Experimental Astronomy

, Volume 39, Issue 3, pp 495–512 | Cite as

Astronomical context coder for image compression

  • Petr PataEmail author
  • Jaromir Schindler


Recent lossless still image compression formats are powerful tools for compression of all kind of common images (pictures, text, schemes, etc.). Generally, the performance of a compression algorithm depends on its ability to anticipate the image function of the processed image. In other words, a compression algorithm to be successful, it has to take perfectly the advantage of coded image properties. Astronomical data form a special class of images and they have, among general image properties, also some specific characteristics which are unique. If a new coder is able to correctly use the knowledge of these special properties it should lead to its superior performance on this specific class of images at least in terms of the compression ratio. In this work, the novel lossless astronomical image data compression method will be presented. The achievable compression ratio of this new coder will be compared to theoretical lossless compression limit and also to the recent compression standards of the astronomy and general multimedia.


Image compression in astronomy Lossless technique Image context model RICE HCOMPRESS JPEG2000 



The work has been supported by the grant No. 14-25251S “Nonlinear imaging systems with spatially variant point spread function” of the Czech Science Foundation.


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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Faculty of Electrical EngineeringCzech Technical University in PraguePrague 6Czech Republic

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