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Conference Paper: Efficiently rendering large volume data using texture mapping hardware

TitleEfficiently rendering large volume data using texture mapping hardware
Authors
Issue Date1999
PublisherSpringer.
Citation
Joint EUROGRAPHICS - IEEE TCCG Symposium on Visualization Proceedings, Vienna, Austria, 26-28 May 1999, p. 121-132 How to Cite?
AbstractVolume rendering with texture mapping hardware is a fast volume rendering method available on high-end workstations. However, limited texture memory often prevents the method from being used to render large volume data efficiently. In this paper, we propose a new approach to fast rendering of large volume data with texture mapping hardware. Based on a new volume-loading pipeline, the volume data is preprocessed in such a way that only the volume data that contains object voxels are loaded into texture memory and resampled for rendering. Moreover, if classification threshold is changed, our algorithm classifies and processes the raw volume data accordingly nearly in real time. Our tests show that about 40% to 60% rendering time is saved in our method for large volume data.
Persistent Identifierhttp://hdl.handle.net/10722/48433

 

DC FieldValueLanguage
dc.contributor.authorTong, Xen_HK
dc.contributor.authorWang, WPen_HK
dc.contributor.authorTsang, WWen_HK
dc.contributor.authorTang, Zen_HK
dc.date.accessioned2008-05-22T04:12:55Z-
dc.date.available2008-05-22T04:12:55Z-
dc.date.issued1999en_HK
dc.identifier.citationJoint EUROGRAPHICS - IEEE TCCG Symposium on Visualization Proceedings, Vienna, Austria, 26-28 May 1999, p. 121-132en_HK
dc.identifier.urihttp://hdl.handle.net/10722/48433-
dc.description.abstractVolume rendering with texture mapping hardware is a fast volume rendering method available on high-end workstations. However, limited texture memory often prevents the method from being used to render large volume data efficiently. In this paper, we propose a new approach to fast rendering of large volume data with texture mapping hardware. Based on a new volume-loading pipeline, the volume data is preprocessed in such a way that only the volume data that contains object voxels are loaded into texture memory and resampled for rendering. Moreover, if classification threshold is changed, our algorithm classifies and processes the raw volume data accordingly nearly in real time. Our tests show that about 40% to 60% rendering time is saved in our method for large volume data.en_HK
dc.format.extent743291 bytes-
dc.format.extent3046 bytes-
dc.format.extent3373 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherSpringer.en_HK
dc.relation.ispartofJoint EUROGRAPHICS - IEEE TCCG Symposium on Visualization Proceedings-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleEfficiently rendering large volume data using texture mapping hardwareen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailWang, WP: wenping@cs.hku.hken_HK
dc.identifier.emailTsang, WW: tsang@cs.hku.hken_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.hkuros40697-

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