Faint source detection in ISOCAM images

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Abstract
We present a tool adapted to the detection of faint mid-infrared sources within ISOCAM mosaics. This tool is based on a wavelet analysis which allows us to discriminate sources from cosmic ray impacts at the very limit of the instrument, four orders of magnitudes below IRAS. It is called PRETI for Pattern REcognition Technique for ISOCAM data, because glitches with transient behaviors are isolated in the wavelet space, i.e. frequency space, where they present peculiar signatures in the form of patterns automatically identified and then reconstructed. We have tested PRETI with Monte-Carlo simulations of fake ISOCAM data. These simulations allowed us to define the fraction of remaining false sources due to cosmic rays, the sensitivity and completeness limits as well as the photometric accuracy as a function of the observation parameters. Although the main scientific applications of this technique have appeared or will appear in separated papers, we present here an application to the ISOCAM-Hubble Deep Field image. This work completes and confirms the results already published (Aussel et al. 1999).

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