An Adaptive Homomorphic Aperture Photometry Algorithm for Merging Galaxies

TL;DR

This paper introduces an adaptive homomorphic aperture photometry algorithm that accurately measures total magnitudes of irregularly shaped merging galaxies, reducing background contamination and improving analysis of complex sources.

Contribution

The paper presents a novel automatic method combining morphological recognition and dilation to adaptively define apertures for irregular galaxy shapes, enhancing photometric accuracy.

Findings

Effective in measuring magnitudes of irregular merging galaxies.

Reduces contamination from nearby backgrounds.

Applicable to crowded field observations.

Abstract

We present a novel automatic adaptive aperture photometry algorithm for measuring the total magnitudes of merging galaxies with irregular shapes. First, we use a morphological pattern recognition routine for identifying the shape of an irregular source in a background-subtracted image. Then, we extend the shape of the source by using the Dilation image operation to obtain an aperture that is quasi-homomorphic to the shape of the irregular source. The magnitude measured from the homomorphic aperture would thus have minimal contamination from the nearby background. As a test of our algorithm, we applied our technique to the merging galaxies observed by the Sloan Digital Sky Survey (SDSS) and the Canada-France-Hawaii Telescope (CFHT). Our results suggest that the adaptive homomorphic aperture algorithm can be very useful for investigating extended sources with irregular shapes and sources in crowded regions.