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Deblending E. BertinDES Munich meeting 05/2010 1 Deblending in DESDM E.Bertin (IAP)

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Presentation on theme: "Deblending E. BertinDES Munich meeting 05/2010 1 Deblending in DESDM E.Bertin (IAP)"— Presentation transcript:

1 Deblending E. BertinDES Munich meeting 05/2010 1 Deblending in DESDM E.Bertin (IAP)

2 Deblending E. BertinDES Munich meeting 05/2010 2 Deblending Detecting sub-components Recovering objects from the sub-components Forthcoming developments

3 Deblending E. BertinDES Munich meeting 05/2010 3 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

4 Deblending E. BertinDES Munich meeting 05/2010 4 Detecting sub-components SExtractor (or COSMOS): Multithresholding –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 x relative pixel value

5 Deblending E. BertinDES Munich meeting 05/2010 5 IMCAT empircal multiscale approach Kaiser et al. 1995

6 Deblending E. BertinDES Munich meeting 05/2010 6 Wavelet analysis Starck et al. 2000 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  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)

7 Deblending E. BertinDES Munich meeting 05/2010 7 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 Lupton 2005

8 Deblending E. BertinDES Munich meeting 05/2010 8 Image segmentation in SExtractor

9 Deblending E. BertinDES Munich meeting 05/2010 9 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

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