Multiple Algorithm Integration Based on Ant Colony Optimization for Endmember Extraction From Hyperspectral Imagery

	Multiple Algorithm Integration Based on Ant Colony Optimization for Endmember Extraction From Hyperspectral Imagery
	Gao, Lianru 1; Gao, Jianwei 1; Li, Jun 1; Plaza, Antonio 1; Zhuang, Lina 1; Sun, Xu 1; Zhang, Bing 1
刊名	IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
	2015
卷号	8 期号:6(SI)页码:16091-16107
关键词	Ant colony optimization (ACO) endmember extraction hyperspectral imagery multiple algorithm integration
通讯作者	Gao, LR (reprint author), Chinese Acad Sci, Key Lab Digital Earth Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China.
英文摘要	Spectral unmixing is an important technique in hyperspectral image exploitation. It comprises the extraction of a set of pure spectral signatures (called endmembers in hyperspectral jargon) and their corresponding fractional abundances in each pixel of the scene. Over the last few years, many approaches have been proposed to automatically extract endmembers, which is a critical step of the spectral unmixing chain. Recently, ant colony optimization (ACO) techniques have reformulated the endmember extraction issue as a combinatorial optimization problem. Due to the huge computation load involved, how to provide suitable candidate endmembers for ACO is particularly important, but this aspect has never been discussed before in the literature. In this paper, we illustrate the capacity of ACO techniques for integrating the results obtained by different endmember extraction algorithms. Our experimental results, conducted using several state-of-the-art endmember extraction approaches using both simulated and a real hyperspectral scene (cuprite), indicate that the proposed ACO-based strategy can provide endmembers which are robust against noise and outliers.
研究领域[WOS]	Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000359264000023
内容类型	期刊论文
源URL	[http://ir.ceode.ac.cn/handle/183411/38176]
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.[Gao, Lianru 2.Gao, Jianwei 3.Zhuang, Lina 4.Sun, Xu 5.Zhang, Bing] Chinese Acad Sci, Key Lab Digital Earth Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China 6.[Zhuang, Lina] Univ Chinese Acad Sci, Beijing 100049, Peoples R China 7.[Li, Jun] Sun Yat Sen Univ, Guangdong Key Lab Urbanizat & Geosimulat, Sch Geog & Planning, Guangzhou 510275, Guangdong, Peoples R China 8.[Plaza, Antonio] Univ Extremadura, Hyperspectral Comp Lab, Dept Technol Comp & Commun, Caceres 10071, Spain
推荐引用方式 GB/T 7714	Gao, Lianru,Gao, Jianwei,Li, Jun,et al. Multiple Algorithm Integration Based on Ant Colony Optimization for Endmember Extraction From Hyperspectral Imagery[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2015,8(6(SI)):16091-16107.
APA	Gao, Lianru.,Gao, Jianwei.,Li, Jun.,Plaza, Antonio.,Zhuang, Lina.,...&Zhang, Bing.(2015).Multiple Algorithm Integration Based on Ant Colony Optimization for Endmember Extraction From Hyperspectral Imagery.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,8(6(SI)),16091-16107.
MLA	Gao, Lianru,et al."Multiple Algorithm Integration Based on Ant Colony Optimization for Endmember Extraction From Hyperspectral Imagery".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 8.6(SI)(2015):16091-16107.