21,208 research outputs found
A multi-scale, multi-wavelength source extraction method: getsources
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
A multi-scale filament extraction method: getfilaments
Far-infrared imaging surveys of Galactic star-forming regions with Herschel
have shown that a substantial part of the cold interstellar medium appears as a
fascinating web of omnipresent filamentary structures. This highly anisotropic
ingredient of the interstellar material further complicates the difficult
problem of the systematic detection and measurement of dense cores in the
strongly variable but (relatively) isotropic backgrounds. Observational
evidence that stars form in dense filaments creates severe problems for
automated source extraction methods that must reliably distinguish sources not
only from fluctuating backgrounds and noise, but also from the filamentary
structures. A previous paper presented the multi-scale, multi-wavelength source
extraction method getsources based on a fine spatial scale decomposition and
filtering of irrelevant scales from images. In this paper, a multi-scale,
multi-wavelength filament extraction method getfilaments is presented that
solves this problem, substantially improving the robustness of source
extraction with getsources in filamentary backgrounds. The main difference is
that the filaments extracted by getfilaments are now subtracted by getsources
from detection images during source extraction, greatly reducing the chances of
contaminating catalogs with spurious sources. The intimate physical
relationship between forming stars and filaments seen in Herschel observations
demands that accurate filament extraction methods must remove the contribution
of sources and that accurate source extraction methods must be able to remove
underlying filamentary structures. Source extraction with getsources now
provides researchers also with clean images of filaments, free of sources,
noise, and isotropic backgrounds.Comment: 15 pages, 19 figures, to be published in Astronomy & Astrophysics;
language polished for better readabilit
Image Restoration Using Joint Statistical Modeling in Space-Transform Domain
This paper presents a novel strategy for high-fidelity image restoration by
characterizing both local smoothness and nonlocal self-similarity of natural
images in a unified statistical manner. The main contributions are three-folds.
First, from the perspective of image statistics, a joint statistical modeling
(JSM) in an adaptive hybrid space-transform domain is established, which offers
a powerful mechanism of combining local smoothness and nonlocal self-similarity
simultaneously to ensure a more reliable and robust estimation. Second, a new
form of minimization functional for solving image inverse problem is formulated
using JSM under regularization-based framework. Finally, in order to make JSM
tractable and robust, a new Split-Bregman based algorithm is developed to
efficiently solve the above severely underdetermined inverse problem associated
with theoretical proof of convergence. Extensive experiments on image
inpainting, image deblurring and mixed Gaussian plus salt-and-pepper noise
removal applications verify the effectiveness of the proposed algorithm.Comment: 14 pages, 18 figures, 7 Tables, to be published in IEEE Transactions
on Circuits System and Video Technology (TCSVT). High resolution pdf version
and Code can be found at: http://idm.pku.edu.cn/staff/zhangjian/IRJSM
Kajian motivasi ekstrinsik di antara Pelajar Lepasan Sijil dan Diploma Politeknik Jabatan Kejuruteraan Awam KUiTTHO
Kajian ini dijalankan untuk menyelidiki pengaruh dorongan keluarga, cara pengajaran pensyarah, pengaruh rakan sebaya dan kemudahan infrastruktur terhadap motivasi ekstrinsik bagi pelajar tahun tiga dan tahun empat lepasan sijil dan diploma politeknik Jabatan Kejuruteraan Awain Kolej Universiti Teknologi Tun Hussein Onn. Sampel kajian ini beijumlah 87 orang bagi pelajar lepasan sijil politeknik dan 38 orang bagi lepasan diploma politeknik. Data kajian telah diperolehi melalui borang soal selidik dan telah dianalisis menggunakan perisian SPSS (Statical Package For Sciences). Hasil kajian telah dipersembahkan dalam bentuk jadual dan histohgrapi. Analisis kajian mendapati bahawa kedua-dua kumpulan setuju bahawa faktor-faktor di atas memberi kesan kepada motivasi ekstrinsik mereka. Dengan kata lain faktpr-faktor tersebut penting dalam membentuk pelajar mencapai kecemerlangan akademik
Implementation of robust image artifact removal in SWarp through clipped mean stacking
We implement an algorithm for detecting and removing artifacts from
astronomical images by means of outlier rejection during stacking. Our method
is capable of addressing both small, highly significant artifacts such as
cosmic rays and, by applying a filtering technique to generate single frame
masks, larger area but lower surface brightness features such as secondary
(ghost) images of bright stars. In contrast to the common method of building a
median stack, the clipped or outlier-filtered mean stacked point-spread
function (PSF) is a linear combination of the single frame PSFs as long as the
latter are moderately homogeneous, a property of great importance for weak
lensing shape measurement or model fitting photometry. In addition, it has
superior noise properties, allowing a significant reduction in exposure time
compared to median stacking. We make publicly available a modified version of
SWarp that implements clipped mean stacking and software to generate single
frame masks from the list of outlier pixels.Comment: PASP accepted; software for download at
http://www.usm.uni-muenchen.de/~dgruen
Simple foreground cleaning algorithm for detecting primordial B-mode polarization of the cosmic microwave background
We reconsider the pixel-based, "template" polarized foreground removal method
within the context of a next-generation, low-noise, low-resolution (0.5 degree
FWHM) space-borne experiment measuring the cosmological B-mode polarization
signal in the cosmic microwave background (CMB). This method was put forward by
the Wilkinson Microwave Anisotropy Probe (WMAP) team and further studied by
Efstathiou et al. We need at least 3 frequency channels: one is used for
extracting the CMB signal, whereas the other two are used to estimate the
spatial distribution of the polarized dust and synchrotron emission. No
external template maps are used. We extract the tensor-to-scalar ratio (r) from
simulated sky maps consisting of CMB, noise (2 micro K arcmin), and a
foreground model, and find that, even for the simplest 3-frequency
configuration with 60, 100, and 240 GHz, the residual bias in r is as small as
Delta r~0.002. This bias is dominated by the residual synchrotron emission due
to spatial variations of the synchrotron spectral index. With an extended mask
with fsky=0.5, the bias is reduced further down to <0.001.Comment: 12 pages, 11 figures, accepted by Ap
Constraining the epoch of reionization with the variance statistic: simulations of the LOFAR case
Several experiments are underway to detect the cosmic redshifted 21-cm signal
from neutral hydrogen from the Epoch of Reionization (EoR). Due to their very
low signal-to-noise ratio, these observations aim for a statistical detection
of the signal by measuring its power spectrum. We investigate the extraction of
the variance of the signal as a first step towards detecting and constraining
the global history of the EoR. Signal variance is the integral of the signal's
power spectrum, and it is expected to be measured with a high significance. We
demonstrate this through results from a simulation and parameter estimation
pipeline developed for the Low Frequency Array (LOFAR)-EoR experiment. We show
that LOFAR should be able to detect the EoR in 600 hours of integration using
the variance statistic. Additionally, the redshift () and duration
() of reionization can be constrained assuming a parametrization. We
use an EoR simulation of and to test the
pipeline. We are able to detect the simulated signal with a significance of 4
standard deviations and extract the EoR parameters as and in 600 hours,
assuming that systematic errors can be adequately controlled. We further show
that the significance of detection and constraints on EoR parameters can be
improved by measuring the cross-variance of the signal by cross-correlating
consecutive redshift bins.Comment: 13 pages, 14 figures, Accepted for publication in MNRA
Component separation methods for the Planck mission
The Planck satellite will map the full sky at nine frequencies from 30 to 857
GHz. The CMB intensity and polarization that are its prime targets are
contaminated by foreground emission. The goal of this paper is to compare
proposed methods for separating CMB from foregrounds based on their different
spectral and spatial characteristics, and to separate the foregrounds into
components of different physical origin. A component separation challenge has
been organized, based on a set of realistically complex simulations of sky
emission. Several methods including those based on internal template
subtraction, maximum entropy method, parametric method, spatial and harmonic
cross correlation methods, and independent component analysis have been tested.
Different methods proved to be effective in cleaning the CMB maps from
foreground contamination, in reconstructing maps of diffuse Galactic emissions,
and in detecting point sources and thermal Sunyaev-Zeldovich signals. The power
spectrum of the residuals is, on the largest scales, four orders of magnitude
lower than that of the input Galaxy power spectrum at the foreground minimum.
The CMB power spectrum was accurately recovered up to the sixth acoustic peak.
The point source detection limit reaches 100 mJy, and about 2300 clusters are
detected via the thermal SZ effect on two thirds of the sky. We have found that
no single method performs best for all scientific objectives. We foresee that
the final component separation pipeline for Planck will involve a combination
of methods and iterations between processing steps targeted at different
objectives such as diffuse component separation, spectral estimation and
compact source extraction.Comment: Matches version accepted by A&A. A version with high resolution
figures is available at http://people.sissa.it/~leach/compsepcomp.pd
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