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Hierarchical Exploration of Volumes Using Multilevel Segmentation of the Intensity-Gradient Histograms
Dec. 2012 (vol. 18 no. 12)
pp. 2355-2363
Cheuk Yiu Ip, Inst. for Adv. Comput. Studies, Univ. of Maryland, College Park, MD, USA
A. Varshney, Inst. for Adv. Comput. Studies, Univ. of Maryland, College Park, MD, USA
J. JaJa, Inst. for Adv. Comput. Studies, Univ. of Maryland, College Park, MD, USA
Visual exploration of volumetric datasets to discover the embedded features and spatial structures is a challenging and tedious task. In this paper we present a semi-automatic approach to this problem that works by visually segmenting the intensity-gradient 2D histogram of a volumetric dataset into an exploration hierarchy. Our approach mimics user exploration behavior by analyzing the histogram with the normalized-cut multilevel segmentation technique. Unlike previous work in this area, our technique segments the histogram into a reasonable set of intuitive components that are mutually exclusive and collectively exhaustive. We use information-theoretic measures of the volumetric data segments to guide the exploration. This provides a data-driven coarse-to-fine hierarchy for a user to interactively navigate the volume in a meaningful manner.
Index Terms:
information theory,data visualisation,gradient methods,image segmentation,data-driven coarse-to-fine hierarchy,hierarchical volume exploration,intensity-gradient histogram,visual exploration,volumetric dataset,visual segmentation,intensity-gradient 2D histogram,exploration hierarchy,user exploration behavior,normalized-cut multilevel segmentation,histogram segmentation,information-theoretic measures,volumetric data segment,Histograms,Image segmentation,Visualization,Entropy,Transfer functions,Shape analysis,Volume measurement,Information-guided exploration,Volume exploration,volume classification,normalized cut
Citation:
Cheuk Yiu Ip, A. Varshney, J. JaJa, "Hierarchical Exploration of Volumes Using Multilevel Segmentation of the Intensity-Gradient Histograms," IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 12, pp. 2355-2363, Dec. 2012, doi:10.1109/TVCG.2012.231
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