Multiscale, multiwavelength extraction of sources and filaments using separation of the structural components: getsf

TL;DR

The paper introduces getsf, a novel multiwavelength image analysis method that separates structural components like sources and filaments, improving extraction accuracy in complex astronomical images across various wavelengths.

Contribution

It presents getsf, a new structural decomposition technique for multiwavelength astronomical images, and introduces hires, an improved algorithm for high-resolution surface density derivation from Herschel data.

Findings

Successfully separates sources and filaments in complex images

Creates a multiwavelength benchmark dataset for evaluation

Achieves high-resolution surface density maps at 5.6 arcsec

Abstract

High-quality astronomical images delivered by modern ground-based and space observatories demand adequate, reliable software for their analysis and accurate extraction of sources, filaments, and other structures, containing massive amounts of detailed information about the complex physical processes in space. The multiwavelength observations with highly variable angular resolutions across wavebands require extraction tools that preserve and use the invaluable high-resolution information. This paper presents getsf, a new method for extracting sources and filaments in astronomical images using separation of their structural components, designed to handle multiwavelength sets of images and very complex filamentary backgrounds. The method spatially decomposes the original images and separates the structural components of sources and filaments from each other and from their backgrounds, flattening their resulting images. It spatially decomposes the flattened components, combines them over wavelengths, detects the positions of sources and skeletons of filaments, and measures the detected sources and filaments. This paper presents a realistic multiwavelength set of simulated benchmark images that can serve as the standard benchmark problem to evaluate qualities of source- and filament-extraction methods. This paper describes hires, an improved algorithm for the derivation of high-resolution surface densities from the multiwavelength far-infrared Herschel images. The algorithm allows creating the surface densities with angular resolutions that reach 5.6 arcsec, when the 70 micron image is used. The codes getsf and hires are illustrated by their applications to a variety of images, from the X-ray domain to the millimeter wavelengths.