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Proceedings Paper

Analysis of multiband astronomical images using multiscale tools
Author(s): Albert Bijaoui; Anaïs Guennec; Christophe Benoist; Eric Slezak
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Paper Abstract

Many regions of the sky are currently being observed with a high number of spectral bands with various instruments and this trend shall develop considerably in the coming years. Even with few wavelength-bands, it is not easy to match the objects identified in each individual image, or to get consistent measurements and classify them spectrally. A detection based on fusion images is proposed. Different algorithms are tested for building such an image. The best results in terms of object detection are obtained from those involving a deconvolution with a wavelet approach. Another way to sort the pixels of astronomical images into a coherent set of physical sources is to classify them following some basic assumptions. The main difficulty comes from the fact that astronomical sources fill a multidimensional continuum of spectral classes leading to a significant color classes increase with the number of bands. The pixels spectral behaviour is assumed here to be a superimposition of several pure elements. The resulting mixing categories define a set of intermediate classes, and the application of the matching pursuit algorithm allows then to get class percentages, providing very promising results for the analysis of multi-wavelength astronomical images.

Paper Details

Date Published: 7 November 2005
PDF: 12 pages
Proc. SPIE 6001, Wavelet Applications in Industrial Processing III, 600101 (7 November 2005); doi: 10.1117/12.629697
Show Author Affiliations
Albert Bijaoui, Observatoire de la Côte d'Azur (France)
Anaïs Guennec, Observatoire de la Côte d'Azur (France)
Christophe Benoist, Observatoire de la Côte d'Azur (France)
Eric Slezak, Observatoire de la Côte d'Azur (France)

Published in SPIE Proceedings Vol. 6001:
Wavelet Applications in Industrial Processing III
Frederic Truchetet; Olivier Laligant, Editor(s)

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