Hierarchical Exploration of Volumes Using Multilevel Segmentation of the Intensity-Gradient Histograms

• Published in: IEEE transactions on visualization and computer graphics Vol. 18; no. 12; pp. 2355 - 2363
• Main Authors: Cheuk Yiu Ip, Varshney, A., JaJa, J.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.12.2012; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Entropy; Exploration; Hierarchies; Histograms; Image segmentation; Information-guided exploration; Multilevel; normalized cut; Segmentation; Segments; Shape analysis; Tasks; Transfer functions; Visual; Visualization; volume classification; Volume exploration; Volume measurement
• ISSN: 1077-2626; 1941-0506
• DOI: 10.1109/TVCG.2012.231

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.