1999
DOI: 10.1051/aas:1999281
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Faint source detection in ISOCAM images

Abstract: 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 patter… Show more

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Cited by 42 publications
(37 citation statements)
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References 13 publications
(19 reference statements)
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“…The Pattern Recognition Technique for ISOCAM data (PRETI) by Starck et al (1999) decomposes the signal at different time scales and models the parts of the signal below and over the median level. Then, it recognizes patterns which are similar to sources and subtract the other parts from the original signal.…”
Section: The Methodsmentioning
confidence: 99%
“…The Pattern Recognition Technique for ISOCAM data (PRETI) by Starck et al (1999) decomposes the signal at different time scales and models the parts of the signal below and over the median level. Then, it recognizes patterns which are similar to sources and subtract the other parts from the original signal.…”
Section: The Methodsmentioning
confidence: 99%
“…Lémonon et al (1998) reported results obtained from a shallower raster over A2390. Both groups used the reduction method called PRETI, described in Starck et al (1999). Barvainis et al (1999) reported CAM photometry of sources in the field of Abell 2218.…”
Section: Figmentioning
confidence: 99%
“…Methods and applications of ISOCAM data analysis directed at the extraction of the faintest sources have been described by Lari et al (2001), Starck et al (1999), Aussel et al (1999a) and Elbaz et al (1998).…”
Section: General Remarksmentioning
confidence: 99%
“…Wavelet decomposition, e.g. for ISOCAM by Starck et al (1999), is not easily implementable because of the poor spatial dynamics of our maps ("big pixels and small maps"). To overcome these difficulties we have developed the following method by combining some well-known techniques for source extraction and flux determination:…”
Section: Source Extractionmentioning
confidence: 99%