caa a22 4500 605541418 CHVBK 20210128100916.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s00371-014-1026-2 doi (NATIONALLICENCE)springer-10.1007/s00371-014-1026-2 Surface carving-based automatic volume data reduction [Elektronische Daten] [Qichao Wang, Yubo Tao, Hai Lin] Many fields, such as medicine and biology, are producing an increasingly large volume using high-resolution digital imaging techniques, and this makes effective data analysis and visualization of these volumes more and more difficult. Volume reduction, decreasing the volume size, is one of the promising directions to solve this challenge for interactive volume visualization. In this paper, we present an automatic volume data reduction method called surface carving. It intelligently removes contextual voxels while preserving important features, and finally generates an optimal volume at the desired reduction size/rate. For large volume data sets, a multilevel banded method is introduced to gracefully overcome the memory limit and speed up volume reduction. We compare our technique with traditional cropping and scaling approaches and demonstrate the effectiveness and efficiency of our method with several volume data sets. Springer-Verlag Berlin Heidelberg, 2014 Automatic nationallicence Volume reduction nationallicence Surface carving nationallicence Wang Qichao State Key Lab of CAD&CG, Zhejiang University, Hangzhou, People's Republic of China aut Tao Yubo State Key Lab of CAD&CG, Zhejiang University, Hangzhou, People's Republic of China aut Lin Hai State Key Lab of CAD&CG, Zhejiang University, Hangzhou, People's Republic of China aut The Visual Computer Springer Berlin Heidelberg 31/11(2015-11-01), 1459-1470 0178-2789 31:11<1459 2015 31 371 https://doi.org/10.1007/s00371-014-1026-2 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00371-014-1026-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wang Qichao State Key Lab of CAD&CG, Zhejiang University, Hangzhou, People's Republic of China aut NATIONALLICENCE 700 1- Tao Yubo State Key Lab of CAD&CG, Zhejiang University, Hangzhou, People's Republic of China aut NATIONALLICENCE 700 1- Lin Hai State Key Lab of CAD&CG, Zhejiang University, Hangzhou, People's Republic of China aut NATIONALLICENCE 773 0- The Visual Computer Springer Berlin Heidelberg 31/11(2015-11-01), 1459-1470 0178-2789 31:11<1459 2015 31 371