Anomaly detection through adaptive background class extraction from dynamic hyperspectral data

Proceedings of the 7th Nordic Signal Processing Symposium, NORSIG 2006

Volumn , Issue , 2006, Pages 234-237

  Duran, Olga ^a   Petrou, Maria ^a   Hathaway, David ^b   Nothara, Joanne ^b  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b QINETIQ   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL EFFICIENCY; DATA REDUCTION; IMAGE ANALYSIS; REMOTE SENSING;

ANOMALY DETECTION; DYNAMIC HYPERSPECTRAL DATA; SPECTRAL SIGNATURE;

SATELLITE IMAGERY;

EID: 39049151340     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NORSIG.2006.275231     Document Type: Conference Paper

References (12)

1. D. Stein, S. Beaven, E. S. A. Hoff, L.E.and Winter, and A. Stocker, "Anomaly detection from hyperspectral imagery," IEEE Signal Processing Magazine, vol. 19, no. 1, pp. 58-69, 2002.
2. O. Duran and M. Petrou, "A time-efficient clustering method for pure class selection," in International Geoscience and Remote Sensing Symposium, (IGARSS), vol. 1, July 2005, pp. 510-513.
3. E. Ashton, "Detection of subpixel anomalies in multispectral infrared imagery using an adaptive bayesian classifier," IEEE Transactions on Geoscience and Remote Sensing, vol. 36, pp. 506-517, 1998.
4. I. Reed, S. Irving, and Y. Xiaoli, "Adaptive multiple-band cfar detection of an optical pattern with unknown spectral distribution," IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 38, pp. 1760-1770, 1990.
5. D. Manolakis and G. Shaw, "Anomaly detection from hyperspectral imagery," IEEE Signal Processing Magazine, vol. 19, no. 1, pp. 29-43, 2002.
6. A. Plaza, P. Martinez, R. Perez, and J. Plaza, "Spatial/spectral endmember extraction by multidimensional morphological operations," IEEE Transactions on Geoscience and Remote Sensing, vol. 40, no. 9, pp. 2025-2041, 2002.
7. G. Foody and D. Cox, "Sub-pixel land cover composition estimation using a linear mixture model and fuzzy membership functions," International Journal of Remote Sensing, vol. 15, pp. 619-631, 1994.
8. P. L. Aguilar, P. Martinez, R. Perez, and A. Hormigo, "Abundance extractions from AVIRIS image using a self-organizing neural network," in AVIRIS Airborne Geoscience Workshop Proceedings. Jet Propulsion Laboratory publication, 2000.
9. P. Martinez, J. Gualtieri, P. Aguilar, R. Perez, M. Linaje, J. Preciado, and A. Plaza, "Hyperspectral image classification using a self-organizing map," in Proceedings of the Tenth JPL Airborne Earth Science Workshop. Jet Propulsion Laboratory publication, 2000, pp. 267-274.
10. T. Kohonen, Self-Organizing Maps, ser. Springer Series in Information Sciences. Berlin, Heidelberg: Springer, 1995, (Third Extended Edition 2001).
11. J. Vesanto and E. Alhoniemi, "Clustering of the self-organizing map," IEEE Transactions on Neural Networks, vol. 11, no. 2, pp. 586-600, 2000.
12. J. Vesanto and M. Sulkava, "Distance matrix based clustering of the self-organizing map," in International Conference on Artificial Neural Networks - ICANN - Lecture Notes in Computer Science, J. R. Dorronsoro, Ed., vol. 2415. Madrid, Spain: Springer, aug 2002, pp. 951-956.