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Interactive level-of-detail selection using image-based quality metric for large volume visualization.
IEEE Trans Vis Comput Graph. 2007 Jan-Feb; 13(1):122-34.IT

Abstract

For large volume visualization, an image-based quality metric is difficult to incorporate for level-of-detail selection and rendering without sacrificing the interactivity. This is because it is usually time-consuming to update view-dependent information as well as to adjust to transfer function changes. In this paper, we introduce an image-based level-of-detail selection algorithm for interactive visualization of large volumetric data. The design of our quality metric is based on an efficient way to evaluate the contribution of multiresolution data blocks to the final image. To ensure real-time update of the quality metric and interactive level-of-detail decisions, we propose a summary table scheme in response to runtime transfer function changes and a GPU-based solution for visibility estimation. Experimental results on large scientific and medical data sets demonstrate the effectiveness and efficiency of our algorithm.

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Authors+Show Affiliations

Wang C
Department of Computer Science and Engineering, The Ohio State University, 395 Dreese Laboratories, Columbus, OH 43210, USA. wangcha@cse.ohio-state.edu
Garcia A
No affiliation info available
Shen HW
No affiliation info available

MeSH

AlgorithmsComputer GraphicsImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalInformation Storage and RetrievalPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificityUser-Computer Interface

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

Language

eng

PubMed ID

17093341

Citation

Wang, Chaoli, et al. "Interactive Level-of-detail Selection Using Image-based Quality Metric for Large Volume Visualization." IEEE Transactions On Visualization and Computer Graphics, vol. 13, no. 1, 2007, pp. 122-34.
Wang C, Garcia A, Shen HW. Interactive level-of-detail selection using image-based quality metric for large volume visualization. IEEE Trans Vis Comput Graph. 2007;13(1):122-34.
Wang, C., Garcia, A., & Shen, H. W. (2007). Interactive level-of-detail selection using image-based quality metric for large volume visualization. IEEE Transactions On Visualization and Computer Graphics, 13(1), 122-34.
Wang C, Garcia A, Shen HW. Interactive Level-of-detail Selection Using Image-based Quality Metric for Large Volume Visualization. IEEE Trans Vis Comput Graph. 2007 Jan-Feb;13(1):122-34. PubMed PMID: 17093341.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Interactive level-of-detail selection using image-based quality metric for large volume visualization. AU - Wang,Chaoli, AU - Garcia,Antonio, AU - Shen,Han-Wei, PY - 2006/11/10/pubmed PY - 2007/2/8/medline PY - 2006/11/10/entrez SP - 122 EP - 34 JF - IEEE transactions on visualization and computer graphics JO - IEEE Trans Vis Comput Graph VL - 13 IS - 1 N2 - For large volume visualization, an image-based quality metric is difficult to incorporate for level-of-detail selection and rendering without sacrificing the interactivity. This is because it is usually time-consuming to update view-dependent information as well as to adjust to transfer function changes. In this paper, we introduce an image-based level-of-detail selection algorithm for interactive visualization of large volumetric data. The design of our quality metric is based on an efficient way to evaluate the contribution of multiresolution data blocks to the final image. To ensure real-time update of the quality metric and interactive level-of-detail decisions, we propose a summary table scheme in response to runtime transfer function changes and a GPU-based solution for visibility estimation. Experimental results on large scientific and medical data sets demonstrate the effectiveness and efficiency of our algorithm. SN - 1077-2626 UR - https://www.unboundmedicine.com/medline/citation/17093341/Interactive_level_of_detail_selection_using_image_based_quality_metric_for_large_volume_visualization_ L2 - https://doi.ieeecomputersociety.org/10.1109/TVCG.2007.15 DB - PRIME DP - Unbound Medicine ER -