Principal Skewness Analysis: Algorithm and Its Application for Multispectral/Hyperspectral Images Indexing

被引：22

作者：

Geng, Xiurui ^{[1
]}

Ji, Luyan ^{[1
]}

Sun, Kang ^{[1
]}

机构：

[1] Chinese Acad Sci, Inst Elect, Key Lab Technol Geospatial Informat Proc & Appl S, Beijing 100190, Peoples R China

来源：

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2014年 / 11卷 / 10期

关键词：

Coskewness tensor; independent components analysis (ICA); multispectral/hyperspectral data; INDEPENDENT COMPONENT ANALYSIS; PROJECTION PURSUIT; HYPERSPECTRAL DATA; DIMENSIONALITY REDUCTION;

D O I：

10.1109/LGRS.2014.2311168

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

In this letter, we present a new feature extraction approach based on third-order statistics (coskewness tensor) called principal skewness analysis (PSA). PSA is the natural extension of principal components analysis from second-order statistics to third-order statistics. The result of PSA is equivalent to that of FastICA when skewness is considered as a non-Gaussian index. Similar to FastICA, PSA also applies the fixed-point method to search the skewness extreme directions. However, when calculating the new projected direction in each iteration, PSA only requires a coskewness tensor, whereas FastICA requires all the pixels to be involved. Therefore, PSA has an advantage over FastICA in speed.

引用

页码：1821 / 1825

页数：5

共 22 条

[1] Dimensionality reduction of hyperspectral data using discrete wavelet transform feature extraction [J].

Bruce, LM ;

Koger, CH ;

Li, J .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2002, 40 (10) :2331-2338

[2] BLIND BEAMFORMING FOR NON-GAUSSIAN SIGNALS [J].

CARDOSO, JF ;

SOULOUMIAC, A .

IEE PROCEEDINGS-F RADAR AND SIGNAL PROCESSING, 1993, 140 (06) :362-370

[3] Hyperspectral Image Classification Using Nearest Feature Line Embedding Approach [J].

Chang, Yang-Lang ;

Liu, Jin-Nan ;

Han, Chin-Chuan ;

Chen, Ying-Nong .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2014, 52 (01) :278-287

[4] Unsupervised target detection in hyperspectral images using projection pursuit [J].

Chiang, SS ;

Chang, CI ;

Ginsberg, IW .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2001, 39 (07) :1380-1391

[5] High-order statistics-based approaches to endmember extraction for hyperspectral imagery [J].

Chu, Shih-Yu ;

Ren, Hsuan ;

Chang, Chein-, I .

ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XIV, 2008, 6966

[6] A multilinear singular value decomposition [J].

De Lathauwer, L ;

De Moor, B ;

Vandewalle, J .

SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS, 2000, 21 (04) :1253-1278

[7] PROJECTION PURSUIT ALGORITHM FOR EXPLORATORY DATA-ANALYSIS [J].

FRIEDMAN, JH ;

TUKEY, JW .

IEEE TRANSACTIONS ON COMPUTERS, 1974, C 23 (09) :881-890

[8] EXPLORATORY PROJECTION PURSUIT [J].

FRIEDMAN, JH .

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1987, 82 (397) :249-266

[9] Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data [J].

Gong, Peng ;

Wang, Jie ;

Yu, Le ;

Zhao, Yongchao ;

Zhao, Yuanyuan ;

Liang, Lu ;

Niu, Zhenguo ;

Huang, Xiaomeng ;

Fu, Haohuan ;

Liu, Shuang ;

Li, Congcong ;

Li, Xueyan ;

Fu, Wei ;

Liu, Caixia ;

Xu, Yue ;

Wang, Xiaoyi ;

Cheng, Qu ;

Hu, Luanyun ;

Yao, Wenbo ;

Zhang, Han ;

Zhu, Peng ;

Zhao, Ziying ;

Zhang, Haiying ;

Zheng, Yaomin ;

Ji, Luyan ;

Zhang, Yawen ;

Chen, Han ;

Yan, An ;

Guo, Jianhong ;

Yu, Liang ;

Wang, Lei ;

Liu, Xiaojun ;

Shi, Tingting ;

Zhu, Menghua ;

Chen, Yanlei ;

Yang, Guangwen ;

Tang, Ping ;

Xu, Bing ;

Giri, Chandra ;

Clinton, Nicholas ;

Zhu, Zhiliang ;

Chen, Jin ;

Chen, Jun .

INTERNATIONAL JOURNAL OF REMOTE SENSING, 2013, 34 (07) :2607-2654

[10] A TRANSFORMATION FOR ORDERING MULTISPECTRAL DATA IN TERMS OF IMAGE QUALITY WITH IMPLICATIONS FOR NOISE REMOVAL [J].

GREEN, AA ;

BERMAN, M ;

SWITZER, P ;

CRAIG, MD .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1988, 26 (01) :65-74

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