Matthew Cheselka (IRAF Group, National Optical Astronomy Obervatories, Tucson AZ 85726)
Reference URL: http://iraf.noao.edu/~cheselka/lfindit.html
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) or bad rows and columns of CCD arrays. 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. Once features have been identifed, information about the features are 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.