Fusion of Infrared and Visible Image Based on Target Regions for Environment Perception

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Abstract:

Infrared and visible image fusion is an important precondition to realize target perception for unmanned aerial vehicles (UAV) based on which UAV can perform various missions. The details in visible images are abundant, while the target information is more outstanding in infrared images. However, the conventional fusion methods are mostly based on region segmentation, and then the fused image for target recognition can’t be actually acquired. In this paper, a novel fusion method of infrared and visible image based on target regions in discrete wavelet transform (DWT) domain is proposed, which can gain more target information and preserve the details. Experimental results show that our method can generate better fused image for target recognition.

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589-593

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October 2011

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] Piella G. A General Framework for Multi-resolution Image Fusion: from Pixels to Regions. Information Fusion, 5(4): 259-280, (2003).

DOI: 10.1016/s1566-2535(03)00046-0

Google Scholar

[2] Liu K, Guo L, Li H, Chen J. Fusion of Infrared and Visible Light Images Based on Region Segmentation. Chinese Journal of Aeronautics. 22(9): 75-80, (2009).

DOI: 10.1016/s1000-9361(08)60071-0

Google Scholar

[3] Yin, S., Cao, L., Ling, Y. & Jin, G. One color contrast enhanced infrared and visible image fusion method. Infrared Physics & Technology, 53(2): 146-150, (2010).

DOI: 10.1016/j.infrared.2009.10.007

Google Scholar

[4] Hong L, He Z, Xiang J, Li S. Fusion of Infrared and Visible Image Based On Genetic Algorithm and Data Assimilation, Proc. of ISA 2009: 1-5. (2009).

DOI: 10.1109/iwisa.2009.5072875

Google Scholar

[5] Liu J, Wang Q, Chen Y. Comparisons of Several Pixel-Level Image Fusion Schemes for Infrared and Visible Light Images, Proc. of IMTC 2005, Ottawa, Canada: 2024-2027. (2005).

DOI: 10.1109/imtc.2005.1604528

Google Scholar

[6] Zhang X, Chen Q, Men T. Comparison of Fusion Methods for the Infrared and Color Visible Images, Proc. of ICCSIT 2009: 421-424. (2009).

Google Scholar

[7] Yao F, Sekmen A. Multi-source Airborne IR and Optical Image Fusion and Its Application to Target Detection. Proceeding of ISVC 2008, Part II, LNCS 5359, 651-660. (2008).

DOI: 10.1007/978-3-540-89646-3_64

Google Scholar

[8] Yao F, Shao G, Sekmen A et al. Real-time Multiple Moving Targets Detection from Airborne IR Imagery by Dynamic Gabor Filter and Dynamic Gaussian Detector, EURASIP Journal on Image and Video Processing, September, pp.1-22. (2010).

DOI: 10.1155/2010/124681

Google Scholar

[9] Xu S, Niu Y, Shen L, et al. Real-time Moving target detection method form unmanned airborne camera image. Computer Engineering, 36(s): 271-273. (2010) (in Chinese).

Google Scholar

[10] Burt P J, Kolczynski R J. Enhanced Image Capture through Fusion: Proceeding of the 4th International Conference on Computer Vision, Berlin, Germany, 5: 173-182. (1993).

DOI: 10.1109/iccv.1993.378222

Google Scholar

[11] Huang W, Jing Z. Evaluation of focus measures in multifocus image fusion. Pattern Recognition Letters, 28(4): 493-500. (2007).

DOI: 10.1016/j.patrec.2006.09.005

Google Scholar