Background derivation and image flattening: getimages

Abstract

Modern high-resolution images obtained with space observatories display extremely strong intensity variations across images on all spatial scales. Source extraction in such images with methods based on global thresholding may bring unacceptably large numbers of spurious sources in bright areas while failing to detect sources in low-background or low-noise areas. It would be highly beneficial to subtract background and equalize the levels of small-scale fluctuations in the images before extracting sources or filaments. This paper describes getimages, a new method of background derivation and image flattening. It is based on median filtering with sliding windows that correspond to a range of spatial scales from the observational beam size up to a maximum structure width $X_{\lambda }$. The latter is a single free parameter of getimages that can be evaluated manually from the observed image ${\mathcal{I}}_{\lambda }$. The median filtering algorithm provides a background image ${\tilde{\mathcal{B}}}_{\lambda }$ for structures of all widths below $X_{\lambda }$. The same median filtering procedure applied to an image of standard deviations ${\mathcal{D}}_{\lambda }$ derived from a background-subtracted image ${\tilde{\mathcal{S}}}_{\lambda }$ results in a flattening image ${\tilde{\mathcal{F}}}_{\lambda }$. Finally, a flattened detection image ${\mathcal{I}}_{\lambda \mathrm{D}}={\tilde{\mathcal{S}}}_{\lambda }/{\tilde{\mathcal{F}}}_{\lambda }$ is computed, whose standard deviations are uniform outside sources and filaments. Detecting sources in such greatly simplified images results in much cleaner extractions that are more complete and reliable. As a bonus, getimages reduces various observational and map-making artifacts and equalizes noise levels between independent tiles of mosaicked images.

14 pages, 11 figures (main text + 3 appendices), accepted by Astronomy & Astrophysics; fixed Metadata abstract (typesetting)

References in corpus (7)

• Herschel Space Observatory - An ESA facility for far-infrared and submillimetre astronomy
• From filamentary clouds to prestellar cores to the stellar IMF: Initial highlights from the Herschel Gould Belt survey
• Filamentary structures and compact objects in the Aquila and Polaris clouds observed by Herschel
• A multi-scale, multi-wavelength source extraction method: getsources
• Source extraction and photometry for the far-infrared and sub-millimeter continuum in the presence of complex backgrounds
• A multi-scale filament extraction method: getfilaments
• Uncertainties and biases of source masses derived from fits of integrated fluxes or image intensities

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• Mass segregation and sequential star formation in NGC 2264 revealed by Herschel
• Fragmentation of star-forming filaments in the X-shape Nebula of the California molecular cloud
• ALMA-IMF XV: The core mass function in the high-mass star-formation regime
• Strong dependence of the physical properties of cores on spatial resolution in observations and simulations
• ALMA observations of RCW 120 Fragmentation at 0.01pc scale
• Multicomponent, multiwavelength benchmarks for source- and filament-extraction methods
• Probing the filamentary nature of star formation in the California giant molecular cloud
• Estimating the confusion noise for the Millimetron space telescope
• Sources of confusion noise in the infrared wavelength range