Deblending
Deblending in DESDM
E.Bertin (IAP)
E. Bertin
DES Munich meeting 05/2010
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Deblending
Deblending
• Detecting sub-components
• Recovering objects from the
sub-components
• Forthcoming developments
E. Bertin
DES Munich meeting 05/2010
2
Deblending
How sources are detected in SExtractor
• 4 steps:
– Sky background
modeling and
subtraction
– Image filtering at the
PSF scale (matched
filter)
– Thresholding and
image segmentation
– Merging and/or
splitting of detections
E. Bertin
DES Munich meeting 05/2010
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Deblending
Detecting sub-components
– Removal of noise
peaks based on
local constrast ratio
• Photo (or DAOPhot):
peak detection
• IMCat: multiscale
peak detection
• SExtractor _PSF
parameters: multiple
PSF fitting with
proximity constraints
relative pixel value
• SExtractor (or
COSMOS):
Multithresholding
x
E. Bertin
DES Munich meeting 05/2010
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Deblending
IMCAT empircal multiscale approach
Kaiser et al.
1995
E. Bertin
DES Munich meeting 05/2010
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Deblending
Wavelet analysis
• Extend the benefit of filtering from
point-sources to very extended objects
• Wavelet analysis: a data cube w( x,a)
is obtained by correlating the image with
the basis functions
1
x
 a ( x)   ( )
a
a
 is localized, isotropic, and has
zero mean.
•The last difficult (yet unsolved)
step is to connect the detections
done at each scale to reconstruct
the final object (Bijaoui & Rué
1995).
• pyramidal median transform is an
alternative to wavelet
decomposition (Starck et al. 1995)
Starck et al. 2000
E. Bertin
DES Munich meeting 05/2010
6
Deblending
Recovering objects
• Sextractor: 1 pixel
« belongs » to one object
only
– Pixels lying close to
boundaries are reassociated
to an object on a statistical
basis (dithering)
• Photo: flux fractions
reassociated based on fits
of « symmetrized »
templates
E. Bertin
DES Munich meeting 05/2010
Lupton 2005
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Deblending
Image segmentation in SExtractor
E. Bertin
DES Munich meeting 05/2010
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Deblending
Suggested improvements
• Drop the assumption: 1 source per pixel
– Still looking for a way to do that in the cleanest way
– Allow to do multiple source fits?
• Try to deblend source blends that show no saddle in their
profiles?
• Multichannel deblending?
• Metrics to measure deblending performance?
– Cluster simulation in SkyMaker
E. Bertin
DES Munich meeting 05/2010
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