Information fusion in the redundant-wavelet-transform domain for noise-robust hyperspectral classification

IEEE Transactions on Geoscience and Remote Sensing

Volumn 50, Issue 9, 2012, Pages 3474-3486

  Prasad, Saurabh ^a   Li, Wei ^b   Fowler, James E ^b   Bruce, Lori M ^b  

^a UNIVERSITY OF HOUSTON   (United States)

^b MISSISSIPPI STATE UNIVERSITY   (United States)

Author keywords

Dimensionality reduction; hyperspectral data; pattern recognition; redundant wavelet transforms

Indexed keywords

CLASSIFICATION APPROACH; CLASSIFICATION TASKS; CONVENTIONAL METHODS; DE-NOISING; DIMENSIONALITY REDUCTION; DIVIDE-AND-CONQUER APPROACH; FEATURE SPACE; HIGH DIMENSIONAL SPACES; HIGH DIMENSIONALITY; HIGH-DIMENSIONAL; HIGH-DIMENSIONAL FEATURE SPACE; HYPER-SPECTRAL CLASSIFICATION; HYPERSPECTRAL DATA; HYPERSPECTRAL IMAGERY; ILL-CONDITIONED; LINEAR DISCRIMINANT ANALYSIS; MULTI SCALE ANALYSIS; MULTI-CLASSIFIER; MULTICLASSIFIER SYSTEM; NOISE PERFORMANCE; NOISE ROBUSTNESS; REDUNDANT WAVELET TRANSFORM; SPECTRAL RESPONSE; TARGET RECOGNITION; VALIDATION STUDY;

PATTERN RECOGNITION; REMOTE SENSING;

WAVELET TRANSFORMS;

CLASSIFICATION; DATA SET; DISCRIMINANT ANALYSIS; IMAGERY; NOISE; PATTERN RECOGNITION; PIXEL; SPECTRAL REFLECTANCE; WAVELENGTH; WAVELET ANALYSIS;

EID: 84865677926     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2012.2185053     Document Type: Article

References (26)

1. P. Dutilleux, "An implementation of the 'algorithme à trous' to compute the wavelet transform," in Wavelets: Time-Frequency Methods and Phase Space, J.-M. Combes, A. Grossman, and P. Tchamitchian, Eds. Berlin, Germany: Springer-Verlag, 1989, pp. 298-304.
2. P. Scheunders, "Wavelet thresholding of multivalued images," IEEE Trans. Image Process., vol. 13, no. 4, pp. 475-483, Apr. 2004.
3. J. Scharcanski, C. Jung, and R. Clarke, "Adaptive image denoising using scale and space consistency," IEEE Trans. Image Process., vol. 11, no. 9, pp. 1092-1101, Sep. 2002. (Pubitemid 35250392)
4. B. Goossens, A. Pizurica, and W. Philips, "Removal of correlated noise by modeling the signal of interest in the wavelet domain," IEEE Trans. Image Process., vol. 18, no. 6, pp. 1153-1165, Jun. 2009.
5. G. Chen and S. Qian, "Denoising of hyperspectral imagery using principal component analysis and wavelet shrinkage," IEEE Trans. Geosci. Remote Sens., vol. 49, no. 3, pp. 973-980, Mar. 2011.
6. A. Pizurica, B. Huysmans, P. Scheunders, and W. Philips, "Wavelet domain denoising of multispectral remote sensing imagery adapted to the local spatial and spectral context," in Proc. Int. Geosci. Remote Sens. Symp., Jul. 2005, vol. 6, pp. 4260-4263.
7. A. Karahaliou, I. Boniatis, S. Skiadopoulos, F. Sakellaropoulos, N. Arikidis, E. Likaki, G. Panayiotakis, and L. Costaridou, "Breast cancer diagnosis: Analyzing texture of tissue surrounding microcalcifications," IEEE Trans. Inf. Technol. Biomed., vol. 6, no. 6, pp. 731-738, Nov. 2008.
8. J. Fowler, S. Cui, and Y. Wang, "Motion compensation via redundantwavelet multihypothesis," IEEE Trans. Image Process., vol. 12, no. 10, pp. 3102-3113, Oct. 2006. (Pubitemid 44473650)
9. Y. Zhang, S. De Backer, and P. Scheunders, "Noise-resistant waveletbased Bayesian fusion of multispectral and hyperspectral images," IEEE Trans. Geosci. Remote Sens., vol. 47, no. 11, pp. 3834-3843, Nov. 2009.
10. J. E. Fowler, "The redundant discrete wavelet transform and additive noise," IEEE Signal Process. Lett., vol. 12, no. 9, pp. 629-632, Sep. 2005. (Pubitemid 41554401)
11. C. S. Burrus, R. A. Gopinath, and H. Gao, Introduction to Wavelets and Wavelet Transforms: A Primer. Upper Saddle River, NJ: Prentice-Hall, 1998.
12. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification, 2nd ed. New York: Wiley, 2001.
13. W. Li, S. Prasad, J. E. Fowler, and L. M. Bruce, "Locality preserving dimensionality reduction and classification for hyperspectral image analysis," IEEE Trans. Geosci. Remote Sens., vol. 50, no. 4, Apr. 2012, to be published.
14. M. M. Dundar and D. Landgrebe, "A model-based mixture-supervised classification approach in hyperspectral data analysis," IEEE Trans. Geosci. Remote Sens., vol. 40, no. 12, pp. 2692-2699, Dec. 2002.
15. A. Berge and A. H. S. Solberg, "Structured Gaussian components for hyperspectral image classification," IEEE Trans. Geosci. Remote Sens., vol. 44, no. 11, pp. 3386-3396, Nov. 2006. (Pubitemid 44711680)
16. N. Vlassis and A. Likas, "A greedy EM algorithm for Gaussian mixture learning," Neural Process. Lett., vol. 15, no. 1, pp. 77-87, Feb. 2002. (Pubitemid 34149545)
17. A. P. Benavent, F. E. Ruiz, and J. M. S. Martínez, "EBEM: An entropybased EM algorithm for Gaussian mixture models," in Proc. IEEE Int. Conf. Pattern Recogn., New York, Jun. 2006, vol. 2, pp. 451-455. (Pubitemid 46532235)
18. G. Schwarz, "Estimation the dimension of a model," Ann. Stat., vol. 6, no. 2, pp. 461-464, Mar. 1978.
19. S. Prasad and L. M. Bruce, "Decision fusion with confidence-based weight assignment for hyperspectral target recognition," IEEE Trans. Geosci. Remote Sens., vol. 46, no. 5, pp. 1448-1456, May 2008.
20. J. A. Benediktsson and J. R. Sveinsson, "Multisource remote sensing data classification based on consensus and pruning," IEEE Trans. Geosci. Remote Sens., vol. 41, no. 4, pp. 932-936, Apr. 2003.
21. K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. San Diego, CA: Academic, 1990.
22. M. L. Nischan, J. P. Kerekes, J. E. Baum, and R. W. Basedow, "Analysis of HYDICE noise characteristics and their impact on subpixel object detection," in Proc. SPIE - Imaging Spectrometry V, M. R. Descour and S. S. Shen, Eds., Denver, CO, Jul. 1999, vol. 3753, pp. 112-123. (Pubitemid 30553867)
23. R.W. Basedow and E. Zalewski, "Characteristics of the HYDICE sensor," in Proc. Summ. 5th Annu. JPL Airborne Earth Sci.Workshop, 1995, vol. 1, p. 9.
24. L. J. Rickard, R. W. Basedow, E. F. Zalewski, P. R. Silverglate, and M. Landers, "HYDICE: An airborne system for hyperspectral imaging," in Proc. SPIE - Imaging Spectrometry of the Terrestrial Environment, G. Vane, Ed., Orlando, FL, Apr. 1993, vol. 1937, pp. 173-179.
25. X. Huang and L. Zhang, "An adaptive mean-shift analysis approach for object extraction and classification from urban hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 46, no. 12, pp. 4173-4185, Dec. 2008.
26. R. C. Gonzalez and R. E. Woods, Digital Image Processing, 2nd ed. Upper Saddle River, NJ: Prentice-Hall, 2002.