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Interactive Multiscale Tensor Reconstruction for Multiresolution Volume Visualization

Susanne K. Suter, José Antonio Iglesias Guitián, Fabio Marton, Marco Agus, Andreas Elsener, Christoph P.E. Zollikofer, M. Gopi, Enrico Gobbetti, and Renato Pajarola

2011

Abstract

Large scale and structurally complex volume datasets from high-resolution 3D imaging devices or computational simulations pose a number of technical challenges for interactive visual analysis. In this paper, we present the first integration of a multiscale volume representation based on tensor approximation within a GPU-accelerated out-of-core multiresolution rendering framework. Specific contributions include (a) a hierarchical brick-tensor decomposition approach for pre-processing large volume data, (b) a GPU accelerated tensor reconstruction implementation exploiting CUDA capabilities, and (c) an effective tensor-specific quantization strategy for reducing data transfer bandwidth and out-of-core memory footprint. Our multiscale representation allows for the extraction, analysis and display of structural features at variable spatial scales, while adaptive level-of-detail rendering methods make it possible to interactively explore large datasets within a constrained memory footprint. The quality and performance of our prototype system is evaluated on large structurally complex datasets, including gigabyte-sized micro-tomographic volumes.

Reference and download information

Susanne K. Suter, José Antonio Iglesias Guitián, Fabio Marton, Marco Agus, Andreas Elsener, Christoph P.E. Zollikofer, M. Gopi, Enrico Gobbetti, and Renato Pajarola. Interactive Multiscale Tensor Reconstruction for Multiresolution Volume Visualization. IEEE Transactions on Visualization and Computer Graphics, 2011. Proc. IEEE Visualization.

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Bibtex citation record

@Article{Suter:2011:IMT,
    author = {{Susanne K.} Suter and {Jos\'e Antonio} {Iglesias Guiti\'an} and Fabio Marton and Marco Agus and Andreas Elsener and {Christoph P.E.} Zollikofer and M. Gopi and Enrico Gobbetti and Renato Pajarola},
    title = {Interactive Multiscale Tensor Reconstruction for Multiresolution Volume Visualization},
    journal = {IEEE Transactions on Visualization and Computer Graphics},
    pages = {2135--2143},
    year = {2011},
    abstract = { Large scale and structurally complex volume datasets from high-resolution 3D imaging devices or computational simulations pose a number of technical challenges for interactive visual analysis. In this paper, we present the first integration of a multiscale volume representation based on tensor approximation within a GPU-accelerated out-of-core multiresolution rendering framework. Specific contributions include (a) a hierarchical brick-tensor decomposition approach for pre-processing large volume data, (b) a GPU accelerated tensor reconstruction implementation exploiting CUDA capabilities, and (c) an effective tensor-specific quantization strategy for reducing data transfer bandwidth and out-of-core memory footprint. Our multiscale representation allows for the extraction, analysis and display of structural features at variable spatial scales, while adaptive level-of-detail rendering methods make it possible to interactively explore large datasets within a constrained memory footprint. The quality and performance of our prototype system is evaluated on large structurally complex datasets, including gigabyte-sized micro-tomographic volumes. },
    note = {Proc. IEEE Visualization},
    url = {http://vic.crs4.it/vic/cgi-bin/bib-page.cgi?id='Suter:2011:IMT'},
}