Statistics – Computation
Scientific paper
Feb 1993
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1993an....314...49m&link_type=abstract
Astronomische Nachrichten (ISSN 0004-6337), vol. 314, no. 2, p. 49-67.
Statistics
Computation
Double Stars, Image Analysis, Stellar Composition, Stellar Spectrophotometry, Stellar Systems, Autocorrelation, Binary Stars, Computational Astrophysics
Scientific paper
With this paper we present the mathematical background for a novel method for the deconvolution of longer exposed double star images, merged by seeing and other effects. This method, which was recently presented in a short paper (Mueller and Geyer 1993) makes use of the autocorrelation of the odd function of the merged, and thus asymmetric two dimensional double star image profile. We give the mathematical evidence that digital filtering during the image processing does not influence the angular distance of the binary components, and that it can be determined independently of the brightness difference of the components. The brightness difference itself can be obtained without ambiguity, if it does not exceed 3 mag, and then the distance has been derived before. We further show that the information content of stellar images is generally less degraded by seeing effects as was previously supposed. Thus closer double stars can be resolved and photometrically deconvoluted by the method. By atmospheric disturbances, telescope guiding errors, optical distortions and silhouetting generally the stellar images on astrometric photographs of modern opto-electronic detectors are asymmetrically deformed. Therefore, the method yields also better accuracy and more adequate results for astrometry, photometry, and also astrospectroscopy.
Geyer Edward H.
Mueller Ralf R.
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