Proceedings: GI 2014

Using stochastic sampling to create depth-of-field effect in real-time direct volume rendering

AmirAli Sharifi , Pierre Boulanger

Proceedings of Graphics Interface 2014: Montréal, Québec, Canada, 7 - 9 May 2014, 77-85

DOI 10.20380/GI2014.10

  • Bibtex

    @inproceedings{Sharifi:2014:10.20380/GI2014.10,
    author = {Sharifi, AmirAli and Boulanger, Pierre},
    title = {Using stochastic sampling to create depth-of-field effect in real-time direct volume rendering},
    booktitle = {Proceedings of Graphics Interface 2014},
    series = {GI 2014},
    year = {2014},
    issn = {0713-5424},
    isbn = {978-1-4822-6003-8},
    location = {Montr{\'e}al, Qu{\'e}bec, Canada},
    pages = {77--85},
    numpages = {9},
    doi = {10.20380/GI2014.10},
    publisher = {Canadian Human-Computer Communications Society},
    address = {Toronto, Ontario, Canada},
    }

Abstract

Real-time visualization of volumetric data is increasingly used by physicians and scientists. Enhanced depth perception in Direct Volume Rendering (DVR) plays a crucial role in applications such as clinical decision making. Our goal is to devise a flexible blurring method in DVR and ultimately improve depth perception in real-time DVR using synthetic depth of field (DoF) effect. We devised a permutation-based stochastic sampling method for ray casting to render images with DoF effect. Our method uses 2D blurring kernels in 3D space for each sample on a ray. Furthermore, we reduce the number of required samples for each kernel of size n2 from n2 to only 2 samples. This method is flexible and can be used for DoF, focus-context blurring, selective blurring, and potentially for other photographic effects such as the tilt effect.