全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
测绘学报  2014 

有监督的邻域保留嵌入的高光谱遥感影像特征提取算法

, PP. 508-513

Keywords: 超光谱遥感图像,特征提取,分类

Full-Text   Cite this paper   Add to My Lib

Abstract:

超光谱遥感图像特征提取对于图像分类具有重要意义,本文提出一种名为判别监督邻域保留嵌入的新型特征提取算法(discriminativesupervisedneighborhoodpreservingembedding,DSNPE)。在高维超光谱遥感图像特征提取过程中,DSNPE不但能保留图像的局部流形结构和邻域信息,而且采用像素点由邻域同类像素点线性表示,将邻域中同类和非同类像素点分开处理,利用判别分式求解最优投影矩阵,使高维像素点投影到低维空间时,同类点离得尽可能近,非同类点离得尽可能远,有利于图像的分类。对三幅超光谱遥感图像的特征提取及分类的实验说明与主成分分析(PCA)、非参数权重特征提取(NWFE)、局部保留投影(LPP)、邻域保留嵌入(NPE)等相比,具有一定的优越性和可判别性。

References

[1]  AGYEMANG T K, HEBLINSKI J. Accuracy Assessment of Supervised Classification of Submersed Macrophytes: the Case of the Gavaraget Region of Lake Sevan, Armenia[J]. Hydrobiologia, 2011,661(1): 85-96 .
[2]  TRACOL Y, GUTIERREZ J R. Plant Area Index and Mmicroclimate Underneath Shrub Species from a Chilean Semiarid Community[J]. Journal of Arid Environments, 2011,75(1): 1-6.
[3]  TOMLINSON C J, CHAPMAN L. Remote Sensing Land Surface Temperature for Meteorology and Climatology: a Review[J]. Meteorological Applications, 2011,18(3): 296-306.
[4]  HUGHES G F. On the mean accuracy of statistical pattern recognizers[J]. IEEE Transactions on Information Theory, 1968,14(1): 55-63.
[5]  XIAO Pengfeng, FENG Xuezhi. Segmentation of high-resolutionremotely sensed imagery based on features in frequency domain[ J] .Acta Geodaetica et Cartographica Sinica, 2008, 37( 3): 401. (肖鹏峰,冯学智. 高分辨率遥感图像频域特征提取与图像分割研究[J], 测绘学报,2008,37(3):401).
[6]  WU Hangbin. Classification and Feature Extraction of Airborne LiDAR Data Fused with Aerial Image[J]. Acta Geodaetica et Cartographica Sinica,2011,0(1):134.(吴杭彬. 融合航空影像的机载激光扫描数据分类与特征提取[J].测绘学报,2011,40(1):134.)
[7]  FONG. M. Dimension reduction on hyperspectral images[R], University of California, Los Angeles, United States, 2007, August 31,.
[8]  SCHOTT J. Remote sensing: the image chain approach[M], Oxford University Press, 1996.
[9]  FAUVEL M, CHANUSSOT J , BENEDIKTSSON J A. Kernel principal component analysis for the classification of hyperspectral remote-sensing data over urban areas[J],EURASIP Journal on Advances in Signal Processing, 2009, Article ID 783194.
[10]  Du Q, Modified Fisher’s linear discriminant analysis for hyperspectral imagery[J], IEEE Geosci. Remote Sens. Lett. 2007, 4(4): 503-507.
[11]  BANDOS T V, BRUZZONE L, CAMPS-VALLS G., Classification of hyperspectral images with regularized linear discriminant analysis [J], IEEE Trans. Geosci. Remote Sens., 2009,47 (3):862-873.
[12]  YANG J.-M, YY P.-T., KUO B.-C., A nonparametric feature extraction and its application to nearest neighbor classification for hyperspectral image data[J], IEEE Trans. Geosci. Remote Sens., 2010,48(3):1279-1293.
[13]  HUANG H.-Y., KUO B.-C., Double nearest proportion feature extraction for hyperspectral-image classi?cation[J], IEEE Trans. Geosci. Remote Sens., 2010, 48(11): 4034-4046.
[14]  LUO Renbo,PI Youguo,LIAO Wenzhi. Research on Supervised LPP Feature Extraction for Hyperspectral Image [J].Remote Sensing Technology and Application,2012,27(6):46-52.(骆仁波,皮佑国,廖文志. 超光谱遥感图像有监督LPP特征提取研究[J],遥感技术与应用,2012,27(6):46-52.)
[15]  HE X. , CAI D., Yan S., ZhANG H., Neighborhood preserving embedding[C], in Proc. IEEE Int. Conf. Comput. Vis., 2005:1208-1213.
[16]  BELKIN M., NIYOGI P., Laplacian eigenmaps and spectral techniques for embedding and clustering[C], in Advances in Neural Infor-mation Processing System, vol. 14. Cambridge, MA: MIT Press, 2002:585-591.
[17]  ROWEIS S. T., SAUL L. K., Nonlinear dimensionality reduction by locally linear embedding[J], Science, 2000, 290 (5500): 2323-2326.
[18]  AVIRIS NW Indiana’s Indian Pines 1992 Data Set. [Online]. Available: ftp://ftp.ecn.purdue.edu /biehl/MultiSpec/92AV3C(original ?les) and ftp://ftp.ecn.purdue.edu/biehl/PC_MultiSpec/Thy Files.zip (ground truth) .
[19]  HAM J., YANGCHI C., CRAWFORD M., GHOSH J., Investigation of the random forest framework for classification of hyperspectral data[J], IEEE Trans. Geosci. Remote Sens., 2005, 43( 3): 492-501.
[20]  LANDGREBE D. A., Signal Theory Methods in Multispectral Remote Sensing. Hoboken, NJ: Wiley, 2003.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133