Using THELI pipeline in order to reduce Abell 226 multi-band optical images
In this paper we review THELI (Erben & Schrimer, 2005), an image processing pipeline developed to reduce multipointing optical images taken by mosaic CCD cameras. This pipeline works on raw images by removing several instrumental contaminations, implementing photometric calibration and astrometr...
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Головна астрономічна обсерваторія НАН України
2013
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| Цитувати: | Using THELI pipeline in order to reduce Abell 226 multi-band optical images / R. Joveini, S. Sotoudeh, A. Roozrokh, M. Taheri // Advances in Astronomy and Space Physics. — 2013. — Т. 3., вип. 1. — С. 38-41. — Бібліогр.: 7 назв. — англ. |
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Digital Library of Periodicals of National Academy of Sciences of Ukraine| id |
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irk-123456789-1194242017-06-07T03:05:29Z Using THELI pipeline in order to reduce Abell 226 multi-band optical images Joveini, R. Sotoudeh, S. Roozrokh, A. Taheri, M. In this paper we review THELI (Erben & Schrimer, 2005), an image processing pipeline developed to reduce multipointing optical images taken by mosaic CCD cameras. This pipeline works on raw images by removing several instrumental contaminations, implementing photometric calibration and astrometric alignment, and constructing a deep co-added mosaic image complemented by a weight map. We demonstrate the procedure of reducing NGC 3923 images from raw data to the final results. We also demonstrate the quality of our data reduction strategy using mag-count and mag-error in mag plots. Emphasis is mainly placed on photometric calibration which is of great interest to us due to our scientific case. Based on the cross-association of the extracted catalogue against a reference catalogue of stellar magnitudes, zero-point calibration is performed. Our data reduction strategy and the method employed for cross-correlating large catalogues is also presented. 2013 Article Using THELI pipeline in order to reduce Abell 226 multi-band optical images / R. Joveini, S. Sotoudeh, A. Roozrokh, M. Taheri // Advances in Astronomy and Space Physics. — 2013. — Т. 3., вип. 1. — С. 38-41. — Бібліогр.: 7 назв. — англ. 2227-1481 http://dspace.nbuv.gov.ua/handle/123456789/119424 en Advances in Astronomy and Space Physics Головна астрономічна обсерваторія НАН України |
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Digital Library of Periodicals of National Academy of Sciences of Ukraine |
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English |
| description |
In this paper we review THELI (Erben & Schrimer, 2005), an image processing pipeline developed to reduce multipointing optical images taken by mosaic CCD cameras. This pipeline works on raw images by removing several instrumental contaminations, implementing photometric calibration and astrometric alignment, and constructing a
deep co-added mosaic image complemented by a weight map. We demonstrate the procedure of reducing NGC 3923 images from raw data to the final results. We also demonstrate the quality of our data reduction strategy using mag-count and mag-error in mag plots. Emphasis is mainly placed on photometric calibration which is of great interest to us due to our scientific case. Based on the cross-association of the extracted catalogue against a reference catalogue of stellar magnitudes, zero-point calibration is performed. Our data reduction strategy and the method employed for cross-correlating large catalogues is also presented. |
| format |
Article |
| author |
Joveini, R. Sotoudeh, S. Roozrokh, A. Taheri, M. |
| spellingShingle |
Joveini, R. Sotoudeh, S. Roozrokh, A. Taheri, M. Using THELI pipeline in order to reduce Abell 226 multi-band optical images Advances in Astronomy and Space Physics |
| author_facet |
Joveini, R. Sotoudeh, S. Roozrokh, A. Taheri, M. |
| author_sort |
Joveini, R. |
| title |
Using THELI pipeline in order to reduce Abell 226 multi-band optical images |
| title_short |
Using THELI pipeline in order to reduce Abell 226 multi-band optical images |
| title_full |
Using THELI pipeline in order to reduce Abell 226 multi-band optical images |
| title_fullStr |
Using THELI pipeline in order to reduce Abell 226 multi-band optical images |
| title_full_unstemmed |
Using THELI pipeline in order to reduce Abell 226 multi-band optical images |
| title_sort |
using theli pipeline in order to reduce abell 226 multi-band optical images |
| publisher |
Головна астрономічна обсерваторія НАН України |
| publishDate |
2013 |
| url |
http://dspace.nbuv.gov.ua/handle/123456789/119424 |
| citation_txt |
Using THELI pipeline in order to reduce Abell 226 multi-band optical images / R. Joveini, S. Sotoudeh, A. Roozrokh, M. Taheri // Advances in Astronomy and Space Physics. — 2013. — Т. 3., вип. 1. — С. 38-41. — Бібліогр.: 7 назв. — англ. |
| series |
Advances in Astronomy and Space Physics |
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2025-07-08T15:51:04Z |
| last_indexed |
2025-07-08T15:51:04Z |
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| fulltext |
Using THELI pipeline in order to reduce Abell 226
multi-band optical images
R. Joveini1,2∗, S. Sotoudeh1,2, A. Roozrokh2,3, M. Taheri1
Advances in Astronomy and Space Physics, 3, 38-41 (2013)
© R. Joveini, S. Sotoudeh, A.Roozrokh, M.Taheri, 2013
1Physics Department, Sharif University of Technology, Azadi Ave., Tehran, Iran
2School of Astronomy, Institute for Research in Fundamental Sciences, Opposite Araj, Artesh Highway, Tehran, Iran
3Physics and Astronomy Department, University of California Riverside, 900 University Ave., Riverside, CA 92521, USA
In this paper we review THELI (Erben & Schrimer, 2005), an image processing pipeline developed to reduce multi-
pointing optical images taken by mosaic CCD cameras. This pipeline works on raw images by removing several
instrumental contaminations, implementing photometric calibration and astrometric alignment, and constructing a
deep co-added mosaic image complemented by a weight map. We demonstrate the procedure of reducing NGC3923
images from raw data to the �nal results. We also demonstrate the quality of our data reduction strategy using
mag-count and mag-error in mag plots. Emphasis is mainly placed on photometric calibration which is of great
interest to us due to our scienti�c case. Based on the cross-association of the extracted catalogue against a reference
catalogue of stellar magnitudes, zero-point calibration is performed. Our data reduction strategy and the method
employed for cross-correlating large catalogues is also presented.
Key words: methods: data analysis � techniques: image processing
introduction
In astronomy, raw CCD images from telescopes
cannot be directly used for scienti�c purposes.
Firstly, several instrumental e�ects must be re-
moved. Generally speaking, data reduction is the
transformation of raw data into a form suitable for
analysis. The following processes are required to
achieve this goal:
� removal of instrumental signatures, such as bias
o�set, dark currents, �eld curvature (caused by
projecting the spherical sky onto a �at CCD
plane), and fringe patterns;
� masking of unwanted signals, such as cosmic
rays, stellar halos and satellite tracks;
� photometric and astrometric calibration;
� co-addition of individual frames.
The THELI (Transforming HEavenly Light into Im-
age)1 pipeline was initially developed for WFI cam-
eras (it consists of 8 CCD chips of 2k×4k each)2
mounted on the ESO 2.2 meter Max Planck tele-
scope. It has a modular design allowing it to be
adapted to other single- or multi-chip cameras with
considerable ease.
The primary goal of developing the THELI pipeline
was to reduce weak lensing data; therefore, more em-
phasis was laid on the accurate alignment of galaxies
for each exposure (precise astrometry, rather than
photometry), acquiring the highest possible resolu-
tion and accurate noise mapping.
Through the course of the data reduction process
the THELI pipeline uses well-tested astronomical soft-
ware. This allows for easy exchange whenever a new
algorithm or a better implementation becomes avail-
able. The preliminary tools in the THELI pipeline
are the LDAC3 software [5], the TERAPIX software [4],
Eclipse and qfits tools4 and IMCAT utilities5.
Next, the processing a set of optical images in
the ESO bands B, R, and I is described. Our ini-
tial data set consisted of 30 Gigabytes of raw expo-
sures: SCIENCE frames of 7 di�erent galaxy groups
and calibration frames taken in 3 successive nights
with WFI at ESO 2.2m6. Prior to the reduction
procedure all objects are treated in the same man-
ner, i. e. we suppose the same calibration frames for
all of the SCIENCE frames.
∗joveini@physics.sharif.edu
1to be obtained from http://astro.uni-bonn.de/~mischa/theli.html
2for more information, see: http://www.eso.org/sci/facilities/lasilla/instruments/wfi/index.html
3Leiden Data Analysis Center, available at: ftp://ftp.strw.leidenuniv.nl/pub/ldac/software
4available at: http://www.eso.org/projects/aot/eclipse
5http://www.ifa.hawaii.edu/~kaiser/imcat/
6ESO Programme ID of the observations: 077.A-0747(A) on April 4, 2006
38
Advances in Astronomy and Space Physics R. Joveini, S. Sotoudeh, A.Roozrokh, M.Taheri
pre-reduction
Algorithms in the pipeline which remove instru-
ment e�ects (such as bad CCD pixels and fringe pat-
terns) and which can be considered constant dur-
ing the period of our observation (3 nights), are de-
scribed further.
Firstly, each �le's header is updated with the nec-
essary keywords for the pipeline. The image is then
divided into the number of chips in the CCD (which
constitutes 8 CCD chips in a WFI mosaic). From
this step on, the pipeline works on individual chips
rather than whole images, thereby enhancing the
speed and enabling us to do multi-chip processing
on multi CPUs.
bias and dark frame
In the �rst step, following a preliminary inspec-
tion of all exposures of a given type (bias, �at �eld),
the pipeline identi�es a typical count level and re-
jects outliers, e. g. DARKs with too-short exposure
time or over-saturated SKYFLATs. The acceptable
range is de�ned by the user. Since ESO WFI is con-
stantly cooled to a stable temperature of 167K [7]
and dark current is negligible, many observers do
not take DARK frames. We will describe their usage
when appropriate, however it should be noted that
we have not had or processed DARK frames.
Each frame is overscan-corrected (OC) and
trimmed: overscan region is trimmed o� the image.
Master BIAS and master DARK frames are created by
(median or arithmetic) averaging of individual BIAS
and DARK frames. The pipeline uses master DARK to
identify bad pixels.
flat-field pattern
In general, the sensitivity and the illumination of
a CCD is not homogeneous. Sensitivity can change
from pixel to pixel, while the shift in illumination
is considerable only at larger scales of distance. To
make surface brightness homogeneous, we utilise a
�at-�eld pattern. Due to the dependence of the
�ux of radiation of astronomical objects and the sky
background on the �lter used, the tasks described
below need to be carried out separately for each �l-
ter.
manual inspection, mask creation
An 8×8 binned mosaic of corrected SCIENCE
frames is created to check the run process. At this
stage, we looked at binned mosaics to check if pre-
reduction was performed correctly. Using DS9 soft-
ware, we manually omitted out-of-focus data, and
masked extended defects like satellite tracks and
bright star re�ections.
creating weight frames
The pipeline creates a weight frame for each
SCIENCE frame. Hot/cold pixels are detected by
studying the master DARK, saturated pixels are iden-
ti�ed by thresholding the SCIENCE frames; cosmic
rays are discovered by SExtractor [3] in connection
with EyE [1], and manual masks are added using the
LDAC utilities.
Global Weight and Flag frames are made for each
CCD chip. Flag frames are integer FITS in which 0
denotes good pixels and every other value denotes a
certain defect. The values are used when producing
weights. Global Weights contain information about
bad pixels of all images from that chip.
reduction
We group SCIENCE frames into sets, depending
on the objects they contain. Our pointings are:
HCG48, HCG62, HCG67, NGC3557, NGC3923,
NGC4697 and RX-J2114.3-6800. We run the reduc-
tion process on each pointing and subsequently add
the reduced individual frames.
astrometery
The initial step in astrometery is to detect high
S/N objects using SExtractor and to generate a cat-
alogue of non-saturated stars. By comparing this
catalogue to the USNO-B1 catalogue, a zero-order,
single shift astrometric solution is calculated for each
image. The CCDs in multi-chip cameras can be ro-
tated unintentionally with respect to each other. In
addition, due to a large �eld of view, the sky must
be considered to be a spherically curved surface.
The next step is to estimate third-order polyno-
mials for the astrometric solution for each chip, using
the SCamp package [2] developed by TERAPIX.
photometry
Exposures are taken under varying conditions:
parameters such as airmass and background radia-
tion di�er from one night of observation to another.
Therefore, during the �rst part of photometric cali-
bration, images should be calibrated relatively. This
is done by the LDAC relphotpm program. Relphotom
takes tables of overlapping exposures as input and
calculates the mean deviation of magnitudes:
Mk,j =
∑
i
(
σ2
K + σ2
J
)−1
(MKi
−MJi
)∑
i
(
σ2
K + σ2
J
)−1 , (1)
where K and J (K 6= J) are �elds, i denotes objects
present in both exposures, and σ are measurement
errors of the magnitude, and �nds the relative zero
point magnitude by χ2 minimisation:
χ2 =
N∑
k,j
[Mk,j − (ZPk − ZPj)]
2 . (2)
In this case we neglect variant photometric condi-
tions which a�ect each spectral type in a di�erent
way.
39
Advances in Astronomy and Space Physics R. Joveini, S. Sotoudeh, A.Roozrokh, M.Taheri
co-addition
preparation for co-adding
Sky background is calculated using SExtractor
BACKGROUND check image for every large-object-
subtracted frame, and is subtracted from all SCIENCE
images. A re-sampled image is made using the astro-
metric solution polynomials calculated in astrometry
step and stored in each chip's header.
co-addition of individual frames
THELI o�ers two tools for image co-adding: SWarp
and EIS Drizzle. Our tool of choice is the former.
Using all input images (which are related to a sin-
gle output pixel) in our sample, SWarp calculates the
�nal results using the weighted mean method.
A WEIGHT image is also produced, as well as a
FLAG image. WEIGHT image plays a key role in source
detection of the �nal image [6], for a comparison be-
tween weighted and un-weighted source detection.
our method of catalogue
cross association
As described above, we need to match object in-
formation from di�erent channels. Generally there
are two cases when it is necessary to consult two or
more catalogues:
1. When there is given a catalogue in a particular
�lter and it is desired to cross-match it with a
reference catalogue, like a Standard Star Mag-
nitude catalogue.
2. When there are multiple observations of a
source in di�erent �lters. In this case, one needs
to deal with multiple channels (in our case: B,
R and I).
Since SExtractor's detection is not perfect in terms
of source coordinates, one has to take one cata-
logue as a reference catalogue and treat the others
as search catalogues; therefore, for each object in a
certain channel, information from the other channels
will be found and added, as to make a �matched and
merged� catalogue.
results and qualifications
With the �nal COADD images along with their
WEIGHTs in hand in B, R and I �lters, one would pro-
duce several plots to show the quali�cation of data
reduction. Throughout this, two of them are very
important: mag-count histogram and mag-error in
mag scatter plot. As shown in Fig. 1 we have plot-
ted the mag-count histogram for NGC3923 �eld of
galaxies (note that stars have been separated from
galaxies using SExtractor's CLASS_STAR parameter
larger than 0.95 as a criteria. Seven outliers have
been removed, since they were only round-shaped
galaxies). As seen, the count drops from magnitude
22.5; this is called completeness limit. It shows that
our data obtained with this instrument is trustwor-
thy up to this completeness limit (note that the count
should be raised with respect to the fainter objects).
Fig. 1: Quali�cation plot for NGC3923 image reduction:
galaxy count histogram for NGC3923 �eld.
Fig. 2: Quali�cation plot for NGC3 923 image reduction:
galaxy magnitude error scatter plot for NGC3923 �eld.
The other plot, which is important in astronom-
ical data reduction, is the mag-error in mag scatter
plot as we showed in Fig. 2. This plot reveals which
data is trustworthy and which data is not based on
our scienti�c goal. It demonstrates that for objects
with magnitude around 22.5 the error in magnitudes
increase very fast; therefore objects fainter than 22.5
are not suitable for this kind of investigation.
As a fundamental parameter in astronomy pho-
tometric data, seeing7 associated with the individual
pointings (in R band) ranged from 0.75 to 1.1 arc-
sec, and the average seeing of the co-added image
has been measured to be 0.89 arcsec.7calculated using FWHM in an area around image centre
40
Advances in Astronomy and Space Physics R. Joveini, S. Sotoudeh, A.Roozrokh, M.Taheri
acknowledgement
The authors acknowledge IPM for providing
computational facilities and also appreciate Reza
Mansouri, Habib G. Khosroshahi and Alireza Mo-
laeinezhad for useful discussions and guidance.
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[2] BertinE. 2006, ASP Conf. Series, 351, 112
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