Exploring three faint source detections methods for aperture synthesis radio images

Peracaula, M.; Torrent, Albert; Masias, M.; Lladó, Xavier; Freixenet, Jordi; Martı́, Josep; Sánchez‐Sutil, J. R.; Muñoz‐Arjonilla, A. J.; Paredes, J. M.

doi:10.1016/j.newast.2014.10.006

Cited by 2 publications

(3 citation statements)

References 23 publications

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“…There has been a strong movement in recent years to ensure that the automated source detection pipelines implemented for these next generation facilities produce catalogues with a high degree of completeness and reliability, together with well-defined and characterised measurement accuracy. Several recent analyses explore the properties of various source-finders, and propose refinements or developments to such tools (e.g., Popping et al 2012; Huynh et al 2012; Hales et al 2012; Hancock et al 2012; Mooley et al 2013; Peracaula et al 2015). At the second annual SKA Pathfinder Radio Continuum Surveys (SPARCS) workshop, held in Sydney over 2012 May 30 to 2012 June 1, many of these results were presented and discussed.…”

Section: Introductionmentioning

confidence: 99%

The ASKAP/EMU Source Finding Data Challenge

Hopkins

Whiting

Seymour

et al. 2015

Publ. Astron. Soc. Aust.

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The Evolutionary Map of the Universe (EMU) is a proposed radio continuum survey of the Southern Hemisphere up to declination +30• , with the Australian Square Kilometre Array Pathfinder (ASKAP). EMU will use an automated source identification and measurement approach that is demonstrably optimal, to maximise the reliability and robustness of the resulting radio source catalogues. As a step toward this goal we conducted a "Data Challenge" to test a variety of source finders on simulated images. The aim is to quantify the accuracy and limitations of existing automated source finding and measurement approaches. The Challenge initiators also tested the current ASKAPsoft source-finding tool to establish how it could benefit from incorporating successful features of the other tools. As expected, most finders show completeness around 100% at ≈10 σ dropping to about 10% by ≈5 σ . Reliability is typically close to 100% at ≈10 σ , with performance to lower sensitivities varying between finders. All finders show the expected trade-off, where a high completeness at low signal-to-noise gives a corresponding reduction in reliability, and vice versa. We conclude with a series of recommendations for improving the performance of the ASKAPsoft source-finding tool.

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Section: Introductionmentioning

confidence: 99%

The ASKAP/EMU Source Finding Data Challenge

Hopkins

Whiting

Seymour

et al. 2015

Publ. Astron. Soc. Aust.

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“…Blobs tagged as "point-like" are removed from the input image using a morphological dilation operator with configurable kernel shape (e.g. elliptic or squared) and size, as suggested in Peracaula et al (2015), and replaced with a random background realization. A kernel size larger than 5 pixels was assumed to prevent the source halo pixels to further affect the residual image.…”

Section: Filtering Compact Sourcesmentioning

confidence: 99%

“…While extensive studies have been performed on compact source search with several algorithms developed (Hancock et al 2012;Whiting 2009;Whiting & Humphreys 2012;Hopkins et al 2002;Bertin & Arnouts 1996;Hales et al 2012;Peracaula et al 2015;Hopkins et al 2015), particularly in the context of the ASKAP telescope, detection of extended sources in a completely unsupervised way (e.g. without requiring any a priori information or source templates) is still a partially explored field, at least for the radio domain.…”

Section: Introductionmentioning

confidence: 99%

Automated detection of extended sources in radio maps: progress from the SCORPIO survey

Riggi

Ingallinera

Leto

et al. 2016

Mon. Not. R. Astron. Soc.

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Automated source extraction and parameterization represents a crucial challenge for the nextgeneration radio interferometer surveys, such as those performed with the Square Kilometre Array (SKA) and its precursors. In this paper we present a new algorithm, dubbed CAESAR (Compact And Extended Source Automated Recognition), to detect and parametrize extended sources in radio interferometric maps. It is based on a pre-filtering stage, allowing image denoising, compact source suppression and enhancement of diffuse emission, followed by an adaptive superpixel clustering stage for final source segmentation. A parameterization stage provides source flux information and a wide range of morphology estimators for postprocessing analysis. We developed CAESAR in a modular software library, including also different methods for local background estimation and image filtering, along with alternative algorithms for both compact and diffuse source extraction. The method was applied to real radio continuum data collected at the Australian Telescope Compact Array (ATCA) within the SCORPIO project, a pathfinder of the ASKAP-EMU survey. The source reconstruction capabilities were studied over different test fields in the presence of compact sources, imaging artefacts and diffuse emission from the Galactic plane and compared with existing algorithms. When compared to a human-driven analysis, the designed algorithm was found capable of detecting known target sources and regions of diffuse emission, outperforming alternative approaches over the considered fields.

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Exploring three faint source detections methods for aperture synthesis radio images

Cited by 2 publications

References 23 publications

The ASKAP/EMU Source Finding Data Challenge

The ASKAP/EMU Source Finding Data Challenge

Automated detection of extended sources in radio maps: progress from the SCORPIO survey

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