TY - JOUR
T1 - Sparse PDF Volumes for Consistent Multi-Resolution Volume Rendering
AU - Sicat, Ronell Barrera
AU - Kruger, Jens
AU - Moller, Torsten
AU - Hadwiger, Markus
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2014/12/31
Y1 - 2014/12/31
N2 - This paper presents a new multi-resolution volume representation called sparse pdf volumes, which enables consistent multi-resolution volume rendering based on probability density functions (pdfs) of voxel neighborhoods. These pdfs are defined in the 4D domain jointly comprising the 3D volume and its 1D intensity range. Crucially, the computation of sparse pdf volumes exploits data coherence in 4D, resulting in a sparse representation with surprisingly low storage requirements. At run time, we dynamically apply transfer functions to the pdfs using simple and fast convolutions. Whereas standard low-pass filtering and down-sampling incur visible differences between resolution levels, the use of pdfs facilitates consistent results independent of the resolution level used. We describe the efficient out-of-core computation of large-scale sparse pdf volumes, using a novel iterative simplification procedure of a mixture of 4D Gaussians. Finally, our data structure is optimized to facilitate interactive multi-resolution volume rendering on GPUs.
AB - This paper presents a new multi-resolution volume representation called sparse pdf volumes, which enables consistent multi-resolution volume rendering based on probability density functions (pdfs) of voxel neighborhoods. These pdfs are defined in the 4D domain jointly comprising the 3D volume and its 1D intensity range. Crucially, the computation of sparse pdf volumes exploits data coherence in 4D, resulting in a sparse representation with surprisingly low storage requirements. At run time, we dynamically apply transfer functions to the pdfs using simple and fast convolutions. Whereas standard low-pass filtering and down-sampling incur visible differences between resolution levels, the use of pdfs facilitates consistent results independent of the resolution level used. We describe the efficient out-of-core computation of large-scale sparse pdf volumes, using a novel iterative simplification procedure of a mixture of 4D Gaussians. Finally, our data structure is optimized to facilitate interactive multi-resolution volume rendering on GPUs.
UR - http://hdl.handle.net/10754/556154
UR - http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6876002
UR - http://www.scopus.com/inward/record.url?scp=84910060938&partnerID=8YFLogxK
U2 - 10.1109/TVCG.2014.2346324
DO - 10.1109/TVCG.2014.2346324
M3 - Article
C2 - 26146475
SN - 1077-2626
VL - 20
SP - 2417
EP - 2426
JO - IEEE Transactions on Visualization and Computer Graphics
JF - IEEE Transactions on Visualization and Computer Graphics
IS - 12
ER -