Abstract
2D image space methods are processing methods applied after the volumetric data are projected and rendered into the 2D image space, such as 2D filtering, tone mapping and compositing. In the application domain of volume visualization, most 2D image space methods can be carried out more efficiently than their 3D counterparts. Most importantly, 2D image space methods can be used to enhance volume visualization quality when applied together with volume rendering methods. In this paper, we present and discuss the applications of a series of 2D image space methods as enhancements to confocal microscopy visualizations, including 2D tone mapping, 2D compositing, and 2D color mapping. These methods are easily integrated with our existing confocal visualization tool, FluoRender, and the outcome is a full-featured visualization system that meets neurobiologists' demands for qualitative analysis of confocal microscopy data.
Keywords
VisualizationVolume renderingCompositingComputer scienceComputer visionConfocalArtificial intelligenceImage processingRendering (computer graphics)Data visualizationInformation visualizationComputer graphics (images)Confocal microscopyVolume (thermodynamics)MicroscopyImage (mathematics)OpticsPhysics
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Publication Info
- Year
- 2012
- Type
- article
- Pages
- 201-208
- Citations
- 132
- Access
- Closed
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Cite This
Yong Wan,
Hideo Otsuna,
Chi-Bin Chien
et al.
(2012).
FluoRender: An application of 2D image space methods for 3D and 4D confocal microscopy data visualization in neurobiology research.
, 201-208.
https://doi.org/10.1109/pacificvis.2012.6183592
Identifiers
- DOI
- 10.1109/pacificvis.2012.6183592