXI |
| Page: |
793 |
| Authors: |
Masias, M.; Freixenet, J.; Lladó, X.; Peracaula, M. |
| Abstract: |
In astronomical imaging great efforts have been done aiming to perform automatic detections of stellar bodies in wide field images or in large surveys. These images contain large volumes of data at different intensity scales and often have a high component of noise. For these reasons, even the source detection done by visual inspection is a challenging task. With the idea to improve this source detection process, different automatic tools have been proposed. We present in this paper a review of the main approaches for the automatic detection of sources in astronomical images. Several approaches that use images at different frequency bands are analysed in order to find out their advantages and drawbacks, and to specify the key points that make them remarkable for the astronomical community. We classify the most important techniques into different strategies according to the type of pre-processing applied and the strategy used to deal with the detection problem. A qualitative and quantitative evaluation of the results of the most outstanding approaches is also presented. Finally, we discuss on the open research fields of the astronomical object detection. |
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