Cross-correlation methods for surface photometry - Two-component models

Details Cross-correlation methods for surface photometry - Two-component models Cross-correlation methods for surface photometry - Two-component models

Jun 1992

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1992mnras.256..673p&link_type=abstract

Monthly Notices of the Royal Astronomical Society (ISSN 0035-8711), vol. 256, no. 4, June 15, 1992, p. 673-678. Research support

Astronomy and Astrophysics

Astronomy

6

Astronomical Models, Astronomical Photometry, Cross Correlation, Galaxies, Imaging Techniques, Matched Filters, Parameterization, Templates

Scientific paper

The present extension of the cross-correlation or 'matched filter' technique for determining surface photometric parameters in low S/N data to two-component models with up to four model parameters indicates that the linearity and distributivity of the convolution process together substantially reduce the number of templates with which the data will be convolved. The derivation of a full four-parameter maximization requires only two or three times as much work as for a simple, single-component fit. The method is well suited to component-parameter determinations of many images in a single frame.

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