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High-quality astronomical images delivered by modern ground-based and spaceobservatories demand adequate, reliable software for their analysis andaccurate extraction of sources, filaments, and other structures, containingmassive amounts of detailed information about the complex physical processes inspace. The multiwavelength observations with highly variable angularresolutions across wavebands require extraction tools that preserve and use theinvaluable high-resolution information.  This paper presents getsf, a new method for extracting sources and filamentsin astronomical images using separation of their structural components,designed to handle multiwavelength sets of images and very complex filamentarybackgrounds. The method spatially decomposes the original images and separatesthe structural components of sources and filaments from each other and fromtheir backgrounds, flattening their resulting images. It spatially decomposesthe flattened components, combines them over wavelengths, detects the positionsof sources and skeletons of filaments, and measures the detected sources andfilaments. This paper presents a realistic multiwavelength set of simulatedbenchmark images that can serve as the standard benchmark problem to evaluatequalities of source- and filament-extraction methods.  This paper describes hires, an improved algorithm for the derivation ofhigh-resolution surface densities from the multiwavelength far-infraredHerschel images. The algorithm allows creating the surface densities withangular 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 ofimages, from the X-ray domain to the millimeter wavelengths.

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