Band selection and its impact on target detection and classification in hyperspectral image analysis

2003 IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data

Volumn , Issue , 2004, Pages 374-377

  Du, Qian ^a  

^a TEXAS A AND M UNIVERSITY   (United States)

Author keywords

Band selection; Classification; Detection; Divergence distance; High order statistics; Hyperspectral imagery

Indexed keywords

CLASSIFICATION (OF INFORMATION); DISTRIBUTION FUNCTIONS; ERROR DETECTION; PROBABILITY DISTRIBUTIONS; RADAR TARGET RECOGNITION; REMOTE SENSING; SPECTROSCOPY;

BAND SELECTION; CLASSIFICATION PERFORMANCE; DIVERGENCE DISTANCE; HIGH ORDER STATISTICS; HYPER-SPECTRAL IMAGERIES; HYPERSPECTRAL IMAGE ANALYSIS; NEYMAN PEARSON DETECTION; TARGET DETECTION AND CLASSIFICATIONS;

IMAGE ANALYSIS;

EID: 84945278269     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WARSD.2003.1295217     Document Type: Conference Paper

References (6)

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2. C.-I Chang, Q. Du, T.-L. Sun and M. L. G. Althouse, "A joint band prioritization and band decorrelation approach to band selection for hyperspectral image classification," IEEE Trans. Geoscience and Remote Sensing, vol.37, pp.2631-2641, Nov.1999.
3. C.-I Chang, "An information theoretic-based approach to spectral variability, similarity and discriminability for hyperspectral image analysis," IEEE Trans. Information Theory, vol. 46, pp. 1927-1932, 2000.
4. J. Harsanyi, W. Farrand and C.-I Chang, "Determining the number and identity of spectral endmembers: an integrated approach using Neyman-Pearson eigenthresholding and iterative constrained RMS error minimization," Proc. Nineth Thematic Conference on Geologic Remote Sensing, February, 1993.
5. T. W. Anderson, An Introduction to Multivariate Statistical Analysis, 2nd. ed., New York: John Wiley & Sons, 1984.
6. C.-I Chang and Q. Du, "Estimation of number of spectrally distinct signal sources in hyperspectral imagery," IEEE Trans. Geoscience and Remote Sensing (in press).