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Paper: Automatic Detection of Linear Features in Astronomical Images
Volume: 172, Astronomical Data Analysis Software and Systems VIII
Page: 349
Authors: Cheselka, Matthew
Abstract: A new IRAF task has been developed that automatically identifies linear (line-like) features in an image or set of images. Such features could include moving targets taken over a long exposure (asteroids, meteors, satellites, aircraft), bad rows and columns of CCD arrays, featured caused by CCD ``bleeding'', or diffraction spikes. The linear features can have gaps and still be recognized as a single feature. Identifying a linear feature in the input image requires several steps. First, a list of pixels within a range of data values is found. Second, pixels within this list are examined to determine if they are colinear. Lastly, the task examines the colinear list of pixels and finds pixels which are adjacent within specified parameters. The colinearity detection is done via the Hough Transform (Gonzalez & Wintz 1987). Once features have been identified, information about the features is written to an output file and profile plots are generated. An optional binary mask can also be created in the case where bad CCD rows or columns are being identified, or where particular linear features need to be masked out.
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