Cosmic-ray rejection by linear filtering of single images

James E. Rhoads

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

We present a convolution-based algorithm for finding cosmic rays in single well-sampled astronomical images. The spatial filter used is the point-spread function (approximated by a Gaussian) minus a scaled delta function, and cosmic rays are identified by thresholding the filtered image. This filter searches for features with significant power at spatial frequencies too high for legitimate objects. Noise properties of the filtered image are readily calculated, which allows us to compute the probability of rejecting a pixel not contaminated by a cosmic ray (the false alarm probability). We demonstrate that the false alarm probability for a pixel containing object flux will never exceed the corresponding probability for a blank-sky pixel, provided we choose the convolution kernel appropriately. This allows confident rejection of cosmic rays superposed on real objects. Identification of multiple-pixel cosmic-ray hits can be enhanced by running the algorithm iteratively, replacing flagged pixels with the background level at each iteration.

Original languageEnglish (US)
Pages (from-to)703-710
Number of pages8
JournalPublications of the Astronomical Society of the Pacific
Volume112
Issue number771
DOIs
StatePublished - May 2000

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science

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