Real-time switching and visualization of logging attributes based on subspace learning

doi:10.1016/j.cageo.2020.104624

	Real-time switching and visualization of logging attributes based on subspace learning
	Shi, Min; Wu, Zirui; Wang, Suqin; Zhu, Dengming
	2021
发表期刊	COMPUTERS & GEOSCIENCES
ISSN	0098-3004
卷号	146 页码:11
摘要	In three-dimensional visualization, sufficient memory and computing power can ensure real-time graphics rendering. However, due to equipment and algorithm performance limitations, it is difficult to graphically present big volume data efficiently and accurately, especially for high-dimensional and large volume geological data. In this paper we propose a real-time visualization method for logging data, which combines volume data compression and fast switching algorithm. First, we introduce an adaptive sampling method for large volume of data compression. Each block of the same size is sampled according to the dispersion and the sampling density grade, after which ray casting algorithm is used to render compressed volume data. Second, aiming at the graphic presentation delay caused by the exchange of large amounts of data in internal and external memory, a fast switching algorithm(FSA) based on subspace learning is presented. The attributes with strong correlation are put into the same group, from which feature subspace are learned and a mapping model between associated attributes is established according to base vector invariance. Once we need to switch from the currently displayed attribute to another for display, only a few coefficient values in the mapping model need to be changed, reducing the amount of data exchange. Our proposed method can greatly increase the compression ratio and reduce the computing time, ensuring real-time visualization for geological data.
关键词	Geological volume data Visualization Data compression Subspace learning Data exchange
DOI	10.1016/j.cageo.2020.104624
收录类别	SCI
语种	英语
资助项目	CNPC Logging[2017ZX05019005] ; Institute of Computing Technology, Chinese Academy of Sciences[61972379] ; Institute of Hydrobiology, Chinese Academy of Sciences[YJKYYQ20190055]
WOS研究方向	Computer Science ; Geology
WOS类目	Computer Science, Interdisciplinary Applications ; Geosciences, Multidisciplinary
WOS记录号	WOS:000599845500002
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/16487
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Shi, Min
作者单位	North China Elect Power Univ, Chinese Acad Sci, Inst Comp Technol, Sch Control & Comp Engn, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Shi, Min,Wu, Zirui,Wang, Suqin,et al. Real-time switching and visualization of logging attributes based on subspace learning[J]. COMPUTERS & GEOSCIENCES,2021,146:11.
APA	Shi, Min,Wu, Zirui,Wang, Suqin,&Zhu, Dengming.(2021).Real-time switching and visualization of logging attributes based on subspace learning.COMPUTERS & GEOSCIENCES,146,11.
MLA	Shi, Min,et al."Real-time switching and visualization of logging attributes based on subspace learning".COMPUTERS & GEOSCIENCES 146(2021):11.