BibTex
@inproceedings{Sharifi:2014:,
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},
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.