@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",
number = "1",
pages = "249--262",
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.",
pdf = "pdfs/Solteszova-2017-OFS.pdf",
images = "images/Solteszova-2017-OFS.jpg",
thumbnails = "images/Solteszova-2017-OFS.png",
youtube = "https://www.youtube.com/watch?v=xGPs560ttp0",
doi = "10.1111/cgf.12799",
keywords = "output-sensitive processing, volume data, filtering"
}