Feature extraction of hyperspectral images using matching pursuit

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Volumn 35, Issue , 2004, Pages 883-888

  Hsu, P H ^a  

^a NATIONAL SCIENCE AND TECHNOLOGY CENTER FOR DISASTER REDUCTION   (Taiwan)

Author keywords

Classification; Feature extraction; Hyper spectral sensing; Matching pursuit; Wavelet transform

Indexed keywords

EXTRACTION; FEATURE EXTRACTION; LAND USE; SPECTROSCOPY; WAVELET ANALYSIS; WAVELET TRANSFORMS;

CLASSIFICATION ACCURACY; CLASSIFICATION METHODS; CLASSIFICATION PERFORMANCE; CURSE OF DIMENSIONALITY; FEATURE EXTRACTION METHODS; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL; MATCHING PURSUIT;

CLASSIFICATION (OF INFORMATION);

EID: 84957080740     PISSN: 16821750     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. Bellman, R., 1961. Adaptive Control Processes: A Guided Tour, Princeton University Press.
2. Benediktsson, J. A., J. R. Sveinsson, and K. Arnason, 1995. Classification and feature extraction of AVIRIS data. IEEE Trans. Geoscience and Remote Sensing, 33(5), pp. 1194-1205.
3. Coifman, R. R., Y. Meyer, and M. V. Wickerhauser, 1992. Wavelet analysis and signal processing. In: Wavelets and Their Applications, Jones and Barlett, Boston.
4. Fukunaga, K., 1990. Introduction to Statistical Pattern Recognition. Academic Press, San Diego.
5. Firedman, J. D. and W. Stuetzle, 1981. Projection pursuit regression. J. of Amer. Stat. Assoc., 76, pp. 817-823.
6. Goetz, A. F. H., G. Vane, J. E. Solomon, and B. N. Rock, 1985. Imaging Spectrometry for earth remote sensing. Science, 228(4704), pp. 1147-1153.
7. Hughes, G. F., 1968. On the mean accuracy of statistical pattern recognizers. IEEE Trans. Information Theory, IT-14(1), pp. 55-63.
8. Hsu, P. H., Y. H. Tseng and P. Gong, 2002. Dimension reduction of hyperspectral images for classification applications. Geographic Information Sciences, 8(1), pp. 1-8.
9. Hsu, P.H., 2003. Spectral Feature Extraction of Hyperspectral Images Using Wavelet Transform. Ph.D. Thesis, Department of Surveying Engineering, National Cheng Kung University, Tainan, Taiwan, R.O.C.
10. Jain, A. K., R. P. W. Duin, and J. Mao, 2000. Statistical pattern recognition: A Review. IEEE Trans. Pattern Analysis and Machine Intelligence, 22(1), pp. 4-37.
11. Jimenez, L. O. and D. A. Landgrebe, 1995. High Dimensional Feature Reduction Via Projection Pursuit. Ph.D. thesis, School of Electrical & Computer Engineering, Purdue University, West Lafayette.
12. Landgrebe, D. A., 2001. Analysis of multispectral and hyperspectral image data. In: Introduction to Modern Photogrammetry, John Wiley & Sons, Inc.
13. Lee, C. and D. A. Landgrebe, 1993. Analyzing highdimensional multisepctral data. IEEE Trans. Geoscience and Remote Sensing, 31(4), pp. 792-800.
14. Lillesand, T. M. and R. W. Kiefer, 2000. Remote Sensing and Image Interpretation. John Wiley & Sons, New York.
15. Mallat, S., 1989. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans. Pattern Analysis and Machine Intelligence, 11(7), pp. 674-693.
16. Mallat, S., Z. Zhang, 1993. Matching pursuit with timefrequency dictionaries. IEEE Trans. Signal Processing, 41(12), pp. 3397-3415.
17. Mallat, S., 1999. A Wavelet Tour of Signal Processing. Academic Press, San Diego.
18. Pittner, S. and S. V. Kamarthi, 1999. Feature extraction from wavelet coefficients for pattern recognition tasks. IEEE Trans. Pattern Analysis and Machine Intelligence, 21(1), pp. 83-88.
19. Saito, N. and R. R. Coifman, 1994. Local discriminant bases. In: Proceeding of SPIE.
20. Tadjudin, S. and D. A. Landgrebe, 1998. Classification of high dimensional data with limited training samples. Ph.D. thesis, School of Electrical & Computer Engineering, Purdue University, West Lafayette.