Unsupervised hyperspectral target detection based on multiresolntion image fusion

International Conference on Signal Processing Proceedings, ICSP

Volumn 2, Issue , 2004, Pages 1076-1079

  Gu, Yanfeng ^a   Jia, Youhna ^a   Zhang, Ye ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Hyperspectral images; Iinage fusion; RX detection; Target detection

Indexed keywords

ALGORITHMS; FEATURE EXTRACTION; IMAGE RECONSTRUCTION; PATTERN MATCHING; PROBABILITY; WAVELET TRANSFORMS;

AUTOMATIC SUBSPACE DECOMPOSITION (ASD); HYPERSPECTRAL IMAGES; IMAGE FUSION; RX DETECTION;

AUTOMATIC TARGET RECOGNITION;

EID: 7744236047     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

1. D.Manolakis and G.Shaw. Detection Algorithms for Hyperspectral Imaging Applications. IEEE Signal Processing Magazine, January 2002. pp. 29-43.
2. Cheng-I Chang, Xiao-Li Zhao, M.L.G.Althouse, Jeng Jong Pan. Least squares subspace projection approach to mixed pixel classification for hyperspectral images. IEEE Trans. Geosci. Remote Sensing, Vol. 36, No.3, May 1998. pp. 898-912
3. Qian Du, Hsuan Ren. Real-time constrained linear discriminant analysis to target detection and classi_cation in hyperspectral imagery. Pattern Recognition. 36(1), January, 2003, pp. 1-12
4. S.M. Schweizer, J.M.F. Moura. Hyperspectral Imagery: Clutter Adaptation in Anomaly Detection. IEEE Tran. On Information Theory, 46(5), August 2000, pp. 1855-1871
5. Chein-I Chang, and Shao-Shan Chiang. Anomaly Detection and Classification for Hyperspectral Imagery. IEEE Trans. Geosci. Remote Sensing, Vol. 40, No. 6, June 2002, pp. 1314-1325.
6. W.J.S. David, G.B. Scott et al. Anomaly Detection from Hyperspectral Imagery. IEEE Signal Processing Magazine, January 2002, pp. 58-69
7. N.J.Gordon, D.J. Salmond, and A.F.M. Smith. Novel approach to nonlinear/non-Gaussian Bayesian state estimation. IEE Proceedings-F, 140(2), 1993, pp. 107-113
8. Zhang Ye, Zhang Junping, Jin Ming & Mita D. Desai. Adaptive Subspace Decomposition and Classification for Hyperspectral Images. Chinese Journal of Electronics. Vol.9, No.1, Jan. 2000, p82-88
9. I.S. Reed and X. Yu. Adaptive multiband CFAR detection of an optical pattern with unknown spectral distribution. IEEE Transactions Acoustics, Speech, and Signal Processing, 38(10), October 1990, pp. 1760-766