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Deblending in DESDM

Deblending in DESDM. E.Bertin (IAP). Deblending. Detecting sub-components Recovering objects from the sub-components Forthcoming developments. How sources are detected in SExtractor. 4 steps: Sky background modeling and subtraction Image filtering at the PSF scale (matched filter)

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Deblending in DESDM

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

  2. Deblending • Detecting sub-components • Recovering objects from the sub-components • Forthcoming developments DES 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 DES 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 relative pixel value x DES Munich meeting 05/2010

  5. IMCAT empircal multiscale approach Kaiser et al. 1995 DES Munich meeting 05/2010

  6. 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 •  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 DES 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 DES Munich meeting 05/2010

  8. Image segmentation in SExtractor DES 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 DES Munich meeting 05/2010

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