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Astrometry and Time-Resolved Photometry from Streaks Using Calibrated Ultra-Wide Field of View Cameras

机译:使用校准的超宽视野摄像机从条纹进行的占星术和时间分辨测光

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Extracting the astrometry and photometry of an observed object in an optical image can be complicated by a number of factors. Wide-angle lenses can introduce significant distortion into images. Popular methods for correcting for distortion assume basic symmetries in optical systems that may not be reflected in reality. Additionally, the photometric intensity and corresponding uncertainty of a streaking object should be extracted in an information optimal manor. This paper approaches both of these problems separately. First, an empirical method for image calibration based on a Delaunay triangulation with vertices defined by observed and catalog star locations is outlined. This method is theoretically capable of less than 0.8 pixel residual error across the image assuming correct association between the observed stars and catalog. Next a method is discussed for information optimal streak extraction based on breaking an observed streak into constant intensity streak segments. Both an analytical and computational method for determining the appropriate number of segments are discussed. The method for extracting the streak is then demonstrated against a sub-optimal method to show that the method extracts all observable information in the streak. These algorithms improve over existing methods for extracting streaking space object information from wide-angle images.
机译:提取光学图像中被观察物体的天体测定法和光度测定法可能会因许多因素而变得复杂。广角镜头会给图像带来明显的失真。校正畸变的流行方法采用光学系统中的基本对称性,而这些对称性在现实中可能不会反映出来。另外,应该在信息最佳庄园中提取裸奔物体的光度强度和相应的不确定性。本文分别解决了这两个问题。首先,概述了一种基于Delaunay三角剖分的图像校准的经验方法,该三角剖分的顶点由观察到的星号位置和目录星号位置定义。假设观察到的恒星与星表之间具有正确的关联,则该方法理论上能够在整个图像中实现小于0.8像素的残留误差。接下来讨论基于将观察到的条纹分成恒定强度的条纹段的信息最优条纹提取方法。讨论了确定适当段数的分析方法和计算方法。然后针对次优方法演示了提取条纹的方法,以表明该方法提取了条纹中的所有可观察信息。这些算法对现有的从广角图像中提取条纹物体信息的方法进行了改进。

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