NDLI: Volume visualization for out-of-core 3D images based on semi-adaptive partitioning

Content Provider	IEEE Xplore Digital Library
Author	Jian Xue Ke Lii
Copyright Year	2015
Abstract	Volume rendering techniques have been used widely for high quality visualization of 3D datasets, especially 3D images. However, when rendering very large (out-of-core) datasets, some traditional in-core volume rendering algorithms do not work due to the impossibility of fitting the entire input data in the main memory of a computer. Their simple out-of-core versions do not perform well either because of the slow speed external memory access overhead. In order to solve this problem, a semi-adaptive partitioning strategy and an efficient out-of-core volume rendering method based on it are proposed in this paper. By this new partitioning strategy, the out-of-core dataset is divided into small sub-blocks in different sizes, which are organized by a BSP tree. Each sub-block can be loaded into the fast texture memory of the graphics hardware and be rendered by certain volume rendering algorithm based on 3D texture. Then the final result is obtained by composing the projection images of all the sub-blocks from back to front after traveling the BSP tree according to the viewpoint position. The experimental results indicate that the new method is effective and efficient for the volume visualization of out-of-core 3D images.
Starting Page	1503
Ending Page	1507
File Size	1850366
Page Count	5
File Format	PDF
e-ISBN	9781479983391
DOI	10.1109/ICIP.2015.7351051
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-27
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Rendering (computer graphics) Three-dimensional displays Partitioning algorithms Casting Algorithm design and analysis Yttrium Computers out-of-core algorithms 3D image processing scientific visualization volume rendering
Content Type	Text
Resource Type	Article

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