1998
Ahrens, James; Painter, James
Efficient sort-last rendering using compression-based image compositing Proceedings Article
In: Proceedings of the 2nd Eurographics Workshop on Parallel Graphics and Visualization, pp. 145–151, Citeseer 1998, (LA-UR-98-2968).
Abstract | Links | BibTeX | Tags: image compositing, sort-last rendering
@inproceedings{ahrens1998efficient,
title = {Efficient sort-last rendering using compression-based image compositing},
author = {James Ahrens and James Painter},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/06/EfficientSort-LastRenderingUsingCompression-BasedImageCompositing.pdf},
year = {1998},
date = {1998-01-01},
booktitle = {Proceedings of the 2nd Eurographics Workshop on Parallel Graphics and Visualization},
pages = {145--151},
organization = {Citeseer},
abstract = {State of the art scientific simulations are currently working with data set sizes on the order of a billion cells. Parallel rendering is a promising approach for interactively visualizing multiple isosurface variables from data sets of this magnitude. In sort-last rendering, each processor creates a depth buffered image of its assigned objects. All processors’ images are composited together to create a final result. Improving the efficiency of this compositing step is key to interactive parallel rendering. This paper presents a compression-based image compositing algorithm which can provide significant savings in both communication and compositing costs.},
note = {LA-UR-98-2968},
keywords = {image compositing, sort-last rendering},
pubstate = {published},
tppubtype = {inproceedings}
}
State of the art scientific simulations are currently working with data set sizes on the order of a billion cells. Parallel rendering is a promising approach for interactively visualizing multiple isosurface variables from data sets of this magnitude. In sort-last rendering, each processor creates a depth buffered image of its assigned objects. All processors’ images are composited together to create a final result. Improving the efficiency of this compositing step is key to interactive parallel rendering. This paper presents a compression-based image compositing algorithm which can provide significant savings in both communication and compositing costs.
: . .
1.
Ahrens, James; Painter, James
Efficient sort-last rendering using compression-based image compositing Proceedings Article
In: Proceedings of the 2nd Eurographics Workshop on Parallel Graphics and Visualization, pp. 145–151, Citeseer 1998, (LA-UR-98-2968).
@inproceedings{ahrens1998efficient,
title = {Efficient sort-last rendering using compression-based image compositing},
author = {James Ahrens and James Painter},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/06/EfficientSort-LastRenderingUsingCompression-BasedImageCompositing.pdf},
year = {1998},
date = {1998-01-01},
booktitle = {Proceedings of the 2nd Eurographics Workshop on Parallel Graphics and Visualization},
pages = {145--151},
organization = {Citeseer},
abstract = {State of the art scientific simulations are currently working with data set sizes on the order of a billion cells. Parallel rendering is a promising approach for interactively visualizing multiple isosurface variables from data sets of this magnitude. In sort-last rendering, each processor creates a depth buffered image of its assigned objects. All processors’ images are composited together to create a final result. Improving the efficiency of this compositing step is key to interactive parallel rendering. This paper presents a compression-based image compositing algorithm which can provide significant savings in both communication and compositing costs.},
note = {LA-UR-98-2968},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
State of the art scientific simulations are currently working with data set sizes on the order of a billion cells. Parallel rendering is a promising approach for interactively visualizing multiple isosurface variables from data sets of this magnitude. In sort-last rendering, each processor creates a depth buffered image of its assigned objects. All processors’ images are composited together to create a final result. Improving the efficiency of this compositing step is key to interactive parallel rendering. This paper presents a compression-based image compositing algorithm which can provide significant savings in both communication and compositing costs.