Multistage infrared target detection

Optical Engineering

Volumn 42, Issue 9, 2003, Pages 2746-2754

  Chan, Alex Lipchen ^a   Der, Sandor Z ^a   Nasrabadi, Nasser M ^a  

^a U S ARMY RESEARCH LABORATORY   (United States)

Author keywords

Clutter rejection; Feature extraction; FLIR imagery; Generalized Hebbian algorithm; Multilayer perceptron; Target detection; Target recognition

Indexed keywords

ALGORITHMS; CLUTTER (INFORMATION THEORY); FEATURE EXTRACTION; IMAGE SENSORS; INFRARED IMAGING; MILITARY VEHICLES; MULTILAYER NEURAL NETWORKS; OBJECT RECOGNITION;

CLUTTER REJECTION; GENERALIZED HEBBIAN ALGORITHM; TARGET DETECTION;

AUTOMATIC TARGET RECOGNITION;

EID: 0142027733     PISSN: 00913286     EISSN: None     Source Type: Journal    
DOI: 10.1117/1.1593038     Document Type: Article

References (31)

1. B. Bhanu, "Automatic target recognition: state of the art survey," IEEE Trans. Aerosp. Electron. Syst. 22(4), 364-379 (1986).
2. B. Bhanu and T. Jones, "Image understanding research for automatic target recognition," IEEE Aerosp. Electron. Syst. Mag., pp. 15-22 (Oct. 1993).
3. M. A. Khabou and P. D. Gader, "Automatic target detection using entropy optimized shared-weight neural networks," IEEE Trans. Neural Netw. 11(1), 186-193 (2000).
4. Q. Zhao, J. C. Principe, V. L. Brennan, D. Xu, and Z. Wang, "Synthetic aperture radar automatic target recognition with three strategies of learning and representation," Opt. Eng. 39(5), 1230-1244 (2000).
5. W. M. Koch, M. M. Moya, L. D. Hostetler, and R. J. Fogler, "Cueing, feature discovery, and one-class learning for SAR automatic target recognition," Neural Networks 8(7/8), 1081-1102 (1995).
6. A. Bernardon and J. Carrick, "A neural system for automatic target learning and recognition applied to bare and camouflaged SAR targets," Neural Networks 8(7/8), 1103-1108 (1995).
7. M. Rubin, "Application of fuzzy ARTMAP and ART-EMAP to automatic target recognition using radar range profiles," Neural Networks 8(7/8), 1109-1116 (1995).
8. K. Ikeuchi, T. Shakunaga, M. D. Wheeler, and T. Yamazaki, "Invariant histograms and deformable template matching for SAR target recognition," in Proc. Computer Vision and Pattern Recognition, pp. 100-105 IEEE (1996).
9. R. Hecht-Nielsen and Y. T. Zhou, "VARTAC: a foveal active vision ATR system," Neural Networks 8(7/8), 1309-1321 (1995).
10. S. Ghosal and D. C. McKee, "Target detection in foveal ATR systems," in Proc. Computer Vision and Pattern Recognition, pp. 714-719, IEEE (1996).
11. M. V. Shirvaikar and M. M. Trivedi, "A neural network filter to detect small targets in high clutter backgrounds," IEEE Trans. Neural Netw. 6(1), 252-257 (1995).
12. D. Ruck, S. Rogers, and M. Kabrisky, "Multisensor fusion classification with a multilayer perceptron," in Proc. Int. Joint Conf. on Neural Networks, Vol. 2, pp. 863-868, IEEE (1990).
13. S. Rong and B. Bhanu, "Modeling clutter and context for target detection in infrared images," in Proc. Computer Vision and Pattern Recognition, pp. 106-113, IEEE (1996).
14. S. Rogers, J. Colombi, C. Martin, J. Gainey, K. Fielding, T. Burns, D. Ruck, M. Kabrisky, and M. Oxley, "Neural networks for automatic target recognition," Neural Networks 8(7/8), 1153-1184 (1995).
15. M. W. Roth, "Survey of neural network technology for automatic target recognition," IEEE Trans. Neural Netw. 1(1), 28-43 (1990).
16. R. P. Lippmann, "Pattern classification using neural networks," IEEE Commun. Mag., pp. 47-64 (Nov. 1989).
17. G. A. Carpenter, "Neural network models for pattern recognition and associative memory," Neural Networks 2, 243-257 (1989).
18. G. A. Carpenter, S. Grossberg, and C. Mehanian, "Invariant recognition of cluttered scenes by a self-organizing ART architecture: CORT-X boundary segmentation," Neural Networks 2, 169-181 (1989).
19. I. E. Dror, M. Zagaeski, and C. F. Moss, "Three-dimensional target recognition via sonar: a neural network model," Neural Networks 8(1), 149-160 (1995).
20. A. Ravichandran and B. Yegnanarayana, "Studies on object recognition from degraded images using neural networks," Neural Networks 8(3), 481-488 (1995).
21. P. Sajda, C. D. Spence, S. Hsu, and J. C. Pearson, "Integrating neural networks with image pyramids to learn target context," Neural Networks 8(7/8), 1143-1152 (1995).
22. I. T. Jolliffe, Principal Component Analysis, Springer-Verlag, New York (1986).
23. R. C. Gonzalez and R. E. Woods, Digital Image Processing, Addison-Wesley, New York (1992).
24. W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes in C, Cambridge University Press, New York (1992).
25. D. Torrieri, "A linear transform that simplifies and improves neural network classifiers," in Proc. Int. Conf. on Neural Networks, Vol. 3, pp. 1738-1743, IEEE (1996).
26. D. Torrieri, "The eigenspace separation transform for neural-network classifiers," Neural Networks 12, 419-427 (1999).
27. G. L. PLett, T. Doi, and D. Torrieri, "Mine detection using scattering parameters and an artificial neural network," IEEE Trans. Neural Netw. 8(6), 1456-1467 (1997).
28. P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman, "Eigenfaces vs. fisherfaces: recognition using class specific linear projection," IEEE Trans. Pattern Anal. Mach. Intell. 19(7), 711-720 (1997).
29. K. Etemad and R. Chellappa, "Dimensionality reduction of multiscale feature spaces using a separability criterion," in Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, pp. 2547-2550 (1995).
30. S. Fahlman, "Faster learning variations on back-propagation: an empirical study," in Proc. 1988 Connectionist Models Summer School, pp. 38-51, Morgan Kaufmann (1988).
31. S. Haykin, Neural Networks: A Comprehensive Foundation, 2nd ed., Prentice Hall, Upper Saddle River, NJ (1999).