103,524 research outputs found

    Detection of point sources on two-dimensional images based on peaks

    Get PDF
    This article considers the detection of point sources in two dimensional astronomical images. The detection scheme we propose is based on peak statistics. We discuss the example of the detection of far galaxies in Cosmic Microwave Background experiments throughout the paper, although the method we present is totally general and can be used in many other fields of data analysis. We assume sources with a Gaussian profile --that is a fair approximation of the profile of a point source convolved with the detector beam in microwave experiments-- on a background modeled by a homogeneous and isotropic Gaussian random field characterized by a scale-free power spectrum. Point sources are enhanced with respect to the background by means of linear filters. After filtering, we identify local maxima and apply our detection scheme, a Neyman-Pearson detector that defines our region of acceptance based on the a priori pdf of the sources and the ratio of number densities. We study the different performances of some linear filters that have been used in this context in the literature: the Mexican Hat wavelet, the matched filter and the scale-adaptive filter. We consider as well an extension to two dimensions of the biparametric scale adaptive filter (BSAF). The BSAF depends on two parameters which are determined by maximizing the number density of real detections while fixing the number density of spurious detections. For our detection criterion the BSAF outperforms the other filters in the interesting case of white noise.Comment: 21 pages, 3 figures, version accepted for publication on EURASIP Journal on Applied Signal Processing: Applications of Signal Processing in Astrophysics and Cosmolog

    The correct estimate of the probability of false detection of the matched filter in the detection of weak signals. II. (Further results with application to a set of ALMA and ATCA data)

    Full text link
    The matched filter (MF) is one of the most popular and reliable techniques to the detect signals of known structure and amplitude smaller than the level of the contaminating noise. Under the assumption of stationary Gaussian noise, MF maximizes the probability of detection subject to a constant probability of false detection or false alarm (PFA). This property relies upon a priori knowledge of the position of the searched signals, which is usually not available. Recently, it has been shown that when applied in its standard form, MF may severely underestimate the PFA. As a consequence the statistical significance of features that belong to noise is overestimated and the resulting detections are actually spurious. For this reason, an alternative method of computing the PFA has been proposed that is based on the probability density function (PDF) of the peaks of an isotropic Gaussian random field. In this paper we further develop this method. In particular, we discuss the statistical meaning of the PFA and show that, although useful as a preliminary step in a detection procedure, it is not able to quantify the actual reliability of a specific detection. For this reason, a new quantity is introduced called the specific probability of false alarm (SPFA), which is able to carry out this computation. We show how this method works in targeted simulations and apply it to a few interferometric maps taken with the Atacama Large Millimeter/submillimeter Array (ALMA) and the Australia Telescope Compact Array (ATCA). We select a few potential new point sources and assign an accurate detection reliability to these sources.Comment: 28 pages, 20 figures, Astronomy & Astrophysics, Minor changes and some typos correcte

    A Bayesian approach to filter design: detection of compact sources

    Full text link
    We consider filters for the detection and extraction of compact sources on a background. We make a one-dimensional treatment (though a generalization to two or more dimensions is possible) assuming that the sources have a Gaussian profile whereas the background is modeled by an homogeneous and isotropic Gaussian random field, characterized by a scale-free power spectrum. Local peak detection is used after filtering. Then, a Bayesian Generalized Neyman-Pearson test is used to define the region of acceptance that includes not only the amplification but also the curvature of the sources and the a priori probability distribution function of the sources. We search for an optimal filter between a family of Matched-type filters (MTF) modifying the filtering scale such that it gives the maximum number of real detections once fixed the number density of spurious sources. We have performed numerical simulations to test theoretical ideas.Comment: 10 pages, 2 figures. SPIE Proceedings "Electronic Imaging II", San Jose, CA. January 200

    X-ray Astronomical Point Sources Recognition Using Granular Binary-tree SVM

    Full text link
    The study on point sources in astronomical images is of special importance, since most energetic celestial objects in the Universe exhibit a point-like appearance. An approach to recognize the point sources (PS) in the X-ray astronomical images using our newly designed granular binary-tree support vector machine (GBT-SVM) classifier is proposed. First, all potential point sources are located by peak detection on the image. The image and spectral features of these potential point sources are then extracted. Finally, a classifier to recognize the true point sources is build through the extracted features. Experiments and applications of our approach on real X-ray astronomical images are demonstrated. comparisons between our approach and other SVM-based classifiers are also carried out by evaluating the precision and recall rates, which prove that our approach is better and achieves a higher accuracy of around 89%.Comment: Accepted by ICSP201

    A two-dimensional Kolmogorov-Smirnov test for crowded field source detection: ROSAT sources in NGC 6397

    Get PDF
    We present a two-dimensional version of the classical one-dimensional Kolmogorov-Smirnov (K-S) test, extending an earlier idea due to Peacock (1983) and an implementation proposed by Fasano & Franceschini (1987). The two-dimensional K-S test is used to optimise the goodness of fit in an iterative source-detection scheme for astronomical images. The method is applied to a ROSAT/HRI x-ray image of the post core-collapse globular cluster NGC 6397 to determine the most probable source distribution in the cluster core. Comparisons to other widely-used source detection methods, and to a Chandra image of the same field, show that our iteration scheme is superior in measuring statistics-limited sources in severely crowded fields.Comment: 12 pages, 6 figures, 6 tables. Accepted by MNRA

    A multi-scale, multi-wavelength source extraction method: getsources

    Full text link
    We present a multi-scale, multi-wavelength source extraction algorithm called getsources. Although it has been designed primarily for use in the far-infrared surveys of Galactic star-forming regions with Herschel, the method can be applied to many other astronomical images. Instead of the traditional approach of extracting sources in the observed images, the new method analyzes fine spatial decompositions of original images across a wide range of scales and across all wavebands. It cleans those single-scale images of noise and background, and constructs wavelength-independent single-scale detection images that preserve information in both spatial and wavelength dimensions. Sources are detected in the combined detection images by following the evolution of their segmentation masks across all spatial scales. Measurements of the source properties are done in the original background-subtracted images at each wavelength; the background is estimated by interpolation under the source footprints and overlapping sources are deblended in an iterative procedure. In addition to the main catalog of sources, various catalogs and images are produced that aid scientific exploitation of the extraction results. We illustrate the performance of getsources on Herschel images by extracting sources in sub-fields of the Aquila and Rosette star-forming regions. The source extraction code and validation images with a reference extraction catalog are freely available.Comment: 31 pages, 27 figures, to be published in Astronomy & Astrophysic

    Plausible fluorescent Ly-alpha emitters around the z=3.1 QSO0420-388

    Full text link
    We report the results of a survey for fluorescent Ly-alpha emission carried out in the field surrounding the z=3.1 quasar QSO0420-388 using the FORS2 instrument on the VLT. We first review the properties expected for fluorescent Ly-alpha emitters, compared with those of other non-fluorescent Ly-alpha emitters. Our observational search detected 13 Ly-alpha sources sparsely sampling a volume of ~14000 comoving Mpc^3 around the quasar. The properties of these in terms of i) the line equivalent width, ii) the line profile and iii) the value of the surface brightness related to the distance from the quasar, all suggest that several of these may be plausibly fluorescent. Moreover, their number is in good agreement with the expectation from theoretical models. One of the best candidates for fluorescence is sufficiently far behind QSO0420-388 that it would imply that the quasar has been active for (at least) ~60 Myrs. Further studies on such objects will give information about proto-galactic clouds and on the radiative history (and beaming) of the high-redshift quasars.Comment: 10 pages, 4 figures.Update to match the version published on ApJ 657, 135, 2007 March
    • …
    corecore