Source extraction and photometry for the far-infrared and sub-millimeter continuum in the presence of complex backgrounds
Sergio Molinari, Eugenio Schisano, Fabiana Faustini, Michele, Pestalozzi, Anna Maria DiGiorgio, Scige John Liu

TL;DR
This paper introduces a novel curvature-based method for detecting and measuring compact sources in complex, variable backgrounds in far-infrared and sub-millimeter images, improving detection accuracy and source characterization.
Contribution
The proposed method uses double-differentiation to create a curvature image, enabling effective detection of compact sources amidst complex backgrounds, with simultaneous fitting of multiple sources.
Findings
Detection rates over 90% for sources above 3-sigma noise
Recovered peak fluxes within 30% for about 80% of sources
Effective in crowded fields with contaminating sources
Abstract
(Abridged) We present a new method for detecting and measuring compact sources in conditions of intense, and highly variable, fore/background. While all most commonly used packages carry out the source detection over the signal image, our proposed method builds from the measured image a "curvature" image by double-differentiation in four different directions. In this way point-like as well as resolved, yet relatively compact, objects are easily revealed while the slower varying fore/background is greatly diminished. Candidate sources are then identified by looking for pixels where the curvature exceeds, in absolute terms, a given threshold; the methodology easily allows us to pinpoint breakpoints in the source brightness profile and then derive reliable guesses for the sources extent. Identified peaks are fit with 2D elliptical Gaussians plus an underlying planar inclined plateau, with…
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