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Deblending of the UV photometry in GALEX deep surveys using optical priors in the visible wavelengths

机译:使用可见光波长中的光学先验在GALEX深度测量中对UV光度法进行混合

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The GALEX mission of NASA, is collecting an unprecedent set of astronomical UV data in the far and the near UV range. The telescope measures the full sky in a continuous automatic scan. Knowing the attitude data, local images are simultaneously extracted and corrected for smearing and instrumental effects. Final UV images show, by far, a lower resolution than their visible counterpart. It originates blends, ambiguities and miss-identifications of the astronomical sources. Our purpose is to deduce from the UV image the UV photometry of the visible objets through a bayesian approach, using the visible data (catalog and image) as the starting reference for the UV analysis. For the feasibility reasons as the deep field images are very large, a segmentation procedure has been defined to manage the analysis in a tractable form. The present paper discusses all these aspects and details the full method and performances.
机译:NASA的GALEX任务正在收集远近紫外线范围内前所未有的天文紫外线数据集。望远镜以连续自动扫描的方式测量整个天空。知道了姿态数据后,就可以同时提取局部图像并进行校正以消除拖影和仪器效果。最终的UV图像显示的分辨率远低于其可见图像。它起源于天文源的混合,歧义和误识别。我们的目的是通过贝叶斯方法从可见光物体的可见光数据(目录和图像)作为紫外线分析的起始参考,从可见光物体的紫外光度推论得出。出于可行性原因,由于深场图像非常大,因此定义了分割程序以易于处理的形式管理分析。本文讨论了所有这些方面,并详细介绍了完整的方法和性能。

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