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Astron. Astrophys. Suppl. Ser. 136, 579-590

Astronomical image compression

M. Louys1,2 - J.L. Starck3 - S. Mei1,4 - F. Bonnarel1 - F. Murtagh1,5

1 - Observatoire de Strasbourg, Université Louis Pasteur, F-67000 Strasbourg, France
2 - Laboratoire des Sciences de l'Informatique, de l'Image et de la Télédétection, ENSPS, Université Louis Pasteur,
F-67000 Strasbourg, France
3 - DAPNIA/SEI-SAP, CEA-Saclay, F-91191 Gif-sur-Yvette Cedex, France
4 - European Southern Observatory, Karl-Schwarzschild-Straße 2, D-85748 Garching, Germany
5 - School of Computer Science, The Queen's University of Belfast, Belfast BT7 1NN, Northern Ireland

Received December 14, 1998; accepted February 8, 1999


We compare a range of powerful compression methods - fractal, wavelets, pyramidal median, JPEG - with compression tools dedicated to astronomy such as HCOMPRESS, FITSPRESS and Mathematical Morphology, and apply these to astronomical images. Quality is quantified from visual appearance, and from photometric and astrometric measurements. Computational requirements of each method are discussed. We also review the implications of Web-based storage and transmission, stressing what we term progressive vision. In summary, no method is perfect, but the PMT method is the best compromise for general astronomical images, combining acceptable photometric and positional precision with good compression capabilities. JPEG is still an excellent method for compression factors less than 40 and has the advantage of being very widely available.

Key words: data analysis -- image processing -- astronomical data bases: miscellaneous

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