A modular eigen subspace scheme for high-dimensional data classification

Future Generation Computer Systems

Volumn 20, Issue 7, 2004, Pages 1131-1143

  Chang, Yang Lang ^a   Han, Chin Chuan ^b   Jou, Fan Di ^c   Fan, Kuo Chin ^c   Chen, K S ^c   Chang, Jeng Horng ^d  

^a ST JOHN'S UNIVERSITY   (Taiwan)

^b CHUNG HUA UNIVERSITY   (Taiwan)

^c NATIONAL CENTRAL UNIVERSITY   (Taiwan)

^d TAKMING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

Author keywords

Greedy modular subspaces; High dimensional data classification; Mean absolute errors; Principal components analysis

Indexed keywords

EIGEN SUBSPACE; GREEDY MODULAR SUBSPACES (GMS); HIGH-DIMENSIONAL DATA CLASSIFICATION; MEAN ABSOLUTE ERRORS;

ALGORITHMS; COMPUTATIONAL COMPLEXITY; DATA ACQUISITION; EIGENVALUES AND EIGENFUNCTIONS; MATHEMATICAL TECHNIQUES; PRINCIPAL COMPONENT ANALYSIS;

CLASSIFICATION (OF INFORMATION);

EID: 4444289278     PISSN: 0167739X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.future.2003.11.003     Document Type: Article

References (19)

1. Jimenez L.O., Landgrebe D.A. Supervised classification in high-dimensional space: geometrical, statistical, and asymptotical properties of multivariate data. IEEE Trans. Syst. Man Cybernet. C. 28(1):1998;39-54.
2. Jimenez L.O., Landgrebe D.A. Hyperspectral data analysis and supervised feature reduction via projection pursuit. IEEE Trans. Geosci. Remote Sensing. 37(6):1999;2653-2667.
3. Kumar S., Ghosh J., Crawford M.M. Best-bases feature extraction algorithms for classification of hyperspectral data. IEEE Trans. Geosci. Remote Sensing. 39(7):2001;1368-1379.
4. A. Pentland, B. Moghaddam, View-based and modular eigenspaces for face recognition, in: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1994, pp. 84-91.
5. Han C.C., Fan K.C., Chen Z.M. Finding of optimal stack filter by graphic searching methods. IEEE Trans. Signal Process. 45(7):1997;1857-1862.
6. C.C. Han, C.L. Tsai, A multi-resolutional face verification system via filter-based integration, in: Proceedings of the IEEE International Carnahan Conference on Security Technology, 2001, pp. 278-281.
7. C.C. Han, A supervised classification scheme using positive Boolean function, in: Proceedings of the International Conference on Pattern Recognition, IEEE Press, Que., Canada, 2002, pp. 100-103.
8. Chang C.-I., Du Q., Sun T.L., Althouse M.L.G. A joint band prioritization and band decorrelation approach to band selection for hyperspectral image classification. IEEE Trans. Geosci. Remote Sensing. 37(6):1999;2631-2641.
9. Chang C.-I., Du Q. Interference and noise adjusted principal components analysis. IEEE Trans. Geosci. Remote Sensing. 37(5):1999;2387-2396.
10. Tu T.M., Chen C.-H., Wu J.-L., Chang C.-I. A fast two-stage classification method for high dimensional remote sensing data. IEEE Trans. Geosci. Remote Sensing. 36:1998;182-191.
11. C.-I Chang, S.-S. Chiang, Discrimination measures for target classification, in: Proceedings of the IEEE International, Geoscience and Remote Sensing Symposium (IGARSS'01), vol. 4, 2001, pp. 1871-1873.
12. Lee C., Landgrebe D.A. Analyzing high-dimensional multispectral data. IEEE Trans. Geosci. Remote Sensing. 31(4):1993;792-800.
13. J.A. Richards, Remote Sensing Digital Image Analysis, An Introduction, 2nd ed., Springer-Verlag, New York, 1993.
14. Jia X., Richards J.A. Segmented principal components transformation for efficient hyperspectral remote-sensing image display and classification. IEEE Trans. Geosci. Remote Sensing. 37(1):1999;538-542.
15. B. Moghaddam, A. Pentland, Probabilistic visual learning for object detection, in: Proceedings of the Fifth International Conference on Computer Vision, Boston, MA, 1995, pp. 786-793.
16. Wendt P.D., Coyle E.J., Gallagher N.C. Stack filter. IEEE Trans. Acoust. Speech Signal Process. 34(4):1986;898-911.
17. Fitch J.P., Coyle E.J., Gallagher N.C. Median filtering by threshold decomposition. IEEE Trans. Acoust. Speech Signal Process. 32:1984;1183-1188.
18. Maragos P., Schafer R.S. Morphological filters. Part II. Their relations to median, order-statistic, and stack filters. IEEE Trans. Acoust. Speech Signal Process. 35:1987;1170-1184.
19. Hook S.J., Myers J.J., Thome K.J., Fitzgerald M., Kahle A.B. The MODIS/ASTER airborne simulator (MASTER) - a new instrument for earth science studies. Remote Sensing Environ. 76(1):2000;93-102.