University of Bergen | Faculty of Mathematics and Natural Sciences | Department of Informatics | Visualization Group
Visualization
You are here: Department of Informatics > Visualization Group > Team > Stefan Bruckner > Publications > Solteszova-2017-OFS
 Visualization
 > about
 > team & contact info
 --- >  Stefan Bruckner
 > research
 > publications
 > projects
 > teaching
 > resources
 > network
 > events
 > links

Output-Sensitive Filtering of Streaming Volume Data

Veronika Šoltészová, Åsmund Birkeland, Sergej Stoppel, Ivan Viola, Stefan Bruckner

JOURNAL ARTICLE: Computer Graphics Forum, vol. 36, no. 1, pp. 249–262, 2017. DOI: 10.1111/cgf.12799

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 artifacts 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 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.

Published

Computer Graphics Forum

Documents and Links

  • paper

Additional Media

  • Click to view
  • Click to view

BibTeX

@ARTICLE{Solteszova-2017-OFS,
  author = {Veronika \v{S}olt{\'e}szov{\'a} and {\AA}smund Birkeland and Sergej
	Stoppel and Ivan Viola and Stefan Bruckner},
  title = {Output-Sensitive Filtering of Streaming Volume Data},
  journal = {Computer Graphics Forum},
  year = {2017},
  volume = {36},
  pages = {249--262},
  number = {1},
  month = jan,
  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 artifacts 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 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.},
  doi = {10.1111/cgf.12799},
  keywords = {output-sensitive processing, volume data, filtering},
}






 Last Modified: Stefan Bruckner, 2017-08-23