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Green Image
Issue No. 12 - Dec. (2011 vol. 17)
ISSN: 1077-2626
pp: 2135-2143
Susanne K. Suter , University of Zurich, Switzerland
Fabio Marton , CRS4, Italy
Marco Agus , CRS4, Italy
Andreas Elsener , University of Zurich, Switzerland
Christoph P.E. Zollikofer , University of Zurich, Switzerland
M. Gopi , University of California, Irvine, USA
Enrico Gobbetti , CRS4, Italy
Renato Pajarola , University of Zurich, Switzerland
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.
GPU/CUDA, multiscale, tensor reconstruction, interactive volume visualization, multiresolution rendering.

M. Agus et al., "Interactive Multiscale Tensor Reconstruction for Multiresolution Volume Visualization," in IEEE Transactions on Visualization & Computer Graphics, vol. 17, no. , pp. 2135-2143, 2011.
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