Information-Guided Transfer Function Refinement

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dc.contributor.authorLuo, Shengzhouen_US
dc.contributor.authorDingliana, Johnen_US
dc.contributor.editorEric Galin and Michael Wanden_US
dc.date.accessioned2014-12-16T07:11:41Z
dc.date.available2014-12-16T07:11:41Z
dc.date.issued2014en_US
dc.description.abstractThis paper examines the methods for exploring volume data by optimization of visualization parameters. The size and complexity of the parameter space controlling the rendering process makes it challenging to generate an informative rendering. In particular, the specification of the transfer function (which is a mapping from data values to visual properties) is frequently a time-consuming and unintuitive task. We propose an information theory based approach to optimize the transfer function based on the intensity distribution of the volume data set and the ability for users to specify priority areas of importance in the resulting image in a simple and intuitive way. This optimization approach reduces the occlusion in the resulting images, and thus improves the perception of structures.en_US
dc.description.seriesinformationEurographics 2014 - Short Papersen_US
dc.identifier.issn1017-4656en_US
dc.identifier.urihttps://doi.org/10.2312/egsh.20141015en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.6.9 [Simulationen_US
dc.subjectModelingen_US
dc.subjectVisualization]en_US
dc.subjectVisualization Volume visualizationen_US
dc.titleInformation-Guided Transfer Function Refinementen_US
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