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Processing of exoplanet
full field images
Farid Karioty
CoRoT Week 12/06/2005
Plan
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I. Already done:
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II. To be done:
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Masks assignment
Background windows
Offset windows
Spectrum calculations for each star after mask assignment
III. Remaining problem
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Images corrections
Stars identification
MGPDV (CoRoT Sight Geometric Model) update
PSF extraction from full field images
Photometric precision of extracted PSF
IV. Conclusion
I. EXOWIND
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Inputs:
3 full field images (equivalent exposition time is 30 min/
image)
 EXODAT extractions
 EXOBASKET
 Theoretic PSF set
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Outputs:
2 positions files of these stars for MGPDV update
 XML assignment file of the masks
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EXOWIND (IHM)
Cosmic impacts correction
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Method:
3 full field images, 30 minutes exposition each
 For each pixel of the 3 images
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Calculate the median for each pixel triplet
 If a pixel value exceeds mean value by more than 3σ, then
it is replaced by the median value of the 3 pixels
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The 3 images are summed
EMC correction (crosstalk)
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Crosstalk:
Depends of seismology channel windowing
 Scrambling on the exoplanet channel
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Correction:
Parasites positions are predictable
 Values of the different scrambling sequences are read in
prescan pixels of the full field images
 An image containing the parasites is generated &
subtracted
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Crosstalk correction
(IHM)
Offset correction
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Method:
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Calculate in prescan and overscan pixels the offset
values for each half CCD
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Subtraction of the measured offset (possibility to
choose between the value measured in the prescan
or the overscan pixels)
Offset correction
(IHM)
Gain correction
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Method:
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Reading in the BDE (calibration data base) of the
gain values for each channel
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Application of the multiplicative factor for each half
CCD
Smearing correction
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Method :
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Calculate the smearing value for each column of the
image
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Smearing subtraction
Background correction
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Methods:
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Division of the image into sub-images in which the
minimum value is taken, then interpolation back to a
2048x2048 pixels image
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Same method but the median value is used
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Convolution method: convolution of the image by an
enlarged Gaussian & fit by a 2nd degree polynomial
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Ravines : search of valleys in the image
Background correction
(IHM)
Identification of saturated stars
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Method :
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Histogram of the image => selection of the
saturation threshold
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Research in the image of saturation domains
(adjacent pixels with values greater to the chosen
saturation threshold)
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Identification of these stars (automatic identification
& manual module for the stars where a doubt
persists e.g. 2 close saturated stars)
Identification of saturated stars
(IHM)
Stars identification
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Identification of about 20 bright slightly
contaminated stars of the same spectral type
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Update of CCD position in the MGPDV
(translation & rotation)
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Identification of 100 to 500 stars (still of the
same spectral type)
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Distortion update of the MGPDV
Stars identification (2)
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Method:
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Projection of the catalogue on the CCD (selection of the
stars with these 3 parameters: mgr, contamination,
spectral type)
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For each star: calculation of the subpixel shift between
the star position on the CCD and it’s position given by the
catalogue & the MGPDV (correlation method)
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If the shift is less than a user-defined limit (depending on
the knowledge of CCD position & distortion coefficients
in the MGPDV) & if the correlation is greater to a userdefined threshold, then the star is identified
Stars identification
(IHM)
PSF extraction
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Method:
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Selection in the catalogue of the stars corresponding to
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the PSF spectral type to extract
the maximum magnitude of these “PSF stars” (MGR min = MGR sat)
the maximum contamination level of these stars
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Choice of the number of sub-domains in the image (1 extracted
PSF by sub-domain and spectral type)
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Summation of the stack of PSF stars after subpixel recentering
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Filtering by an ellipsoidal Gaussian to decrease the background
noise (residuals of the corrections, other fainter stars…)
PSF extraction (IHM)
Extracted PSF
II. Masks assignment
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Method:
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For each EXOBASKET star:
PSF fitting
 Fitted PSF = signal, remaining = noise
 Stack of images for the attribution procedure
 XML file of the masks assignments
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But: it is crucial to know precisely the PSF
III. Unsolved problem
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Photometric precision of the extracted PSF :
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Important remainders, maximum errors ≈ 20%
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Too much important imprecision for a PSF fit
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assignment quality is decreased
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A deconvolution method is being implemented
IV. Conclusion
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Images corrections: OK
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Identification of the saturated stars and of the
saturation magnitude: OK
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Identification of the stars: OK
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PSF extraction: not totally solved but the
deconvolution method seems to give better results