article

Output-Sensitive Filtering of Streaming Volume Data

Authors:

Veronika Solteszova,

Åsmund Birkeland,

Sergej Stoppel,

Stefan BrucknerAuthors Info & Claims

Computer Graphics Forum, Volume 36, Issue 1

Pages 249 - 262

https://doi.org/10.1111/cgf.12799

Published: 01 January 2017 Publication History

Abstract

Real-time volume data acquisition poses substantial challenges for the traditional visualization pipeline where data enhancement is typically seen as a pre-processing step. In the case of 4D ultrasound data, for instance, costly processing operations to reduce noise and to remove artefacts need to be executed for every frame. To enable the use of high-quality filtering operations in such scenarios, we propose an output-sensitive approach to the visualization of streaming volume data. Our method evaluates the potential contribution of all voxels to the final image, allowing us to skip expensive processing operations that have little or no effect on the visualization. As filtering operations modify the data values which may affect the visibility, our main contribution is a fast scheme to predict their maximum effect on the final image. Our approach prioritizes filtering of voxels with high contribution to the final visualization based on a maximal permissible error per pixel. With zero permissible error, the optimized filtering will yield a result that is identical to filtering of the entire volume. We provide a thorough technical evaluation of the approach and demonstrate it on several typical scenarios that require on-the-fly processing.

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Cited By

Ballester-Ripoll RSteiner DPajarola R(2018)Multiresolution Volume Filtering in the Tensor Compressed DomainIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2017.277128224:10(2714-2727)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1109/TVCG.2017.2771282

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Published In

cover image Computer Graphics Forum

Computer Graphics Forum Volume 36, Issue 1

January 2017

346 pages

ISSN:0167-7055

EISSN:1467-8659

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The Eurographs Association & John Wiley & Sons, Ltd.

Chichester, United Kingdom

Publication History

Published: 01 January 2017

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Cited By

Ballester-Ripoll RSteiner DPajarola R(2018)Multiresolution Volume Filtering in the Tensor Compressed DomainIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2017.277128224:10(2714-2727)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1109/TVCG.2017.2771282

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