Spectral-spatial Classification of Hyperspectral Images Using Signal Subspace Identification and Edge-preserving Filter

doi:10.1007/s11633-019-1188-5

CORC > 自动化研究所 > 中国科学院自动化研究所 > 学术期刊 > International Journal of Automation and Computing

	Spectral-spatial Classification of Hyperspectral Images Using Signal Subspace Identification and Edge-preserving Filter
	Negin Alborzi 2; Fereshteh Poorahangaryan 1; Homayoun Beheshti 2
刊名	International Journal of Automation and Computing
	2020
卷号	17 期号:2 页码:222-232
关键词	Hyperspectral image remote sensing the hyperspectral signal subspace identification (HYSIME) edge-preserving filter classification support vector machine.
ISSN号	1476-8186
DOI	10.1007/s11633-019-1188-5
英文摘要	Hyperspectral images in remote sensing include hundreds of spectral bands that provide valuable information for accurately identify objects. In this paper, a new method of classifying hyperspectral images using spectral spatial information has been presented. Here, using the hyperspectral signal subspace identification (HYSIME) method which estimates the signal and noise correlation matrix and selects a subset of eigenvalues for the best representation of the signal subspace in order to minimize the mean square error, subsets from the main sample space have been extracted. After subspace extraction with the help of the HYSIME method, the edge-preserving filtering (EPF), and classification of the hyperspectral subspace using a support vector machine (SVM), results were then merged into the decision-making level using majority rule to create the spectral-spatial classifier. The simulation results showed that the spectral-spatial classifier presented leads to significant improvement in the accuracy and validity of the classification of Indiana, Pavia and Salinas hyperspectral images, such that it can classify these images with 98.79%, 98.88% and 97.31% accuracy, respectively.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/42298]
专题	自动化研究所_学术期刊_International Journal of Automation and Computing
作者单位	1.Department of Electrical Engineering, Faculty of Electrical and Computer Engineering, Ayandegan Institute of Higher Education in Tonekabon, Mazandaran 4681853617, Iran 2.Department of Computer Engineering, Faculty of Electrical and Computer Engineering,Ayandegan Institute of Higher Education in Tonekabon, Mazandaran 4681853617, Iran
推荐引用方式 GB/T 7714	Negin Alborzi,Fereshteh Poorahangaryan,Homayoun Beheshti. Spectral-spatial Classification of Hyperspectral Images Using Signal Subspace Identification and Edge-preserving Filter[J]. International Journal of Automation and Computing,2020,17(2):222-232.
APA	Negin Alborzi,Fereshteh Poorahangaryan,&Homayoun Beheshti.(2020).Spectral-spatial Classification of Hyperspectral Images Using Signal Subspace Identification and Edge-preserving Filter.International Journal of Automation and Computing,17(2),222-232.
MLA	Negin Alborzi,et al."Spectral-spatial Classification of Hyperspectral Images Using Signal Subspace Identification and Edge-preserving Filter".International Journal of Automation and Computing 17.2(2020):222-232.