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Local and Global Geometric Structure Preserving and Application to Hyperspectral Image Classification
Joint Authors
Yang, Lina
Luo, Huiwu
Li, Chunli
Tang, Yuan Yan
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-04-15
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Locality Preserving Projection (LPP) has shown great efficiency in feature extraction.
LPP capturesthe locality by the K-nearest neighborhoods.
However, recent progress has demonstrated the importanceof global geometric structure in discriminant analysis.
Thus, both the locality and global geometricstructure are critical for dimension reduction.
In this paper, a novel linear supervised dimensionalityreduction algorithm, called Locality and Global Geometric Structure Preserving (LGGSP)projection, is proposed for dimension reduction.
LGGSP encodes not only the local structure informationinto the optimal objective functions, but also the global structure information.
To be specific,two adjacent matrices, that is, similarity matrix and variance matrix, are constructed to detect the localintrinsic structure.
Besides, a margin matrix is defined to capture the global structure of differentclasses.
Finally, the three matrices are integrated into the framework of graph embedding for optimalsolution.
The proposed scheme is illustrated using both simulated data points and the well-knownIndian Pines hyperspectral data set, and the experimental results are promising.
American Psychological Association (APA)
Luo, Huiwu& Tang, Yuan Yan& Li, Chunli& Yang, Lina. 2015. Local and Global Geometric Structure Preserving and Application to Hyperspectral Image Classification. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1075050
Modern Language Association (MLA)
Luo, Huiwu…[et al.]. Local and Global Geometric Structure Preserving and Application to Hyperspectral Image Classification. Mathematical Problems in Engineering No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1075050
American Medical Association (AMA)
Luo, Huiwu& Tang, Yuan Yan& Li, Chunli& Yang, Lina. Local and Global Geometric Structure Preserving and Application to Hyperspectral Image Classification. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1075050
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1075050