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» Implementing LNS using filtering units of GPUs
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EGH
2010
Springer
13 years 5 months ago
Hardware implementation of micropolygon rasterization with motion and defocus blur
Current GPUs rasterize micropolygons (polygons approximately one pixel in size) inefficiently. Additionally, they do not natively support triangle rasterization with jittered samp...
J. S. Brunhaver, Kayvon Fatahalian, Pat Hanrahan
ICPR
2008
IEEE
14 years 1 months ago
Cellular automaton for ultra-fast watershed transform on GPU
In this paper we describe a cellular automaton (CA) used to perform the watershed transform in N-D images. Our method is based on image integration via the Ford-Bellman shortest p...
Claude Kauffmann, Nicolas Piche
VIS
2004
IEEE
186views Visualization» more  VIS 2004»
14 years 8 months ago
Hardware-Accelerated Adaptive EWA Volume Splatting
We present a hardware-accelerated adaptive EWA volume splatting algorithm. EWA splatting combines a Gaussian reconstruction kernel with a low-pass image filter for high image qual...
Wei Chen, Liu Ren, Matthias Zwicker, Hanspeter Pfi...
JCC
2010
105views more  JCC 2010»
13 years 5 months ago
PAPER - Accelerating parallel evaluations of ROCS
Abstract: Modern graphics processing units (GPUs) are flexibly programmable and have peak computational throughput significantly faster than conventional CPUs. Herein, we describ...
Imran S. Haque, Vijay S. Pande
CMPB
2010
186views more  CMPB 2010»
13 years 7 months ago
GPU-based cone beam computed tomography
The use of cone beam computed tomography (CBCT) is growing in the clinical arena due to its ability to provide 3-D information during interventions, its high diagnostic quality (su...
Peter B. Noël, Alan M. Walczak, Jinhui Xu, Ja...