Astrometry in wide-field surveys
Astrometry in wide-field surveys
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DOI：
10.1086/508573
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发表时间：
2006-10-01
影响因子：
3.5
通讯作者：
Bakos, Gaspar A.
中科院分区：
文献类型：
--
作者：
Pal, Andras;Bakos, Gaspar A.
我们提出了一个强大的和快速的算法，用于执行天体测量和源交叉识别的二维点列表，如目录和天文图像之间，或两个图像之间。该方法基于最小的假设：列表可以以任意方式旋转，放大和反转。该算法被定制为有效地工作在具有大量源和显著非线性失真的宽场上，只要失真可以在点之间的平均距离的尺度长度上局部地用线性变换近似。该过程是基于对称点匹配在一个新定义的连续三角形空间，由扩展Delaunay三角剖分生成的三角形。我们的软件实现在类似于HATNet项目所拍摄的260，000帧上以99.995%的成功率执行。
We present a robust and fast algorithm for performing astrometry and source cross- identification on lists of two- dimensional points, such as between a catalog and an astronomical image, or between two images. The method is based on minimal assumptions: the lists can be rotated, magnified, and inverted with respect to each other in an arbitrary way. The algorithm is tailored to work efficiently on wide fields with a large number of sources and significant nonlinear distortions, as long as the distortions can be approximated with linear transformations locally over the scale length of the average distance between the points. The procedure is based on symmetric point matching in a newly defined continuous triangle space that consists of triangles generated by extended Delaunay triangulation. Our software implementation performed at the 99.995% success rate on similar to 260,000 frames taken by the HATNet project.