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Compression for Large-Scale Time-Varying Volume Data Using Spatio-temporal Features

  • Kun Zhao
  • Naohisa Sakamoto
  • Koji Koyamada
Part of the Communications in Computer and Information Science book series (CCIS, volume 402)

Abstract

Data compression is always needed in large-scale time-varying volume visualization. In some recent application cases, the compression method is also required to provide a low-cost decompression process. In the present paper, we propose a compression scheme for large-scale time-varying volume data using the spatio-temporal features. With this compression scheme, we are able to provide a proper compression ratio to satisfy many system environments (even a low-spec environment) by setting proper compression parameters. After the compression, we can also provide a low-cost and fast decompression process for the compressed data. Furthermore, we implement a specialized particle-based volume rendering (PBVR) [2] to achieve an accelerated rendering process for the decompressed data. As a result, we confirm the effectiveness of our compression scheme by applying it to the large-scale time-varying turbulent combustion data.

Keywords

compression time-varying volume data visualization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Kun Zhao
    • 1
  • Naohisa Sakamoto
    • 2
  • Koji Koyamada
    • 2
  1. 1.Graduate School of EngineeringKyoto UniversityJapan
  2. 2.Institute for the Promotion of Excellence in Higher EducationKyoto UniversityJapan

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