Feature reduction of hyperspectral imagery using hybrid wavelet-principal component analysis

Optical Engineering

Volumn 43, Issue 2, 2004, Pages 350-362

  Kaewpijit, Sinthop ^a   Le Moigne, Jacqueline ^b   El Ghazawi, Tarek ^a  

^a George Washington University   (United States)

^b NASA GODDARD SPACE FLIGHT CENTER   (United States)

Author keywords

Dimension reduction; Maximum likelihood; Principal component analysis; Wavelet decomposition

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; INFRARED SPECTROMETERS; LOW PASS FILTERS; MAXIMUM LIKELIHOOD ESTIMATION; PRINCIPAL COMPONENT ANALYSIS; WAVELET TRANSFORMS;

DIMENSION REDUCTION; FEATURE REDUCTION; HYPERSPECTRAL IMAGERY; WAVELET PRINCIPAL COMPONENT ANALYSIS;

INFRARED IMAGING;

EID: 1942424078     PISSN: 00913286     EISSN: None     Source Type: Journal    
DOI: 10.1117/1.1637907     Document Type: Article

References (21)

1. J. A. Richards, Remote Sensing Digital Image Analysis: An Introduction, Spring-Verlag, Berlin, Heidelberg (1999).
2. D. Landgrebe, "Multispectral data analysis: A signal theory perspective," Technical Report, School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 1998. Available: http://ee.www.ecn.purdue.edu/~biehl/MultiSpec/Signal_Theory.pdf
3. S. G. Mallat, "A theory for multiresolution signal decomposition: the wavelet representation," IEEE Trans. Pattern Anal. Mach. Intell. 11(7), 674-693 (1989).
4. S. Kaewpijit, J. Le Moigne, and T. El-Ghazawi, "Automatic wavelet spectral analysis for reduction of hyperspectral imagery," IEEE Trans. Geosci. Remote Sens. 41(4), 863-871 (2003).
5. I. Daubechies, Ten Lectures on Wavelets, SIAM, Philadelphia, PA (1992).
6. S. A. Dianat and R. Rao, "Wavelet transforms: Theory and applications," Short Course Note: Proc. SPIE's 12th Annual International-Symposium on Aerosense/Defense Sensing, Simulation & Controls, 13-17 April (1998).
7. L. Bruce and J. Li, "Wavelet for computationally efficient hyperspectral derivative analysis," IEEE Trans. Geosci. Remote Sens. 39(7), 1540-1546 (2001).
8. C. I. Chang, "An information theoretic-based approach to spectral variability, similarity and discriminability for hyperspectral image analysis," IEEE Trans. Inf. Theory 46(5), 1927-1932 (2000).
9. H. Kim and P. H. Swain, "Evidential reasoning approach to multisource-data classification in remote sensing," IEEE Trans. Syst. Man Cybern. 25(8), 1257-1265 (1995).
10. S. Kaewpijit, J. Le Moigne, and T. El-Ghazawi, "A wavelet-based PCA reduction for hyperspectral imagery," in Proc. 2002 Intl. Geosci. Remote Sens. Symp. (IGARSS'02), Toronto, Canada.
11. X. Jia and J. E. Richards, "Efficient maximum likelihood classification for imaging spectrometer data sets," IEEE Trans. Geosci. Remote Sens. 32(2), 274-281 (1994).
12. J. A. Gualtieri, S. R. Chettri, R. F. Cromp, and L. F. Johnson, "Support vector machine classifiers as applied to AVIRIS data," Summaries 8th JPL Airborne Earth Sci. Workshop, Feb. 8-11, 1999.
13. Research System Inc., ENVI User's Guide (1999).
14. X. Jia and J. A. Richards, "Segmented principal components transformation for efficient hyperspectral remote-sensing image display and classification," IEEE Trans. Geosci. Remote Sens. 37(1), 538-542 (1999).
15. R. O. Duda and P. E. Hart, Pattern Classification and Scene Analysis, John Wiley and Sons, New York (1973).
16. T. M. Lillesand and R. W. Kiefer, Remote Sensing and Image Interpretation, John Wiley and Sons, Inc., New York (1994).
17. P. H. Swain and S. M. Davis, Remote Sensing: The Quantitative Approach, McGraw-Hill, Inc., New York (1978).
18. H. H. Szu, J. Le Moigne, N. S. Netanyahu, and C. C. Hsu, "Integration of local texture information in the automatic classification of Landsat images," Proc. SPIE 3078, 116-127 (1997).
19. T. El-Ghazawi, P. Charlemwat, and J. Le Moigne. "Wavelet-based image registration on parallel computers," Proc. ACM/IEEE (1997).
20. D. Ridge, D. Becker, P. Merkey, and T. Sterling, "Beowulf: Harnessing the power of parallelism in a pile-of-pCs," Proc. IEEE Aerospace Conf. 2, 79-91 (1997).
21. K. Hwang and Z. Xu, Scalable Parallel Computing, McGraw-Hill, Boston, MA (1998).