Visible and Infrared Video Fusion Using Uniform Discrete Curvelet Transform and Spatial-Temporal Information

LI Qingping; DU Junping; XU Liang

doi:10.1049/cje.2015.10.016

Volume 24 Issue 4

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LI Qingping, DU Junping, XU Liang, “Visible and Infrared Video Fusion Using Uniform Discrete Curvelet Transform and Spatial-Temporal Information,” Chinese Journal of Electronics, vol. 24, no. 4, pp. 761-766, 2015, doi: 10.1049/cje.2015.10.016

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LI Qingping, DU Junping, XU Liang, “Visible and Infrared Video Fusion Using Uniform Discrete Curvelet Transform and Spatial-Temporal Information,” Chinese Journal of Electronics, vol. 24, no. 4, pp. 761-766, 2015, doi: 10.1049/cje.2015.10.016

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Visible and Infrared Video Fusion Using Uniform Discrete Curvelet Transform and Spatial-Temporal Information

doi: 10.1049/cje.2015.10.016

School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China

Funds: This work was supported by the National Basic Research Program of China (973 Program) (No.2012CB821200-2012CB821206), the National Natural Science Foundation of China (No.91024001, No.61070142), and the Beijing Natural Science Foundation (No.4111002).

Received Date: 2013-12-30
Rev Recd Date: 2014-02-21
Publish Date: 2015-10-10

Abstract

Abstract

Multiple visual sensor fusion provides an effective way to improve the robustness and accuracy of video surveillance system. Traditional video fusion methods fuse the source videos using static image fusion methods frame-by-frame without considering the information in temporal dimension. The temporal information can't be fully utilized in fusion procedure. Aiming at this problem, a visible and infrared video fusion method based on Uniform discrete curvelet transform (UDCT) and spatial-temporal information is proposed. The source videos are decomposed by using UDCT, and a set of local spatial-temporal energy based fusion rules are designed for decomposition coefficients. In these rules, we consider the current frame's coefficients and the coefficients on temporal dimension which are the coefficients of adjacent frames. Experimental results demonstrated that the proposed method works well and outperforms comparison methods in terms of temporal stability and consistency as well as spatial-temporal information extraction.
- Video fusion,
- Uniform discrete curvelet transform,
- Spatial-temporal information,
- Local spatial-temporal energy

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References(20)

References

Dong Jiang, Zhuang Dafang, Huang Yaohuan and Fu Jingying, "Advances in multi-sensor data fusion: Algorithm and applications", Sensors, Vol.9, No.10, pp.7771-7784, 2009.

Xu Xiaobin, Feng Haishan, Wang Zhi and Wen Chenglin, "An information fusion method of fault diagnosis based on interval basic probability assignment", Chinese Journal of Electronics, Vol.20, No.2, pp.255-260, 2011.

Zhang Xiuwei, Zhang Yanning, Guo Zhe, Zhao Jing and Tong Xiaomin, "Advances and perspective on motion detection fusion in visual and thermal framework", Journal of Infrared and Millimeter Waves, Vol.30, No.4, pp.354-360, 2011.

S. Denman, T. Lamb, C. Fookes, V. Chandran and S. Sridharan, "Multi-spectral fusion for surveillance systems", Computers & Electrical Engineering, Vol.36, No.4, pp.643-663, 2010.

G. Piella, "A general framework for multiresolution image fusion: From pixels to regions", Information Fusion, Vol.4, No.4, pp.259-280, 2003.

Jing Xiaojun, Zhang Bo, Zhang Jie and Zhong Mingliang, "A fusion scheme of region of interest extraction in incomplete fingerprint", Chinese Journal of Electronics, Vol.21, No.4, pp.663- 666, 2012.

O. Rockinger, "Image sequence fusion using a shift-invariant wavelet transform", Proc. of International Conference on Image Processing, Santa Barbara, CA, pp.288-291, 1997.

G. Pajares and J.M. Cruz, "A wavelet-based image fusion tutorial", Pattern Recognition, Vol.37, No.9, pp.1855-1872, 2004.

I. De and B. Chanda, "A simple and efficient algorithm for multifocus image fusion using morphological wavelets", Signal Processing, Vol.86, No.5, pp.924-936, 2006.

M.N. Do and M. Vetterli, "The contourlet transform: An efficient directional multiresolution image representation", IEEE Transactions on Image Processing, Vol.14, No.12, pp.2091- 2106, 2005.

I.W. Selesnick, R.G. Baraniuk and N.G. Kingsbury, "The dualtree complex wavelet transform", IEEE Signal Processing Magazine, Vol.6, No.22, pp.123-151, 2005.

T.T. Nguyen and H. Chauris, "Uniform discrete curvelet transform", IEEE Trans. Signal Process, Vol.58, No.7, pp.3618-3634, 2010.

Liu Congyi, Jing Zhongliang, Xiao Gang and Yang Bo, "Feature-based fusion of infrared and visible dynamic image using target detection", Chinese Optics Letters, Vol.5, No.5, pp.274-277, 2007.

Liu Kun, Guo Lei and Chen Jingsong, "Seqence infrared image fusion algorithm using region segmentation", Infrared and Laser Engineering, Vol.38, No.3, pp.553-558, 2009.

Wang Meng, Dai Yaping, Liu Yan and Tian Yanbing, "Feature level image sequence fusion based on histograms of oriented gradients", Proc. of IEEE International Conference on Computer Science and Information Technology (ICCSIT), Chengdu, China, pp.265-269, 2010.

A. Malviya and S.G. Bhirud, "Visual infrared video fusion for night vision using background estimation", Journal of Computing, Vol.2, No.4, pp.66-69, 2010.

A.L. Chan and S.R. Schnelle, "Fusing concurrent visible and infrared videos for improved tracking performance", Optical Engineering, Vol.52, No.1, DOI: 10.1117/1.0E.52.1.017004, 2013.

E.P. Bennett, L.M. John and M. Leonard, "Multispectral bilateral video fusion", IEEE Trans. On Image Processing, Vol.16, No.5, pp.1185-1194, 2007.

T.D. Dixon, S.G. Nikolov, J.J. Lewis and J. Li, "Task-based scanpath assessment of multi-sensor video fusion in complex scenarios", Information Fusion, Vol.11, No.1, pp.51-65, 2010.

V. Petrovic, T. Cootes and R. Pavlovic, "Dynamic image fusion performance evaluation", Proc. of IEEE International Conference on Information Fusion, pp.1-7, 2007.

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