Efficient 1-Pass Prediction for Volume Compression

  • Nils Jensen
  • Gabriele von Voigt
  • Wolfgang Nejdl
  • Johannes Bernarding
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3540)


The aim is to compress and decompress structured volume graphics in a lossless way. Lossless compression is necessary when the original scans must be preserved. Algorithms must deliver a fair compression ratio, have low run-time and space complexity, and work numerically robust. We have developed PR0 to meet the goals. PR0 traces runs of voxels in 3D and compensates for noise in the least significant bits by way of using differential pulse-code modulation (DPCM). PR0 reduces data to 46% of the original size at best, and 54% on average. A combination of PR0 and Worst-Zip (Zip with weakest compression enabled) gives reductions of 34% at best, and 45% on average. The combination takes the same or less time than Best-Zip, and gives 13%, respectively 5%, better results. To conduct the tests, we have written a non-optimised, sequential prototype of PR0, processed CT and MRI scans of different size and content, and measured speed and compression ratio.


Execution Time Compression Ratio Lossless Compression Volume Compression Weak Compression 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Nils Jensen
    • 1
  • Gabriele von Voigt
    • 2
  • Wolfgang Nejdl
    • 1
  • Johannes Bernarding
    • 3
  1. 1.Forschungszentrum L3SUniversität HannoverHannoverGermany
  2. 2.Regionales Rechenzentrum für NiedersachsenUniversität HannoverHannoverGermany
  3. 3.Institut für Biometrie und Medizinische InformatikMedizinische Fakultät der Otto-von-Guericke Universität MagdeburgMagdeburgGermany

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