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Department of Physics |
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AstroLab |
Stacking Images
The combining of several images allow fainter sources to be detected and
their apparent magnitudes determined with improved precision.
stackX2.py
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Create a working directory(folder) and "change" to this directory, e.g.
> mkdir mystack
> cd mystack
It is helpful, of course, to give this directory a sensible name!
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Examine the
observing logs and select the fits images required. If necessary visually examine
the fits images with the Starlink GAIA image display tool and note the numbers of
the images that you may which to exclude from the stracking,
e.g. those with poor tracking or poor S/N.
Copy the images you would like to stack to your working directory, e.g.
> cp /mnt/archive/draco2/2024/24_01_15/d0001.fits .
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Run the python script /mnt/64bin/stackX2.py .
The syntax is:
> python /mnt/64bin/stackX2.py PSF_limit
e.g. > python /mnt/64bin/stackX2.py 5.0
will attempt to stack all d*.fits in the current directory where the PSF has FWHM<5.0.
If master_flat.fits is included in the working directory, it will be used to flat field each frame first.
If successful, an output image called "mosaic.fits "
will be produced.
This is the average of all the "d " fits images in the sequence.
In the stacking process averaging is used rather than summing to allow
for pixels with missing values.
- If this is unsuccessful, try dfstack.py3 below
dfstack.py3
We can also use the routines provided by Peter Draper's
CCDPACK
package to stack, i.e. register and average, sets of images.
A basic csh script is available that stacks of a set of
the "default" AstroLab dark-subtracted images, i.e. the
"dxxxx.fits, ... " image files.
Follow the same steps as above, but instead run:
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Run the python script
> /mnt/64bin/dfstack.py
The syntax is:
> python /mnt/64bin/dfstack.py telescope date start end
e.g. > python /mnt/64bin/dfstack.py east-14 19_01_30 140 150
If you want to exclude files in the sequence put their numbers in a file called "DONT_PROCESS".
The average of the fits header keyword DATE-OBS , i.e. the
UTC (Coordinated Universal Time) of each image, is calculated and stored in the fits header
of the output image as the DATE-OBS value. The mean
modified julian date
is also calculated and is stored as the value of the keyword
MJD-OBS .
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The script will also attempt to determine the astrometry mapping for the image,
i.e. the (x, y) pixel to (RA, Dec) mapping, from the auto identification
of UCAC4 stars.
(This image when displayed with Starlink's GAIA image display tool will give (RA, Dec) positions as well as
the (x, y) pixel positions).
If successful, an output image called "
amosaic_ucac4.fits "
will be produced.
The code will also attempt to use the ESA-GAIA star catalogue to
put an astrometry mapping on the image. If successful, an output image called "amosaic_gaia.fits "
will be produced.
Calculation of Photometric Errors in Stack Images
When undertaking aperture photometry with Starlink's
GAIA the usual defaults
calculate the photometric errors by assuming that
the input image has units of "photon" counts and
hence photon statistics are used to estimate the error.
The stacked image produced by the csh script is the "average" (rather than the summed) image
and hence GAIA's default setup parameters will give an erronous estimate
of the photometric error.
Consider the following simple case. If an object in an individual image had a total count of ∼100, then ignoring any
background/readout noise uncertainties, the statistical error would be the square root of 100, i.e. 10,
and hence a 10% error on the flux.
If nine images were used in stacking process the total count for this object would still be reported as
∼100, i.e. the images are averaged rather than summed. Now if
photon statistics were assumed the same 10% error would be calculated which is incorrect.
The stacked image effectively has 900 counts in the object and hence the statistical error
is the square root of 900, i.e. 30, and hence a 3.3% error on the flux.
In GAIA the simplest way to get approximately correct photometric errors on a stack
image is to change the "aperture photometry parameter" "Measurement errors use:"
from "photon statistics" to "sky variance". GAIA will then use the scatter in the
pixel counts in the sky annulus to estimate a reasonable "gain" factor
to use in the photometric error calculation.
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