Realistic matched filter performance prediction for hyperspectral target detection

Optical Engineering

Volumn 44, Issue 11, 2005, Pages

  Manolakis, Dimitris ^a  

^a MIT LINCOLN LABORATORY   (United States)

Author keywords

Hyperspectral; Linear matched filter; Target detection

Indexed keywords

EDGE DETECTION; MATHEMATICAL MODELS; NORMAL DISTRIBUTION; PROBABILITY DENSITY FUNCTION;

HYPERSPECTRAL TARGET DETECTION; LINEAR MATCHED FILTER; MULTIVARIATE DISTRIBUTIONS;

OPTICAL FILTERS;

EID: 33747584910     PISSN: 00913286     EISSN: 15602303     Source Type: Journal    
DOI: 10.1117/1.2125487     Document Type: Article

References (16)

1. D. Manolakis and G. Shaw, "Detection algorithms for hyperspectral imaging application," IEEE Signal Process. Mag., 29-43 (Jan. 2002).
2. G. Healey and D. Slater, "Models and methods for automated material identification in hyperspectral imagery acquired under unknown illumination and atmospheric conditions," IEEE Trans. Geosci. Remote Sens. GE-37(6), 2706-2717 (Nov. 1999).
3. J. D. Echard, "Estimation of radar detection and false alarm probabilities," IEEE Trans. Aerosp. Electron. Syst. 27(2), 255-260 (Mar. 1991).
4. X. Yu, I. S. Reed, and A. D. Stocker, "Comparative performance analysis of adaptive multiband detectors," IEEE Trans. Signal Process. 41(8), 2639-2656 (Aug. 1993).
5. E. J. Kelly, "An adaptive detection algorithm," IEEE Trans. Aerosp. Electron. Syst. 22(1), 115-127 (Mar. 1986).
6. I. S. Reed and X. Yu, "Adaptive multiple-band CFAR detection of an optical pattern with unknown spectral distribution," IEEE Trans. Acoust., Speech, Signal Process. ASSP- 38(10), 1760-1770 (Oct. 1990).
7. F. C. Robey, D. R. Fuhrmann, E. J. Kelly, and R. Nitzberg, "A CFAR adaptive matched filter detector," IEEE Trans. Aerosp. Electron. Syst. 28(1), 208-218 (Jan. 1992).
8. C. D. Richmond, "Performance of the adaptive sidelobe blanker detection algorithm in homogeneous environments," IEEE Trans. Signal Process. 48(5), 1235-1247 (May 2000).
9. D. Manolakis, M. Rossacci, J. Cipar, R. Lockwood, T. Cooley, and J. Jacobson, "Statistical characterization of natural hyperspectral backgrounds using t-elliptically contoured distributions," Proc. SPIE 5806, 56-65 (2005).
10. S. M. Kay, Fundamentals of Statistical Signal Processing, Prentice Hall, Englewood Cliffs, NJ (1998).
11. D. Manolakis, D. Marden, and G. Shaw, "Target detection algorithms for hyperspectral imaging application," Lincoln Lab. J. 14(1), 79-116 (2003).
12. J. P. Kerekes and J. E. Baum, "Spectral imaging system analytical model for subpixel object detection," IEEE Trans. Geosci. Remote Sens. GE-40(5), 1088-1101 (May 2002).
13. C. Rozell and D. Manolakis, "Matched filter performance for unequal target and background covariance matrices," Proc. SPIE 5425, 109-117 (2004).
14. D. Marden and D. Manolakis, "Modeling hyperspectral imaging data using elliptically contoured distributions," Proc. SPIE 5425, 558-572 (2003).
15. D. Marden and D. Manolakis, "Statistical modeling of hyperspectral imaging data and their applications," Tech. Rep. HTAP-16, Lincoln Laboratory, MIT, Lexington, MA (2004).
16. K. T. Fang, S. Kotz, and K. W. Ng, Symmetric Multivariate and Related Distributions, Chapman and Hall, New York (1990).