De-starring Challenging Cygnus Data: A Comparison of Three Methods
This report addresses recent questions concerning the RadPro de-starring process. Ultimately, the issues that gave rise to the questions proved to be unrelated to the de-starring process. However, the nature of the questions exposed some misunderstanding on how to evaluate de-starring results. A fundamental of the de-starring process is that not every data point that is extracted as a star is actually a star. This work applies and compares three different methods to very challenging data to illustrate how to evaluate de-starring results. These three methods include (1) the procedure in RadPro, (2) a version of StarStats8, and (3) a method found in the literature by Abel Diaz (L.A. Cosmic), that was developed for astrophysical applications by Pieter G. van Dokkum. In L.A. Cosmic the radiation stars are generated by cosmic-ray hits and the data of interest are true physical stars and galaxies. Dokkum’s work is heavily referenced and appears in over 1,000 citations; a scholarly article on the topic describes it. The term de-starring will include removing cosmic-ray hits from such data. Another de-starring application, developed by Archambault et al. at the M. D. Anderson Cancer Center at the University of Texas in Houston is reviewed in this work but no comparison is made, as the algorithm is very similar to that of RadPro. This process was not named in their paper, and we will refer to it as MDACC. The focus of this report is on identifying stars. Computing replacement values, a different topic, is not covered in this report.