  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.
