Approximate Computing of Remotely Sensed Data: SVM Hyperspectral Image Classification as a Case Study

	Approximate Computing of Remotely Sensed Data: SVM Hyperspectral Image Classification as a Case Study
	Wu, Yuanfeng 1; Yang, Xinghua 1; Plaza, Antonio 1; Qiao, Fei 1; Gao, Lianru 1; Zhang, Bing 1; Cui, Yabo 1
刊名	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
	2016
卷号	9 期号:12 页码:5806-5818
通讯作者	Gao, Lianru (gaolr@radi.ac.cn)
英文摘要	Onboard processing systems are becoming very important in remote sensing data processing. However, a main problem with specialized hardware architectures used for onboard processing is their high power consumption, which limits their exploitation in earth observation missions. In this paper, a novel strategy for approximate computing is proposed for reducing energy consumption in remotely sensed onboard processing tasks. As a case study, the implementation of support vector machine (SVM) hyperspectral image classification is considered by using the proposed approximate computing framework. Experimental results show that the proposed approximate computing scheme achieves up to 70% power savings in the kernel accumulation computation procedure with negligible degradation of classification accuracy as compared to the traditional ripple carry adder (RCA) precise computation. This is an important achievement to meet the restrictions of onboard processing scenarios. © 2016 IEEE.
收录类别	EI
语种	英语
WOS记录号	WOS:20162002376184
内容类型	期刊论文
源URL	[http://ir.radi.ac.cn/handle/183411/39623]
专题	遥感与数字地球研究所_SCI/EI期刊论文_期刊论文
作者单位	1. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 2.100094, China 3. Institute of Circuits and Systems, Department of Electronic Engineering, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing 4.100084, China 5. Hyperspectral Computing Laboratory, Department of Technology of Computers and Communications, University of Extremadura, Cáceres 6.10071, Spain
推荐引用方式 GB/T 7714	Wu, Yuanfeng,Yang, Xinghua,Plaza, Antonio,et al. Approximate Computing of Remotely Sensed Data: SVM Hyperspectral Image Classification as a Case Study[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2016,9(12):5806-5818.
APA	Wu, Yuanfeng.,Yang, Xinghua.,Plaza, Antonio.,Qiao, Fei.,Gao, Lianru.,...&Cui, Yabo.(2016).Approximate Computing of Remotely Sensed Data: SVM Hyperspectral Image Classification as a Case Study.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,9(12),5806-5818.
MLA	Wu, Yuanfeng,et al."Approximate Computing of Remotely Sensed Data: SVM Hyperspectral Image Classification as a Case Study".IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9.12(2016):5806-5818.