Abstract
This paper describes the fusion of the airborne optical image and IR (infrared) image generated from a moving platform, and the target detection from the fused images. The proposed algorithm first detects the object from optical image and IR image, respectively. Then it performs the object mapping to determine parameters for image fusion. And then it fuses the optical image and IR image and detects the target from the fused images. The real-world videos generated from a helicopter are used to test this algorithm. The experiment results validate the proposed algorithm.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Burt, P.J., Adelson, E.: The Laplacian pyramid as a compact image code. IEEE Trans. Communications 31(4), 532–540 (1983)
Toet, A.: Image fusion by a ratio of low-pass pyramid. Pattern Recognition Letters 9(4), 245–253 (1989)
Burt, P.J.: A gradient pyramid basis for pattern-selective image fusion, Society for Information Display. Digest of Technical Papers, 467–470 (1992)
Zhang, Z., Blum, R.S.: A categorization and study of multiscale-decompositionbased image fusion schemes. Proc. of the IEEE, 1315–1328 (August 1999)
Sadjadi, F.: Comparative Image Fusion Analysis. In: Proc. of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 (2005)
Sheikh, Y.A., Shah, M.: Trajectory Association across Multiple Airborne Cameras. IEEE Trans. Pattern Anal. Mach. Intell (accepted)
Yao, F.H., Sekmen, A., Malkani, M.: A Novel Method for Real-time Multiple Moving Targets Detection from Moving IR Camera. In: Proc. of ICPR 2008 (accepted)
Shi, J., Tomasi, C.: Good features to track. In: Proc. of 9th IEEE Conference on Computer Vision and Pattern Recognition. Springer, Heidelberg (1994)
Bouguet, J.Y.: Pyramidal Implementation of the Lucas Kanade Feature Tracker Description of the algorithm, Intel Corporation (2003)
Kim, H.Y., Araújo, S.A.: Grayscale Template-Matching Invariant to Rotation, Scale, Translation, Brightness and Contrast. In: Mery, D., Rueda, L. (eds.) PSIVT 2007. LNCS, vol. 4872, pp. 100–113. Springer, Heidelberg (2007)
Schikuta, E.: Grid-Clustering: A fast hierarchical clustering method for very large data sets, CRPCTR93358 (1993)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yao, F., Sekmen, A. (2008). Multi-source Airborne IR and Optical Image Fusion and Its Application to Target Detection. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89646-3_64
Download citation
DOI: https://doi.org/10.1007/978-3-540-89646-3_64
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89645-6
Online ISBN: 978-3-540-89646-3
eBook Packages: Computer ScienceComputer Science (R0)