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

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AsiaSim 2013 (AsiaSim 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 402))

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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.

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Zhao, K., Sakamoto, N., Koyamada, K. (2013). Compression for Large-Scale Time-Varying Volume Data Using Spatio-temporal Features. In: Tan, G., Yeo, G.K., Turner, S.J., Teo, Y.M. (eds) AsiaSim 2013. AsiaSim 2013. Communications in Computer and Information Science, vol 402. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45037-2_13

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  • DOI: https://doi.org/10.1007/978-3-642-45037-2_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-45036-5

  • Online ISBN: 978-3-642-45037-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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